We tend to think the solution to a complicated problem is more.

More engineering. More technology. More of whatever solved the last problem.

We rarely step back and look at the actual problem in front of us. Instead, we grab the toolkit that worked last time and force it onto whatever we’re facing now.

As Abraham Maslow wrote in 1966, “it is tempting, if the only tool you have is a hammer, to treat everything as if it were a nail.”

We’ve become a hammer that sees everything as a nail.

We Doubled Human Lifespan in a Century

Make no mistake about it, medicine has been the most remarkable achievement of mankind. Through it, we have conquered much of what killed us for millennia. Even over the last 500 years we have seen our lifespan double, and medicine is almost entirely responsible.

That jump from roughly 35 years to roughly 80 comes down to a handful of critical advances: our understanding of infectious disease, anesthesia, surgery, and imaging technology.

A quick look at the timeline shows exactly how a handful of breakthroughs drove that shift.

In the 1500s, global life expectancy sat somewhere in the early-to-mid 30s, and that number is misleading on its own. It was dragged down by infant mortality, infectious disease in young children, accidents, and starvation. Infant mortality rates in the 1500s ran as high as 30–50%, meaning nearly half of the people born on the planet didn’t survive their first year.

Life expectancy barely moved between the 1500s and the 1900s, hovering between 30 and 40 for four straight centuries.

Most early deaths came from the same handful of causes: women and children dying in childbirth, infant mortality from infection or accident, and other deaths that antibiotics, minor surgery, or basic emergency medicine would have easily prevented.

That started to change around the turn of the 19th century, when a string of advances in biology and medicine began addressing the leading causes of death directly.

In 1796, the first vaccine protected people against smallpox, one of the deadliest viruses of the era.

In 1861, germ theory was formalized, kicking off the revolution in our understanding of infectious disease.

In 1846, anesthesia arrived and modern surgical technique began to develop alongside it. In 1867, antiseptic technique entered hospitals broadly, cutting the transmission of infectious disease in clinical settings.

In 1928, Alexander Fleming discovered penicillin and opened the antibiotic era.

In 1960, mass vaccination against measles, mumps, and rubella rolled out across much of the developed world and drove the burden of those diseases way down.

Together, these advances knocked out most of the reasons people died young: childbirth complications and infection, infant mortality from disease, viral and bacterial infections, untreated trauma, and the gaps that broader public health initiatives closed.

We extended lifespan by preventing our environment from killing us, and it worked remarkably well.

Between 1870 and 2000, life expectancy climbed from roughly 35 to almost 80. We doubled our lifespan as a species in a little over a century. But that gain had less to do with making people healthier and more to do with removing the causes of early, preventable death: antibiotics, vaccination, surgery, emergency medicine.

We used acute interventions to solve acute problems.

Still Swinging the Same Hammer

Treating acute problems with acute interventions un-bottlenecked human lifespan from its biggest constraint: early mortality.

For decades, life expectancy climbed almost in a straight line. Then, in the late 20th and early 21st centuries, that growth slowed, stalled, and in some places started reversing.

That stall came with a second shift: the leading causes of death changed. Infectious disease, infant mortality, and accidents gave way to a new class of conditions: cardiovascular disease, diabetes, cancer, lung disease, and the broader category we’d eventually call chronic disease.

These diseases have completely different underlying mechanisms, but we’ve leaned on the same playbook for all of them: find the disease, find the intervention, cure it. Treat every problem like an acute medical event and reach for a drug, a surgery, or a procedure.

That approach has produced small gains in some conditions, but life expectancy has hit another bottleneck. It’s there because we’re still swinging the hammer of traditional medicine at a problem that doesn’t look anything like a nail. The bottleneck comes down to a basic confusion: treating disease and health as the same concept.

For the reasons we actually die in the 21st century, the story of modern medicine is a story of misreading the data. Of staying committed to the wrong path. Of being a hammer and treating everything like a nail.

Conventional Medicine Was Built for Your First 40 Years... or Acute Crises

Understanding where we need to go starts with understanding where we are. That means looking at how modern medicine sees the human body, and how we define health in the most conventional sense.

Conventional medicine runs on a disease-cure, pathology-first model. Medical training, at least the allopathic pipeline, is built around understanding normal physiology and pathophysiology: how disease and injury cause functional and biochemical change in the body.

Its job is to identify disease states and return the body to normal working condition. Summed up, conventional medicine looks like this:

• Disease Centric

• Treatment Focused

• Surgical Intervention

• Acute Intervention

• Symptom Management

• Drug Based Prevention

• Chronic Disease Management

• Return to Normal

This model is genuinely powerful in the right circumstances, the ones we just covered. But map it against longevity and true health across a full lifespan, and it only covers a narrow slice of what we actually need. Conventional medicine maps almost perfectly onto the medical needs of our early decades.

From birth to roughly age 35–40, the acute and critical care approaches line up almost perfectly with what actually threatens our health. In those decades, the reasons we deviate from ideal health, or die, are mostly infectious disease, genetic disorders, accidents and trauma, or freak events like an aortic dissection or an early cancer. That’s exactly what conventional medicine was built to handle.

Push into our 40s and beyond, and that fit breaks down. Age-related sarcopenia, obesity, neurocognitive decline, heart failure: none of these respond directly to conventional treatment (in any meaningful way). The best conventional medicine can do is manage symptoms and extend life: digitalis for heart failure, stents for blocked arteries, supplemental oxygen or a ventilator to keep the body running.

That’s not medicine that improves health. It’s medicine that reduces disease burden enough to keep someone alive longer.

Conventional Medicine Was Never Built to Treat Aging

Here’s the short version: conventional medicine was remarkably effective at curing acute disease, and it extended our lifespan by keeping our environment from killing us. That effectiveness created a brand-new problem. Instead of building a new solution for it, we tried to force that new problem into the old solution box.

The new problem introduced by extending our lifespan past 30 is biological aging. Look at the top nine causes of death:

1. Heart Disease

2. Cancer

3. Accidents

4. Stroke

5. Chronic Lung Disease

6. Alzheimer’s

7. Diabetes

8. Kidney Disease

9. Chronic Liver Disease

Of those nine, only one, accidents, falls under what conventional medicine was built to address. The other eight are deaths related to chronic disease and biological aging.

Conventional medicine was born out of the disease model of health, and it succeeded at preventing early death from infection, accident, and genetic disorder.

But solving the early-life problems gave us the wrong answers for the later-life ones. As a society, we’re leaning on a system to solve problems it was never built to solve.

This isn’t just a problem. It’s the fundamental problem.

We’re no longer dying from the reasons medicine was designed to solve. We’re dying from biological aging and things that accelerate that process (or put another way living lives in ways that accelerate it).

Plot the average age of onset for the most common modern diseases and the pattern is obvious. We live essentially disease-free until our late 30s or early 40s, then diseases start stacking up, one after another, until one or more of them eventually gets us. Our lives split cleanly into two phases: the disease-free years and the disease years.

The common explanation is that these are simply diseases of modern life: poor food quality, inactivity, health falling last on the priority list. But the evidence suggests aging itself drives these diseases, independent of lifestyle.

Some of the most compelling evidence for this comes from mummies. One study examined 137 mummies spanning nearly 4,000 years of history across five populations, from North America to South America to Africa to East Asia. About 34% showed signs of heart disease. The mummies with heart disease averaged 42 years old; the ones without it averaged 32.

Biological aging underpins most of the diseases we face today. Conventional medicine isn’t just ill-equipped to handle that, it’s looking at health through the wrong lens entirely.

Aging Starts With a Single Cell

Addressing aging isn’t about curing disease. It’s about understanding what health actually means, what drives aging, and how to slow or reverse it.

Slowing or reversing aging, and actually preventing the diseases that come with it, starts with the most basic question there is: what drives aging.

Aging begins with cellular senescence.

Cellular senescence is the process by which cells stop dividing, enter a state of growth arrest without dying, and start functioning far worse than they should.

Senescent cells carry damaged DNA, dysfunctional mitochondria, high oxidative stress, and a buildup of misfolded proteins that can’t carry out a cell’s basic functions. Think of them as the unhealthy version of our cells.

A handful of biological processes drive cellular senescence: cell division, oxidative stress, DNA damage, mitochondrial dysfunction, inflammation, and epigenetic change.

Cell division drives senescence through telomere shortening. In young cells, the ends of our chromosomes are capped with DNA-protein structures that protect our DNA and help control cell division, similar to the plastic caps on the ends of a shoelace.

Telomeres shorten with every cell division. As they shorten, they protect the DNA less effectively, until they become too short for the DNA to replicate at all. This process is well documented in human cells: most cells hit that limit after roughly 40–60 divisions.

Oxidative stress drives senescence through a few key mechanisms: it degrades functional proteins and accelerates DNA damage. Some of that damage gets repaired, but not all of it, and not completely, so it accumulates over time, the way scars accumulate and never fully heal. Oxidative stress also tends to rise with age, partly as a result of aging itself and partly because accumulated damage begets more oxidative stress.

DNA damage accumulates with age for two reasons. First, the proteins that repair our DNA get less effective as we age. Second, we keep accumulating new damage from oxidative stress, UV exposure, and inflammatory stress. Those two factors feed each other. DNA gets damaged by UV exposure, inflammation, or a simple copying error. Our repair proteins fix about 99.999% of it. What’s left gets damaged again, repaired again to 99.999%, but each repair is a little less perfect than the last. Over time, those imperfect repairs pile up until the genes coding for our DNA repair systems themselves start accumulating errors, which makes the repair systems less effective, which lets more damage through. The loop continues until the cell can’t keep up with the damage and becomes senescent.

Senescence is the leading cause of age-related disease. Dig deep enough into any of the leading causes of death and you’ll find the accumulation of senescent cells in a specific organ, tissue, or system.

Senescence has been directly linked to nearly every major age-related disease: neurodegeneration, cardiovascular disease, osteoporosis, sarcopenia, diabetes, cancer, arthritis, kidney disease.

That accumulation tracks almost exactly with how we accumulate age-related disease. In our first 30–40 years, close to 85% of us have zero age-related disorders. After 40, that number starts climbing fast: by 80, 95% of us have at least one, and most of us have three or more.

Senescence drives disease, and we know what drives senescence, mostly the same processes that come with aging itself. But each of those drivers can be slowed, and in some cases reversed. Specific interventions can activate telomerase and restore telomere length. Others can boost antioxidant capacity to blunt oxidative stress, or strengthen DNA repair protein activity and its resilience to degradation.

Where those senescent cells accumulate determines what breaks. Build up in the vasculature and heart, and you get cardiovascular disease. Build up in muscle and bone, and you get sarcopenia and osteoporosis. Build up in the brain, and you get neurodegeneration. It’s the same underlying process wearing different clothes depending on which system it hits.

Senescence can be controlled. We just have to know how.

Wellness Is Built, System by System

The traditional model of health, shaped entirely by conventional medicine, doesn’t capture the problem we’re actually facing as a species today. It treats health as the absence of disease: a baseline you fall away from and get pulled back to with a prescription once something breaks. That’s not health. That’s damage control.

Aging isn’t a fixed, uncontrollable process running on its own clock. It’s malleable. The same systems that decline with age also respond to demand, which means health isn’t something you preserve.

It’s something you build.

Even most of the science chasing longevity is still swinging the same hammer. Something like $20 billion has gone into pharmaceutical longevity research in recent years, nearly all of it aimed at one isolated molecular pathway at a time. Metformin’s longevity signal comes almost entirely from people who already have type 2 diabetes, where it cuts all-cause mortality by roughly 7% and cardiovascular disease by roughly 25%; in healthy animals, the data is a coin flip. Rapamycin extends lifespan in animal models, but the doses required in humans would halt growth before a person reached adult height. Both drugs are precise. Both hit exactly one pathway. Neither builds a body that adapts.

Real prevention doesn’t work pathway-by-pathway. It works system by system: cardiovascular, musculoskeletal, metabolic, cognitive, the major systems that actually determine how long, and how well, you live. And it’s built the same way the body has always been built: through demand. Diet and exercise aren’t lifestyle add-ons to real medicine. Applied deliberately, they are the intervention.

A single bout of exercise does something no drug has managed: it moves four independent mechanisms at once. It raises NRF2 activity and the antioxidant enzymes that clear oxidative stress. It increases DNA repair capacity and telomerase activity, the same telomere machinery we covered above. It reshapes DNA methylation patterns around metabolism and oxidative stress genes. And unlike a drug that stops working the moment you stop taking it, these effects persist into old age in people who stayed active their whole lives.

Take the cardiovascular system. Cardiorespiratory fitness, VO2 max, outperforms the Framingham Risk Score at predicting cardiovascular mortality. It isn’t a single biomarker. It’s the emergent output of cardiac output, lung capacity, vascular compliance, hematocrit, iron status, capillary density, and mitochondrial density, all working in concert. You can’t isolate one of those and call it fitness. You have to train the whole system, and the whole system responds.

Take the musculoskeletal system. People in the top quartile of muscle mass have roughly 20 to 50% lower all-cause mortality, and the advantage gets stronger after age 60. Skeletal muscle stores 80 to 85% of the carbohydrate you eat, which makes it one of the primary regulators of metabolic health, not just a structural tissue. It also produces myokines that move in opposite directions with age and exercise: irisin declines with age and rises with exercise, while myostatin rises with age and falls with resistance training.

Take the metabolic system. A body in energy balance at 1,500 kcal a day and a body in energy balance at 3,500 kcal a day can carry an identical body weight and tell you almost nothing about each other’s health. The high-flux body holds more enzymatic machinery for fatty acid oxidation and substantially greater glycogen storage capacity, built in a matter of weeks. Restriction alone moves in the opposite direction: in controlled studies, cutting energy intake looks good on paper, but the body compensates. Total energy expenditure drops, T3 and T4 drop, and activity-related energy expenditure quietly falls by 80 to 120 kcal a day within two years. Building metabolic capacity and starving it are not the same strategy, even when they produce the same number on a scale.

Take the cognitive system. It doesn’t decline in isolation either. Cardiovascular capacity determines how much oxygen and nutrient-rich blood reaches the brain, and metabolic flexibility determines how well the brain can fuel itself as glucose availability shifts throughout the day. Build the cardiovascular and metabolic systems, and cognitive resilience comes with it, not as a side effect, but as the same system doing what it was built to do.

Thermal stress adds another lever most people ignore entirely. Heat exposure triggers the heat shock protein response, HSP70 and its related chaperones, which help proteins fold correctly and clear the misfolded ones, the same kind of damage that drives cellular senescence. Cold exposure activates brown adipose tissue, improving energy expenditure and glucose handling. Repeated heat exposure has even been shown to build measurable performance tolerance over time.

None of this is generic. Two people can carry identical body weight, identical bloodwork on a standard panel, and completely different reserve capacity in their cardiovascular, musculoskeletal, and metabolic systems. Treating them the same is just a gentler version of the same mistake conventional medicine already makes.

This Is Healthcare 3.0

You can’t personalize what you don’t measure. Diagnostics and biometrics, the actual data on how each of a person’s systems is functioning, are what make it possible to build a plan around a specific body instead of an average one. Nutrition data and exercise data close the loop: they show whether the demand you’re placing on a system is actually producing adaptation, or just producing fatigue. That’s the difference between guessing and building.

Community is the other half, and it isn’t a soft add-on. The evidence linking social connection to mortality risk is as strong as almost anything in the public health literature, on par with the evidence against smoking. An intervention that doesn’t get sustained doesn’t work, no matter how well-designed it is on paper, and the single best predictor of whether someone sustains a hard behavior change is whether they’re doing it inside a community that expects them to show up.

This is what Healthcare 3.0 actually means: proactive instead of reactive, built system by system instead of chased pathway by pathway, personalized with real diagnostic and biometric data instead of prescribed off a population average, and sustained through community instead of willpower alone.

Diet, exercise, and community aren’t simply the soft, secondary tools of health. Applied with the right data behind them, they’re become the primary ones.

Get that right, and it moves us away from accelerated neurodegeneration, cardiovascular disease, osteoporosis, type II diabetes, and accelerated sarcopenia, and toward high cognitive function, robust cardiovascular capacity, a strong and resilient skeleton, well-regulated metabolism, and strong, metabolically flexible skeletal muscle.

It creates real separation between chronological age and biological age, and it lets us add not just years to our life, but life to our years.

Anyway... that’s what we are working on. Follow our work at FITTR. It will be a long road, and we have a lot of work to do. But it is worth it.

• 10 years ago, food logging software was genuinely hard to build and sold for $400M. Today, you can get an open-access database and code up your own in a weekend.

• The algorithms for wearables were cutting-edge for a decade; now they are open access and can be implemented in days by amateurs with the right sensors.

• DNA-based health and nutrition recommendations used to require a $2,000+ test and a genetics lab relationship (23andMe raised hundreds of millions building that pipeline). Now consumer genotyping is a commodity API, and the interpretation layer (linking SNPs to traits) is mostly open literature anyone can wire up.

• Separately, even cars are now just commodities*, and people are really only paying for brand names.

These are just a few examples, but they highlight the key point: many businesses operate in a domain where commoditization is inevitable. From what I can tell, there are only a few ways to win in these situations:

1. Skip the race to the bottom on pricing and win on brand. Some of the most successful companies in history, and today, have adopted this strategy - they make the brand play. LVMH is perhaps the best example. They sell clothes at a huge markup ($400-1,000 for a T-shirt) because of their brand, not because of the quality of their clothes (they pay <$15 for the T-shirt).

2. Create an ecosystem, not singular products. Apple has won the consumer electronics commoditization game with this strategy. Yes, they have great design in their products, but the fact that they created an ecosystem around their products is what makes them valuable. If your MacBook, iMac, iPhone, Apple Watch, iPods, and television didn’t all connect seamlessly, would you pay the premium for all those products?

3. Build a community around it. Brand and ecosystem are part of building a community, but having an actual community matters as well. Most investors who think about unit economics miss the social aspects of business, and community is often what drives revenue for decades. If you have a community of users who galvanize around your business, you can step outside of commoditization and build loyal customers who buy from you, even when there is a cheaper alternative.

*Most cars have always been just commodities, but different manufacturers produced cars that looked and felt different for decades; now, they are all basically just the same (with some rare exceptions).

Whack-a-mole biology

The two most talked-about longevity drugs, metformin and rapamycin, illustrate the problem directly. Metformin’s longevity signal comes almost entirely from diseased populations, specifically people with type 2 diabetes, where it reduces all-cause mortality by around 7% and cardiovascular disease by around 25%. That study wasn’t designed to test longevity at all. It was designed to test glucose-lowering efficacy on mortality in diabetics. Using it as evidence that metformin extends life in a healthy person is a category error. The animal data doesn’t even agree with itself: some model organism studies show increased longevity, some show decreased, and there’s evidence it can worsen cardiac metabolic reprogramming in some models. Rapamycin has a harder ceiling. The doses that show benefit in model organisms would need to be given early enough and high enough in humans to halt growth before someone reaches adult height. Lower, later doses are speculation with no human data behind them, and the drug’s real, FDA-approved use, immunosuppression, comes with a mortality risk of its own in older, more vulnerable people: more infection deaths, not fewer.

That’s whack-a-mole in its purest form. Each compound hits one mole, one pathway, and either doesn’t touch the others or actively lets a new one out. A meaningful share of that $20B is going toward platforms built to find the next target, the next pathway, the next molecule. Even the platforms marketed as multi-target are still operating at the level of stacking individual molecules, not building a system.

Reductionism fails just as badly when the lever is “natural,” and that should worry this capital more than any single trial failure. A well-designed two-year trial put 53 people on a sustained caloric restriction and tracked body composition, energy expenditure, thyroid hormones, and oxidative stress markers against a control group. The intervention worked exactly as advertised on paper: about 9 kg lost, mostly fat, sustained through year two, with a meaningful drop in a urinary marker of oxidative stress. It tells you almost nothing about longevity. Total energy expenditure dropped, T3 and T4 dropped, and activity-related energy expenditure quietly fell by 80 to 120 kcal a day by year two. The oxidative stress marker was measured in urine, an end-product, not actual antioxidant activity or cellular damage, and a separate study using similar restriction found barely a flicker of change in the actual antioxidant gene machinery. The rate-of-living and free-radical theories of aging that justify caloric restriction as an anti-aging strategy don’t hold up well across species either. Smaller animals with higher metabolic rates often outlive larger, slower ones, and there’s no clean relationship between resting metabolic rate and lifespan within a species. Cutting calories in isolation produces a body that’s smaller and burns less energy. It does not produce a body that ages more slowly, and there’s a real argument it produces the opposite: metabolic downregulation that primes someone for future fat regain the moment restriction ends.

The brain-in-a-vat problem

This same mistake has a philosophical name, Dennett’s brain-in-a-vat problem, and it explains why whack-a-mole failure is structural, not incidental. Daniel Dennett’s argument about brain-in-a-vat scenarios isn’t about whether a simulated signal feels like the real thing. It’s an argument about tractability. To convince a brain that it’s embodied in the world, you don’t just need to feed it a plausible stream of signals. You need to generate the exact correct response to whatever that brain does next, for every possible thing it might do, indefinitely. The moment the brain reaches for something and the simulated world doesn’t respond the way a real world would, the illusion collapses. The space of possible actions a brain could initiate is effectively unbounded, and no finite simulator can pre-script the right response to all of it. Building a convincing vat isn’t just hard. It’s combinatorially impossible. You cannot enumerate every input in advance and hard-code a response to each one.

Your heart runs on exactly this kind of branching program, and it’s the clearest biological proof of the same point. Your heart has two distinct genetic pathways available to it: the fetal gene program, which runs before birth and drives constrictive, thickening growth, and the adult gene program, which takes over at birth and drives efficient, compliant growth. Exercise pushes the heart down the adult, adaptive path: the chambers enlarge, the walls stay thin and pliable, contractile force and blood volume per beat go up. Obesity and hypertension push the heart back toward the fetal program: the walls thicken and turn fibrotic, the chambers shrink, and the whole thing becomes stiffer and less efficient. Same DNA. Same two available programs. The outcome is decided entirely by which program the heart’s actual physiological situation calls for, and nobody scripted that choice in advance. The heart senses the specific demand it’s under and answers correctly, every time, because it’s in a live loop with whatever is actually happening to it.

A drug is a pre-written instruction. It doesn’t sense your specific physiological state and choose the correct one of many possible adaptive programs. It delivers the same molecular signal regardless of what your heart, your muscle, or your DNA repair machinery actually needs in that moment. This is what the investment thesis misses. Lifestyle inputs, real exercise, real nutrition, a real physical environment, aren’t a weaker version of a drug. They’re a fundamentally different kind of intervention. They put the organism back in a live loop that generates the correct, context-specific response across every system, every time, without anyone having to enumerate what that response should be in advance. No amount of capital replicates that mechanism by finding more targets, because more targets is still more script, and the problem was never a shortage of script.

Why lifestyle inputs drive full-system adaptation, and drugs don’t

Your own DNA makes this case most clearly, and DNA is about as far from “lifestyle” as biology gets. DNA integrity depends on at least four separable things: resistance to damage, capacity to repair damage once it happens, telomere length, and the epigenetic architecture that decides which genes get expressed. A single senolytic or peptide is built to move one lever, maybe two. Exercise moves all four at once, through the same general stress response. It increases NRF2 activity and the downstream antioxidant enzymes, superoxide dismutase, catalase, glutathione peroxidase, that make DNA more resistant to oxidative damage in the first place. It increases DNA repair capacity and resistance against oxidative damage to proteins in skeletal muscle. It increases telomerase activity after even a single session, and chronic training sustains that elevation, which is why physically fit people, including people with existing coronary disease, tend to carry meaningfully longer telomeres than sedentary people of the same age. It reshapes DNA methylation patterns specifically around metabolism, myogenesis, contractile properties, and oxidative stress resistance genes, in ways that persist into old age in people who stayed active their whole lives. One stimulus moves four independent mechanisms of genetic integrity simultaneously, in the same beneficial direction, because they were never actually independent to begin with. They’re different readouts of the same underlying adaptive response, one a molecule aimed at a single pathway structurally cannot produce.

Muscle tissue makes the same case from a different angle. Skeletal muscle is a quasi-endocrine organ that secretes myokines, and two of the best studied, irisin and myostatin, move in opposite directions with age and opposite directions again with exercise. Irisin, which improves insulin sensitivity and bone density, declines with age and rises with exercise. Myostatin, which suppresses muscle growth, rises with age and falls with resistance training. Muscle is simultaneously your largest glucose sink, storing 80 to 85% of the carbohydrate you eat, your primary lever for metabolic flexibility, and, through Wolff’s Law, the main driver of your skeletal loading and bone density. People in the top quartile of muscle mass have roughly 20 to 50% lower all-cause mortality, an effect that gets stronger, not weaker, after age 60. No pharmaceutical touches all of that at once. Resistance training does, by default, because the tissue was built to respond to real mechanical demand across every one of those functions at the same time.

Cardiorespiratory fitness is the cleanest clinical proof of this same principle. VO2 max isn’t measuring one thing. It’s the emergent output of cardiac output, lung capacity, vascular compliance, hematocrit, iron status, capillary density, and mitochondrial density in your peripheral tissue, all working in concert. Impair any single piece and the number drops. That’s why it outperforms the Framingham Risk Score, a model built from discrete, isolated biomarkers, at predicting cardiovascular mortality, and why adding VO2 max to a standard blood panel improves its accuracy further. It’s a summary statistic for a whole system’s capacity, and the only way to move it is to build that whole system’s capacity, which is precisely what a molecule aimed at one node can’t do.

Metabolic capacity works the same way. A body in energy balance at 1,500 kcal a day and a body in energy balance at 3,500 kcal a day can carry an identical body weight and tell you almost nothing about each other’s health. The high-flux body has more of the enzymatic machinery for fatty acid oxidation, more glucose-handling machinery, meaningfully more mitochondria, and substantially greater glycogen storage capacity, all built in a matter of weeks once real energy demand goes up. That capacity is what actually protects against the energy overload that drives insulin resistance in the first place. Eating less doesn’t build it. Asking more of your metabolism, repeatedly, builds the reserve capacity that isolated caloric restriction, or an isolated drug, was never structured to build.

Thermal exposure follows the identical pattern. Heat and cold stress activate the same Nrf2 antioxidant pathway that shows up in genetic reserve capacity, with the same episodic-stress-then-adaptation signature seen in exercise. Heat stress triggers the heat shock protein response, HSP70 and related chaperones that protect protein structure and cellular integrity under thermal load, and repeated heat exposure builds a measurable tolerance to that stress over time. Cold exposure activates brown adipose tissue, a genuinely thermogenic tissue in adult humans that was assumed for decades to matter only in infants, and recruiting it increases energy expenditure and improves glucose handling. I’ve published case data of my own showing that heat exposure builds a measurable running performance tolerance over repeated sessions. It’s one more environmental input the body knows how to translate into systemic capacity, using machinery a targeted drug was never designed to engage.

What this means for where the money is going

None of this is an argument against the science behind metformin, rapamycin, senolytics, or caloric restriction research. Understanding these mechanisms is genuinely valuable, and some of them may end up as legitimate adjuncts for people who already have a real physiological base to build on. My argument is narrower: none of these interventions are a substitute for building homeodynamic space, because none of them are built to handle the open-ended, contingent nature of what your body actually needs to respond to as you age. They’re pre-scripted answers to enumerated problems, in a domain where most of the problems can’t be enumerated in advance.

That’s the disconnect in that $20B. Some of these companies will generate a return, plenty of biotech does, on the back of a single approved indication, a licensing deal, an acquisition. That’s a fine business outcome. It isn’t the same thing as moving the needle on how long or how well people live, because the thing that actually moves that needle was never a molecule waiting to be discovered. It’s been sitting in exercise physiology and nutrition science for decades, and it doesn’t have a patent. Build a body that has to keep adapting: heavier loads, harder efforts, real thermal and mechanical demands from an actual physical environment. That’s not a supplement stack, and it’s not a platform. It’s the only intervention that has ever reliably rebuilt the thing all these biomarkers were only ever measuring in the first place.

P.S.

Articles may be coming less frequently as I am working on them as more long-form content to help crystalize the ideas I am working through as we built this new preventative health platform at FITTR.

References

Metformin and rapamycin

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Caloric restriction

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Cardiac gene programs (exercise vs. pathological hypertrophy)

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Genetic reserve capacity

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12. Kim SB, et al. Targeting of Nrf2 induces DNA damage signaling and protects colonic epithelial cells from ionizing radiation. Proc Natl Acad Sci U S A. 2012;109.

13. Radák Z, Kaneko T, Tahara S, Nakamoto H, Ohno H, Sasvári M, Nyakas C, Goto S. Exercise training decreases DNA damage and increases DNA repair and resistance against oxidative stress of proteins in aged rat skeletal muscle. Pflugers Arch. 2002;445(2):273-278.

14. Denham J, Sellami M. Exercise training increases telomerase reverse transcriptase gene expression and telomerase activity: a systematic review and meta-analysis. Ageing Res Rev. 2021;70:101411.

15. Krauss J, et al. Physical fitness and telomere length in patients with coronary heart disease: findings from the Heart and Soul Study. PLoS One. 2011;6:e26983.

16. Sailani MR, et al. Lifelong physical activity is associated with promoter hypomethylation of genes involved in metabolism, myogenesis, contractile properties and oxidative stress resistance in aged human skeletal muscle. Sci Rep. 2019;9:3272.

Muscle mass and myokines

17. Liu S, et al. Role of irisin in physiology and pathology. Front Endocrinol (Lausanne). 2022;13.

18. Yarasheski KE, Bhasin S, Sinha-Hikim I, Pak-Loduca J, Gonzalez-Cadavid NF. Serum myostatin-immunoreactive protein is increased in 60-92 year old women and men with muscle wasting. J Nutr Health Aging. 2002;6.

19. Walker KS, Kambadur R, Sharma M, Smith HK. Resistance training alters plasma myostatin but not IGF-1 in healthy men. Med Sci Sports Exerc. 2004;36.

20. Lenk K, et al. Exercise training leads to a reduction of elevated myostatin levels in patients with chronic heart failure. Eur J Prev Cardiol. 2012;19.

21. Murray B, Rosenbloom C. Fundamentals of glycogen metabolism for coaches and athletes. Nutr Rev. 2018;76:243.

22. Rozenberg S, et al. How to manage osteoporosis before the age of 50. Maturitas. 2020;138:14-25.

23. Watson SL, et al. High-intensity resistance and impact training improves bone mineral density and physical function in postmenopausal women with osteopenia and osteoporosis: the LIFTMOR randomized controlled trial. J Bone Miner Res. 2018;33:211-220.

24. Wang H, Hai S, Liu Y, Liu Y, Dong B. Skeletal muscle mass as a mortality predictor among nonagenarians and centenarians: a prospective cohort study. Sci Rep. 2019;9.

25. Srikanthan P, Karlamangla AS. Muscle mass index as a predictor of longevity in older adults. Am J Med. 2014;127.

26. Ruiz JR, et al. Association between muscular strength and mortality in men: prospective cohort study. BMJ. 2008;337:92.

27. McLeod M, Breen L, Lee Hamilton D, Philp A. Live strong and prosper: the importance of skeletal muscle strength for healthy ageing. Biogerontology. 2016;17:497.

VO2 max and cardiorespiratory fitness

28. Kang SJ, Ko KJ. Association between resting heart rate, VO2max and carotid intima-media thickness in middle-aged men. Int J Cardiol Heart Vasc. 2019;23.

29. LaManca JJ, Haymes EM. Effects of iron repletion on VO2max, endurance, and blood lactate in women. Med Sci Sports Exerc. 1993;25.

30. Acevedo M, et al. Cardiorespiratory fitness improves prediction of mortality of standard cardiovascular risk scores in a Latino population. Clin Cardiol. 2020;43:1167.

31. Gray BJ, et al. Cardiorespiratory fitness testing and cardiovascular disease risk in male steelworkers. Occup Med (Lond). 2017;67.

32. Gupta S, et al. Cardiorespiratory fitness and classification of risk of cardiovascular disease mortality. Circulation. 2011.

Energy utilization and metabolic reserve capacity

33. Coker RH, et al. The impact of exercise training compared to caloric restriction on hepatic and peripheral insulin resistance in obesity. J Clin Endocrinol Metab. 2009;94:4258-4266.

34. Koh JH, et al. Enhancement of anaerobic glycolysis - a role of PGC-1α4 in resistance exercise. Nat Commun. 2022;13:2324.

35. Fritzen AM, et al. Effect of aerobic exercise training and deconditioning on oxidative capacity and muscle mitochondrial enzyme machinery in young and elderly individuals. J Clin Med. 2020;9.

36. Haun CT, et al. Muscle fiber hypertrophy in response to 6 weeks of high-volume resistance training in trained young men is largely attributed to sarcoplasmic hypertrophy. PLoS One. 2019;14:e0215267.

37. Hoppeler H, Baum O, Lurman G, Mueller M. Molecular mechanisms of muscle plasticity with exercise. Compr Physiol. 2011;1:1383-1412.

38. Nielsen JN, et al. 5’-AMP-activated protein kinase activity and subunit expression in exercise-trained human skeletal muscle. J Appl Physiol. 2003;94:631-641.

39. Hume DJ, Yokum S, Stice E. Low energy intake plus low energy expenditure (low energy flux), not energy surfeit, predicts future body fat gain. Am J Clin Nutr. 2016;103:1389-1396.

Thermal stress and environmental exposure

40. Done AJ, Traustadóttir T. Nrf2 mediates redox adaptations to exercise. Redox Biol. 2016;10:191-199.

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43. Dahlquist DT, Dieter BP, Brotherhood J, Koehle MS. The effects of post-exercise sauna bathing on 5- and 10-km performance in university level track athletes: heat acclimation and running performance. J Sport Human Perf. 2023;11(1):13-22.

This isn’t a spiritual argument for kindness. It’s a strategic observation about how professional ecosystems actually work.

Over the course of my career, I’ve had intellectual property stolen. Business partnerships that turned predatory. People who came in with offers to help, extracted what they needed, and built competing versions of what we’d built together. Those things happened. They were real losses.

The long-game perspective changes how you respond. If you’re playing for one deal, one season, one relationship, then short-term maximization makes some sense. Squeeze the best terms. Win the dispute. Burn the bridge if it means the better outcome now.

If you’re playing for decades, that calculus inverts. Your reputation is the asset that compounds. The relationships you build become the infrastructure your future self will need. Burning a bridge to win a small battle is often the worst trade you can make, even when you win.

Repeat founders get funded even after losing their last venture. Not because investors reward failure. Because investors can evaluate whether the person acted with integrity, made reasonable decisions under difficult circumstances, and treated people well along the way. Sometimes timing beats you. Sometimes the market moves against you. A good founder who ran out of luck is a fundamentally different profile from someone who ran a bad ship.

The question that matters is this: if every person you’ve worked with were asked to describe you as a colleague, employer, partner, or competitor, what would they say? That reputation is built incrementally, across every interaction. You either build it genuinely or you don’t have it. The money will run out or stop mattering at some point, but your reputation stays.

A paper published in the Journal of Nutrition used data from the Nurses Health Study, a large prospective cohort that tracked diet and health outcomes from 1980 to 2011. The researchers specifically measured compliance with the dietary fat guidelines that were in force during that period: keep fat below 30% of total calories, saturated fat below 10%, and dietary cholesterol below 300 milligrams per day. They then categorized participants as compliant or non-compliant and tracked what happened to their BMI over time.

The results undercut both sides of the debate. Non-compliance was the norm in 1980, with fewer than 20% of the population meeting the fat guidelines. By 1995, compliance had climbed to around 50 to 60%, meaning roughly half the study population was actually following the advice. Then compliance fell back toward 25% by 2010. During that entire period, BMI increased across the board. Both the compliers and the non-compliers got heavier. The compliers saw mean BMI increase by about 10%. The non-compliers saw it increase by about 12%. Two different groups, same direction, almost the same magnitude.

That finding eliminates “following the guidelines” as the driver of the obesity increase. If the guidelines themselves were the problem, the people who followed them would have gotten meaningfully heavier than the people who did not. They did not. And if ignoring the guidelines was protective, non-compliers would have maintained their weight better. They did not do that either.

What the data does tell us is that single-nutrient guidelines, framed as a percentage of total calories, are largely ineffective at the population level. Keeping fat below 30% of calories says nothing about how many total calories you eat. A person consuming 5,000 calories per day can hit that target and still be dramatically overeating. The guidelines also say nothing about physical activity, food environment, sleep, stress, or the dozens of other factors that influence energy balance and body weight over decades.

The obesity increase across both compliant and non-compliant groups points to something bigger than dietary fat percentages. Environmental changes in how much we move, how much we sleep, how food is engineered and marketed, and how our work and social patterns have shifted, these are load-bearing contributors that nutrition guidelines alone cannot counteract.

The practical implication is that more specific and individualized nutrition guidance is needed. A recommendation expressed as a percentage of total calories has limited utility if it does not account for how many total calories a person should be eating in the first place. That calculation depends on body weight, age, activity level, and goals. Guidelines that ignore those variables are going to produce the exact kind of results this data shows: modest, inconsistent, and easily overwhelmed by everything else going on in people’s lives.

The problem is that the interpretation does not hold up when you look more carefully at the data.

The flaw is in how researchers define “zero drinkers.” Most studies lump two very different groups together: people who have never really drunk, and former heavy drinkers who have since quit.

Former drinkers carry accumulated health risks from years of heavy use. When they stop drinking and join the abstainer category, they inflate the risk for that group. The result is that zero drinkers look sicker than moderate drinkers, not because abstaining is harmful, but because a substantial portion of that group already has a history of alcohol-related damage.

Studies that separate former drinkers from lifelong abstainers or rare drinkers consistently show a more linear relationship: risk increases with each additional drink per day. The apparent protective effect of one drink per day largely disappears once you account for this.

Cardiovascular disease follows the same pattern. It is the leading cause of death in most developed nations, which means the all-cause mortality data mirrors it closely. More rigorous studies of homogenous populations with fewer former drinkers show a linear relationship between alcohol intake and cardiovascular risk. The suggestion that red wine offers extra protection through antioxidants like resveratrol has not been supported by sufficient evidence. All alcohol types appear to carry similar cardiovascular risk.

Liver disease is cleaner. The data here is more straightforward than either all-cause mortality or cardiovascular disease. Any level of alcohol intake increases your risk of liver disease, particularly cirrhosis. The risk is relatively small at around one drink per day, roughly a 10 percent increase. At two to three drinks per day, that risk jumps by approximately 300 percent.

The dose-response relationship is essentially exponential.

Alcohol and cancer is the other area worth understanding. Alcohol increases the risk of cancers associated with the digestive tract in a roughly linear way: mouth, esophageal, stomach, gallbladder, and colorectal cancer all increase with alcohol intake. It does not meaningfully affect the risk of most other cancers, and despite some claims to the contrary, alcohol does not offer any protective effect against cancer.

So what does this mean practically? The risk from two or three drinks per week is fairly minimal. We are talking single-digit adjustments to risk. The story changes when you move to daily drinking or multiple drinks per day. That is where risk curves start to move meaningfully.

The takeaway is not that you need to eliminate alcohol entirely (you 100% can... my intake is closer to 0 than it is 2-3 per week which is already low). The takeway is that the idea of having a daily drink to protect your health is not supported by the evidence.

If you enjoy a drink occasionally, the risk is low.

If you are drinking daily under the belief that it is somehow beneficial, that belief is probably worth revisiting.

REFERENCES

• Tian, Y. et al. Alcohol consumption and all-cause and cause-specific mortality among US adults: prospective cohort study. BMC Medicine 21, 208 (2023).

• Stockwell, T. et al. Do ‘Moderate’ Drinkers Have Reduced Mortality Risk? A Systematic Review and Meta-Analysis of Alcohol Consumption and All-Cause Mortality. Journal of Studies on Alcohol and Drugs 77, 185–198 (2016).

• Knott, C. S., Coombs, N., Stamatakis, E. & Biddulph, J. P. All cause mortality and the case for age specific alcohol consumption guidelines: pooled analyses of up to 10 population based cohorts. BMJ 350, h384 (2015).

• Leading Causes of Death. CDC (2024).

• Global health estimates: Leading causes of death. World Health Organization

• Simpson, R. F. et al. Alcohol drinking patterns and liver cirrhosis risk: analysis of the prospective UK Million Women Study. The Lancet Public Health 4, e41–e48 (2019).

Medicine taught us to measure disease. High glucose, elevated hs-CRP, high triglycerides, elevated blood pressure; in a very real sense, these are sick markers. They tell you something is going wrong.

They are the biological equivalent of a check engine light. Useful, certainly. But a check engine light only fires after the problem has already developed. It tells you nothing about how much road you have left.

We’ve built an entire healthcare system around sick markers, and almost nothing around health markers. We know what broken looks like. We have very little scientific or clinical vocabulary for what thriving looks like, and even less infrastructure for measuring it.

Health markers are different in a fundamental way. They don’t measure the absence of disease. They measure the presence of actual biological capacity: VO2 max, grip strength, lean mass relative to body weight, resting heart rate, heart rate variability, and fasting insulin. These tell you how much capacity your body actually has. And that capacity, it turns out, is one of the most powerful predictors of how long you live and how well you live while you’re doing it.

The predictive data on health markers is striking.

A 46-year follow-up study tracked individuals from middle age into late life and stratified them by VO2 max at around age 50. Those in the top 5% of cardiorespiratory fitness were more than twice as likely to be alive at age 80 compared to those in the bottom 5%, and about 50% more likely to be alive than those with an average VO2 max. Estimates from the broader literature suggest that maintaining high cardiorespiratory fitness can add 15-20 years of healthful, independent living. Another study found that every decline of ~5-7 mL/kg/min in VO2 max was associated with a 100% increase in all-cause mortality risk. Another found risk falls roughly 9% for every 1 mL/kg/min gained. These are not modest signals. They are among the largest effect sizes in the entire longevity literature.

The same pattern holds for strength and muscle mass. Grip strength is one of the best predictors of all-cause mortality in older adults, better in many analyses than conventional clinical risk factors like blood pressure or cholesterol. Low lean mass is independently associated with metabolic disease, cardiovascular mortality, and accelerated biological aging. These are hard predictors of hard outcomes.

Health markers don’t just add to the predictive picture — in many cases they outperform sick markers.

The Framingham Risk Score, one of the most widely used cardiovascular risk calculators, incorporates age, sex, blood pressure, total cholesterol, HDL, diabetes status, and smoking. It is accurate in roughly 65-80% of cases. Cardiorespiratory fitness models using VO2 max or MET-based proxies are accurate in roughly 70-90% of cases, without any blood-based biochemical data. When you add fitness metrics to standard biomarker panels, predictive accuracy improves further. A single performance measure of your body’s actual functional capacity tells you more about your future health trajectory than a standard lab panel does in most populations.

And every one of these markers is directly, dramatically modifiable through lifestyle.

A few months of structured aerobic training at moderate intensity can increase VO2 max by approximately 4 mL/kg/min. Map that back to the mortality data and it translates to roughly a 40% reduction in risk. Active individuals experience age-related declines in VO2 max at less than half the rate of their sedentary counterparts. Regular exercise lengthens telomeres, slows the epigenetic clock, and increases mitochondrial density. Resistance training builds lean mass, improves insulin sensitivity, and increases grip strength. These are not incremental lifestyle adjustments. They are fundamental interventions that change how your biology ages at a cellular level.

You cannot say the same about managing sick markers with medication. Lowering glucose pharmacologically is not the same as improving total metabolic capacity. Health markers only improve when the underlying system actually improves. You cannot fake a high VO2 max. You cannot medicate your way to strong grip strength or a favorable lean mass ratio. You have to build biological capacity to move these numbers and when you do, the whole system tends to improve along with them.

This is the shift we need to make in how we talk about health. Not just in clinical settings, but in gyms, in coaching programs, in the way we educate the public about what health actually means. Telling someone their cholesterol is “normal” is not the same as telling them they are healthy. Normal in a sick population is not a standard worth aspiring to.

The goal is not the absence of disease. The goal is the presence of health. Those are not the same target, and as long as we only measure sick markers, we will keep optimizing for the wrong outcome, and missing the most actionable signal we have.

He had struggled with severe obesity for years, well over 150 pounds above a healthy weight. He was successful, disciplined in other areas of his life, and genuinely motivated to make changes. But he could not crack it.

Then he had to relocate for work. He moved somewhere with better weather, walkable access to his office, grocery stores nearby, and a culture where physical activity was a normal part of daily life. Within a year, without dramatically overhauling his gym routine or going on any particular diet, he had lost 60 to 70 pounds.

I tell that story because it is an illustration of something the data shows repeatedly: your physical environment has an outsized influence on your health outcomes, and we systematically underestimate it.

The CDC obesity maps make this visible at a geographic scale. The states with the highest obesity rates, concentrated in a belt running through the South and Midwest, overlap almost perfectly with the states that have the lowest fruit and vegetable consumption, the highest sugar-sweetened beverage intake, the highest fast food consumption, the highest density of food deserts, and the lowest levels of physical activity. These are not random correlations. They track because the environment drives the behavior that drives the outcome.

Compare that to states like Colorado, Vermont, and California, where obesity rates are materially lower. Those places tend to have higher rates of physical activity, better access to fresh food, more walkable infrastructure, and cultures where being active is the default rather than the exception.

None of this is about assigning blame to people who live in difficult environments. It is about being honest about what is actually hard. If you have to drive 20 minutes to find fresh food, if there is no safe place to walk near your home, if your workplace culture does not support movement, you are fighting against structural forces that have nothing to do with discipline.

What this means practically is that environmental design should be a first-order consideration in health behavior change, not an afterthought. Before adding more rules to your diet or scheduling another workout, ask what about your environment is making the healthy choice harder. Sometimes the highest leverage move is as simple as rearranging what is in your kitchen, changing your commute, or picking a different grocery store.

And sometimes, like my client, the highest leverage move is bigger than that.

You can write down your core values. You can put them on the wall. You can reference them in all-hands meetings. None of that builds culture. What builds culture is what you actually do, every day, in the decisions that are easy to rationalize away. If you say honesty is a core value and then dodge a hard conversation with a client or an employee, the people around you notice. Not always consciously, but they notice. Culture is what people observe, not what they are told.

I have been in some version of a leadership role for over a decade, and the thing I did not fully appreciate early on is how much the personal bleeds into the professional. The people who work with you know more about how you operate outside the building than you might think.

The way you treat a server at a restaurant.

Whether you keep your commitments to friends.

What your actual habits look like.

This is not about performing virtue for your team. It is about recognizing that if you want to build an organization with a genuine culture, you have to be the person you are asking everyone else to be.

The same dynamic plays out in coaching. You cannot ask clients to make the hard behavioral changes while living in visible contradiction to those changes yourself. Clients are watching. They are pattern-matching on whether you actually believe what you tell them. A coach who talks about the importance of consistent training and recovery while clearly not applying those principles to their own life has already undermined their credibility in ways that no credential can repair.

In personal relationships, it works the same way. Telling someone you love them, that you are patient, that you are present, matters much less than actually being those things. Declarations of intent do not substitute for the behavior. They can even make things worse if the gap between the words and the actions is obvious.

The actionable piece here is not complicated. Before you make a decision, especially one you might rationalize as a personal matter, run it through one question: if the people I lead saw this, would it reflect what I am asking of them? That filter clarifies decisions quickly. It also, over time, closes the gap between who you say you are and who you actually are. That gap is what leadership is made of.

Grind 24/7.

No vacations in your 20s.

Make it rain.

Lamborghinis.

Private jets.

I’ll be honest. I did all that. Well… everything except the private jet.

And, it taught me a lot. I wouldn’t trade my experience for anything.

But there was one thing about the whole experience that I always wrestled with: generational wealth.

The main idea that circulated over the last 20 years was essentially this: build a business empire so you generate enough money that your kids, kids, kids, are financially set. Create a legacy of financial abundance.

In some aspects, this makes sense, especially in today’s world where education is effectively lifelong financial handcuffs, homes are becoming unobtanium for the average adult, and the whiplash of the public markets makes it scary to invest. Leaving the next generations of your lineage capital to navigate those hurdles in life is a huge gift and a blessing. But… I’m not sure that really is generational wealth. Mostly because I think we have sort of lost the plot of what capital is and what wealth is.

As I am about 18 months from exiting my 30s and entering my 40s I have started spending more time thinking about these ideas: legacy and generational wealth. The more I think about it, the more I think that just leaving capital to next generation is generational (un)wealth. Sure, it provides opportunity, access, and safety, but I think that is the lowest form of legacy.

In fact, I saw a video clip the other day where someone was speaking into the camera and they stated something to the effect of, “I can’t believe no one in my lineage ever just locked in and made and saved a whole bunch of money and created generational wealth.” My immediate thought was, “Instead of wishing for someone to hand you an easy life, why not wish for someone to have taught you how to create a life you are proud of.”

Here is what I think generational wealth means in my home: values, character, relationships, stewardship. These are the things I want to pass down to the generations that follow me. Admittedly, I think these things are harder and require more work than just leaving capital behind.

When I think about values, I think about things like teaching my kid(s) how to prioritize their health, be physically active, develop nutritional literacy, and develop financial literacy. I think about teaching them character traits like resilience, patience, kindness, generosity, and agency. I think about modeling great relationships in the home and the workplace; showing them conflict resolution and repair. I think about teaching them to be good stewards of their bodies, their minds, their talents, their energy, their local community, and in the end, their capital.

A pile of money without these things is just a pile of money. These things without a pile of money is a path to a great life. Both are a path to making a big impact with your life.

I think generational wealth is far more about values, character, relationships, and stewardship than it is about the starting capital you have in life.

What started as a year rooted in the intention of continued growth has quickly become a year of change. Admittedly, some of this change has been self-induced.

An initial change that was out of my control provided me an opportunity to execute a series of changes that I would have otherwise not executed.

Amidst these changes, I was presented with a weird opportunity: with a few small lifestyle adjustments, I could have effectively retired three decades early.

I spent a few weeks legitimately thinking about this as an option. The last two decades of my life have been a mad sprint… and I woke up one day this year realizing I could wrap it all up and fade into the background and live my life on my own terms, pretty much forever.

While I was chewing on this concept for a few weeks, I found myself sitting in my 1-year-old son’s nursery rocking him to sleep for the night. I was staring at a Lego rocket I had built while we were wiating for him to arrive. I built it to help decorate his nursery. The thought was to surround him with big ideas… to chase big dreams… to chase the stars. And here I was, actively thinking about letting some of my big dreams fade at the age of 38 to follow a path because it would be an easier life.

This internal conversation I was having with myself brought a lot of ideas to the surface. I began thinking about all the people i’ve known in my life and the dreams they shared with me when they were young… and how many of them let those dreams die a decade ago.

The professional sports careers they quit on when they got cut for the first time.

The business empire they let die after the second failed business.

The marathon they wanted to run but didn’t because of an injury during their first real attempt at training.

The girl they didn’t marry because they were afraid of rejection.

This has become one of the most predictable phenomena of humans. We start our lives with big dreams because we believe anything is possible. Then, slowly, over time, those dreams slowly die. We make choices that push them away and/or we accumulate evidence that those dreams are increasingly unlikely. But the reality is, dreams only become impossible once we stop pursuing them.

But first, we need to retire the old version of the idea. Because the popular conception of “set point” is almost certainly wrong, and replacing it with a more accurate framework is one of the most practically useful things you can do for your clients and for yourself.

The Problem With the Classic Version

The version of Set Point Theory most people have heard goes something like this: your body has a genetically predetermined weight, call it 165 pounds, or 210, or whatever , and your physiology will do whatever it takes to get back to that number.

This version is seductive because it feels like it explains something real. Clients do seem to gravitate toward certain weight ranges. Weight loss does tend to stall. Regained weight does seem to “find its way home.” But the predetermined-weight version of set point theory is both scientifically insufficient and practically useless, because if the set point is genetically fixed and immutable, there’s nothing to be done about it.

The better framing, the one supported by the actual evidence, is this:

Your body has systems that defend against changes in energy balance. Not a specific number on the scale. Not a predetermined body weight. Change itself is what the body resists.

This is a subtle but enormously important distinction. It means that if someone has spent years at 230 pounds, their body will resist moving away from 230. But if they successfully shift to 195 and maintain it, the biology begins defending 195. The “set point” isn’t a destiny, it’s a description of where your body is currently fighting to stay.

Why Individual Variation Is the Core Story

Before we get into the mechanisms, we need to sit with the most underappreciated fact in weight management science: the extraordinary variation between individuals in how they respond to the same intervention.

Look at the data from the Dansinger et al. 2005 study, which tested four popular diets Atkins, Zone, Weight Watchers, and Ornish head to head:

Figure 1: Individual weight change responses across four major dietary interventions. Dansinger et al. 2005

The spread here is staggering. Some people lost close to 30 kg. Others on the exact same diet gained weight. The average between diets was essentially identical, which is what most people take away from this study. But the real story is the range within any given diet. Same protocol, same duration, dramatically different outcomes.

This is not an outlier. The pattern repeats across every kind of intervention we’ve studied. When we look at GLP-1 agonists, some of the most powerful weight loss drugs ever developed:

Figure 2: Individual weight loss responses to GLP-1 agonists (left) vs placebo (right). Ryan et al. 2024

Even on semaglutide, some people lose 40% of their body weight. Others lose almost nothing or gain. The placebo group shows a similar variation in response… just right shifted.

When we look at deliberate overfeeding:

Figure 3: Individual fat gain responses to 1,000 kcal/day surplus overfeeding. Levine et al. 1999

Sixteen people. Same metabolic ward. Same 1,000 calorie surplus per day for eight weeks. Fat gain ranged from under 0.5 kg to over 4 kg. That is an 8-fold difference in response to identical conditions.

Here is the single most important conceptual takeaway from all of this data:

Variation in response to weight change interventions is a feature, not a bug, of human biology.

Your clients who struggle are not broken. Your clients who thrive are not simply more disciplined. They are expressing different underlying biology. Understanding that biology is what the rest of this article is about.

Reframing Set Point: Systems That Defend Energy Balance

The evidence clearly shows that our bodies do have regulatory systems that resist changes in body weight. Let’s walk through how those systems actually work.

The SGLT-2 Inhibitor Natural Experiment

One of the most elegant pieces of evidence for these systems came from an unexpected source: diabetes medication. SGLT-2 inhibitors work by causing the kidneys to excrete glucose in the urine — meaning patients lose roughly 200 calories a day without knowing it. They’re not dieting. They’re not exercising more. They simply have a hidden caloric drain they’re completely unaware of.

This made SGLT-2 inhibitors the perfect tool to study how the body responds to a covert energy deficit. And the results from Ferrannini et al. (2015) were quite interesting.

Figure 4: Observed vs. expected body weight loss (left) and the divergence between caloric intake and expenditure over time (right). Ferrannini et al. 2015

In the first 6–8 weeks, weight loss tracked almost perfectly with what the 200-calorie daily deficit would predict. But then something happened: weight loss stalled, and eventually stopped almost entirely. Total weight lost was only about 20–30% of what the physics of the deficit would have predicted.

What happened? The body increased food intake by almost exactly 200 calories per day. The participants weren’t doing this consciously. They weren’t “cheating.” Their biology detected the energy deficit and quietly dialed up hunger and food intake to match, over the course of several weeks. A second, larger study by Polidori et al. (2016) found nearly identical results on nearly identical timelines.

This is one of the clearest demonstrations we have that the body has active feedback mechanisms designed to restore energy balance when it detects a deficit. It does not respond immediately, and the response is not perfectly precise — but it is real, and it is powerful enough to substantially blunt the effect of an ongoing caloric deficit over time.

NEAT: The Primary Defense Against Surpluses

On the other side of the equation, how does the body handle caloric surpluses? It turns out it relies primarily on a single mechanism: increases in Non-Exercise Activity Thermogenesis (NEAT). NEAT encompasses everything you do physically that isn’t formal exercise: fidgeting, standing, walking to the kitchen, gesturing while you talk, posture adjustments. It seems trivial. It is not.

Leibel et al. (1995) demonstrated that deliberate overfeeding caused substantial increases in non-resting energy expenditure, on the order of 500–700 extra calories per day in some individuals. This wasn’t from going to the gym more. It was unconscious, spontaneous physical activity ramping up to burn off the surplus.

But the headline finding from the Levine et al. (1999) overfeeding study was about variation. The same 16 people described above showed wildly different fat gain responses to identical caloric surpluses. And the variable that explained nearly 80% of the variance in fat gain was changes in NEAT.

Figure 5: Relationship between change in activity thermogenesis (NEAT) and fat gain during overfeeding.

The correlation is r = -0.77. That is extraordinary for a single variable in human physiology research. People who increased their NEAT by 700 calories per day barely gained any fat. People who decreased their NEAT by 100 calories per day gained substantially. The difference between the highest and lowest fat gainers in the study amounted to roughly 45,000 calories across the 8-week period, the caloric equivalent of 12–13 pounds of body fat.

This suggests that the body’s main defense against energy surpluses is not a metabolic rate increase. It is not burning more calories at rest. It is moving more. And clearly, people differ enormously in how strongly this response activates.

The Fat Thermostat: Leptin and the Adipostat

Beyond the behavioral compensations (eating more, moving more or less), there is a hormonal axis specifically designed to regulate body fat mass. This is the leptin-hypothalamus system, often called the adipostat, or what I prefer to call the Fat Thermostat.

The story of its discovery is one of the most fascinating in metabolic science. In the 1950s, researchers discovered a genetically obese mouse strain with a mutation in the “ob” gene. A decade later, a second strain with a different “db” gene mutation appeared. By connecting the circulatory systems of these strains together with normal mice in a series of parabiosis experiments, researchers demonstrated that one strain was failing to produce a satiety-signaling protein, and the other was failing to receive it. The satiety signal was so potent that when one of the mutant mice overproduced it, it caused the connected normal mouse to die of starvation.

By the mid-1990s, that protein had been identified: leptin, produced by fat tissue itself. The logic is elegant. As fat mass increases, leptin rises, signaling the hypothalamus to reduce food intake, increase movement, and enhance thermogenesis. As fat mass falls, leptin drops, signaling the brain to eat more and move less. A true fat thermostat.

In people with genetic leptin deficiency, this system is catastrophically broken, and they develop severe obesity that is almost completely corrected with leptin replacement therapy. This proves the system can powerfully control body weight when it’s working.

The problem is that in common obesity, the system is working, but it isn’t working well. Leptin resistance, analogous to insulin resistance, develops, where the brain becomes less responsive to leptin’s signals despite high circulating levels. Multiple clinical trials of leptin therapy in people with common (non-genetic) obesity have failed to produce meaningful weight loss, precisely because the receptor-level signaling is impaired. Leptin levels are high; the message just isn’t getting through.

Importantly, leptin resistance does appear to partially resolve with weight loss, which is why leptin signaling may become more relevant after weight is lost, and why maintaining a lower body weight gets slightly easier over time for some people. However, this system alone is not driving the major variations in individual responses nor does it adequately explain why some people have a harder (or easier) time losing weight.

The Five Drivers of Individual Variation

So why do some people’s systems respond more aggressively than others? The evidence points to five key sources of biological and behavioral variation:

1. NEAT Adaptation — As shown above, NEAT response to both overfeeding and caloric restriction varies enormously between individuals. Some people’s activity thermogenesis barely budges; others shift by hundreds of calories per day spontaneously. This is likely the single largest driver of individual differences in weight change.

2. Appetite Adaptation — The SGLT-2 inhibitor studies showed that hunger responses to a caloric deficit vary in timing and magnitude. Some people’s hunger spikes quickly and powerfully; others maintain greater appetite suppression for longer.

3. Hormonal Adaptation — Ghrelin, the primary hunger-stimulating hormone, rises in response to weight loss — but how much it rises varies significantly between individuals:

Figure 6: Individual variation in ghrelin response to weight change. Greater weight loss is associated with greater ghrelin increase, but the relationship has wide scatter. Leidy et al. 2004

Some people lose 4 kg and see their ghrelin spike dramatically. Others lose the same amount and see a minimal response. This divergence in hormonal signaling likely explains much of why some people find dieting so physically uncomfortable while others find it manageable.

4. BMR Adaptation — Basal metabolic rate does decline with weight loss (beyond what’s explained by reduced body mass), but the degree of this adaptive thermogenesis varies between individuals. Research by Martin et al. (2022) demonstrated this variation directly, with some individuals showing large BMR drops and others showing minimal adaptation.

5. Adherence Decay — This is not purely biological, but it has biological drivers. The capacity to sustain behavioral change in the face of biological resistance (hunger, fatigue, cravings) varies between people. Dansinger et al. (2005) showed both that adherence scores were highly variable across participants and that adherence was one of the strongest predictors of actual weight loss outcomes.

Figure 7: The relationship between dietary adherence score and weight change. Higher adherence strongly predicts greater weight loss. Dansinger et al. 2005

Thrifty and Spendthrift: Two Ends of a Spectrum

Researchers have bucketed these patterns into two phenotypic extremes, termed “thrifty” and “spendthrift” metabolic responders. The work of Piaggi et al. (2019) characterized these phenotypes through how energy expenditure responds to both fasting and overfeeding:

Figure 8: Thrifty vs. spendthrift metabolic phenotypes energy expenditure responses to fasting and overfeeding. Piaggi 2019

The “thrifty” phenotype dramatically reduces energy expenditure when calories are restricted, and shows a muted metabolic response to surplus. They are efficient at conserving energy. Evolutionarily, this was probably an advantage in times of food scarcity. In an obesogenic environment with abundant food and reduced physical activity demands, it becomes a significant burden.

The “spendthrift” phenotype does the opposite they burn more energy during overfeeding and show a more modest suppression during restriction. They waste energy more readily in both directions. In a food-secure environment, this tends to make weight management easier.

The crucial point is that these aren’t two discrete categories. They’re the ends of a continuous spectrum. Every person sits somewhere along it and their position is determined by the composite of their NEAT adaptation, appetite signaling, hormonal response, and metabolic flexibility. Three different people expressing these drivers differently:

Figure 9: Individual variation across five key drivers of metabolic response. Three people showing different profiles of NEAT adaptation, adherence decay, BMR adaptation, appetite adaptation, and hormone adaptation.)

Person 1 might have minimal NEAT adaptation and strong hormonal adaptation to dieting but good adherence. Person 2 might have strong NEAT but powerful hunger responses. Person 3 might have high adherence capacity but significant BMR suppression. All three will have different experiences with the same intervention, not because any of them is failing, but because their underlying biological profiles differ.

Where Set Point Theory Breaks Down

Despite the reality of these regulatory systems, obesity rates have climbed inexorably for the last 50–70 years. If the body has all these defenses, why aren’t they working?

The answer is scale and duration. These adaptive mechanisms operate within a range, and they can be overwhelmed by sufficiently large or sufficiently persistent environmental pressures. Our current food environment delivers caloric inputs that are roughly 400–600 kcal per day higher than they were 50 years ago. Occupational physical activity has declined by 10–15% over the same period, representing an enormous reduction in baseline NEAT for the population. And these changes have been sustained for decades, not weeks.

The SGLT-2 inhibitor data showed that the body’s compensatory mechanisms kicked in and matched a 200-calorie deficit within about 8–10 weeks. But what happens when the surplus is 400–600 calories per day, sustained for years, in an environment specifically engineered to undermine satiety signaling? The systems are real, but they were not designed to handle this magnitude of sustained environmental pressure.

Furthermore, Set Point Theory in its simple form fails to account for different tissue types. Fat mass and muscle mass respond to entirely different stimuli — fat to energy balance, muscle to mechanical loading and hormonal signals. Adding 5 kg of muscle over several years of resistance training does not trigger the same energy balance defenses that adding 5 kg of fat would. The idea of a single “set point weight” ignores this fundamental tissue-level distinction.

Complexity Doesn’t Mean Unpredictability

Here is the piece that too many practitioners miss: the fact that biology is complex doesn’t mean it’s random. When you actually control all the key variables the variance collapses.

Figure 10: Predicted vs. actual body weight under controlled calorie restriction (left) and calorie surplus (right). When energy balance is tightly controlled, weight change becomes highly predictable. Thomas et al. 2014

When adherence is high and energy balance is measured, predicted weight tracks actual weight remarkably well. The the apparent unpredictability is largely a function of the uncontrolled variables, primarily NEAT adaptation and adherence decay.

This is the most practically important insight in all of this science. The complexity is real. But the levers that drive most of the variance, NEAT and adherence, are the same levers that are most modifiable through coaching.

What This Means in Practice

If you take one thing from this article, let it be this: your clients’ different responses to the same intervention are not necessarily character flaws, they are often variations in biological responses

So what does this mean in practice?

First, acknowledge the variance. Every client needs to understand going in that their trajectory will be their own. It will not look like their friend’s, or the before-and-after they saw on social media, or what the math says it “should” be. The reasons for this are complex but real, and they are modifiable. The client is not broken.

Second, pull the biggest levers. NEAT and adherence together explain the vast majority of individual variance in weight change outcomes. If you can find strategies that genuinely work for your specific client to keep daily movement high and dietary adherence sustainable — not just theoretically adequate, but actually sustainable for them — you will have addressed the factors that matter most. Be agnostic about the specific tools. Be relentless about the outcomes.

Third, reduce the noise. The hormonal adaptations, the BMR changes, the ghrelin responses are real and they matter. But they are largely outside a client’s direct control. Acknowledge them when relevant, so clients understand why they’re experiencing what they’re experiencing. But keep the focus on what can actually be changed.

The body does have systems that defend against changes in energy balance. Those systems are not a fixed prison. They are a biological landscape that varies by individual and can be navigated, with accurate information, appropriate expectations, and the right strategic focus.

That is what a properly understood Set Point Theory actually gives us.

Thirty-four percent of them had atherosclerosis. Not in a few isolated populations, in all of them, across cultures that had almost nothing in common. Importantly, the biggest predictor of the presence of atherosclerosis was age.

This finding tells us something important: chronic disease isn’t simply the product of bad modern habits. Its root cause is something deeper and more universal: biological aging itself. Biological aging is fundamentally about, for the lack of a better word, the accumulation of cellular damage (more on this in a minute). The accumulation of cellular damage that begins in your thirties and compounds quietly for decades, driving heart disease, cancer, dementia, and metabolic disease as its downstream consequences.

This process of aging and accumulation occurs. We can’t stop it. But we can alter the pace at which it occurs. How do we do that? Well, we have to understand the biology underpinning that accumulation. To do that, we need to take a brief detour to the history of modern medicine.

The Problem With the Triumph of Modern Medicine

Modern medicine achieved something genuinely extraordinary in the 20th century. Between antibiotics, vaccines, improved sanitation, and advances in surgical and emergency care, the leading causes of death shifted dramatically. Infectious diseases that once killed in childhood — tuberculosis, cholera, influenza, polio — were brought under control. Life expectancy climbed by decades across the developed world.

This was a triumph. But it was a triumph over a specific problem: early death from acute disease and infection. And the tools built to solve that problem were perfectly calibrated for it. Identify the pathogen. Eliminate the pathogen. Restore the patient to their previous state.

The problem is that solving that problem revealed a new one. When people stopped dying young from infectious disease, they began living long enough to die from something else entirely: the slow accumulation of biological damage that we now recognise as chronic disease. Heart disease, cancer, Alzheimer’s, type 2 diabetes, and kidney failure are conditions that emerge over decades of biological time, not in response to an acute insult, but as the downstream consequence of a process that has been quietly running since your thirties.

The medicine that triumphed over infectious disease is extraordinarily good at what it was designed to do: find the pathogen, eliminate it, and manage the acute crisis. But chronic disease doesn’t work that way. It doesn’t have a pathogen. It doesn’t present acutely. And by the time it has a name — “you have type 2 diabetes,” “you have early-stage atherosclerosis,” “you have mild cognitive impairment” — the biological process driving it has been accumulating for twenty years.

Managing the symptoms of that disease, once it has a name, is not the same as understanding what produced it. And understanding what produced it is the only way to do something meaningful about it before the name arrives.

What Aging Actually Is at the Cellular Level

Here is the thing most people don’t know, every major chronic disease of aging, such as heart disease, cancer, Alzheimer’s, type 2 diabetes, sarcopenia, and kidney failure traces back to a single upstream biological process. Not different processes for different diseases. One process, with different downstream expressions depending on which tissues are most affected.

That process is called cellular senescence. And understanding it properly is the most important thing you can learn about your own biology.

A healthy cell has a specific lifespan. It divides, performs its function, replicates accurately, repairs its own damage, and eventually — when it accumulates irreparable damage — undergoes programmed self-destruction, a process called apoptosis. The body clears the debris. The space is occupied by fresh, functional cells. This is the normal cycle.

Senescent cells are the failure mode of this cycle. A senescent cell is one that has stopped dividing, typically because it has accumulated damage beyond a threshold, but hasn’t died. Instead of destroying itself and making way for a healthy replacement, it lingers. Dysfunctional, consuming resources, and, critically, actively making the situation worse for every healthy cell around it.

The mechanism by which it does this is called the senescence-associated secretory phenotype, or SASP. A senescent cell releases a constant stream of inflammatory signals: cytokines, chemokines, proteases, and growth factors that degrade the tissue environment around it. These signals can trigger healthy neighbouring cells into senescence themselves. They suppress local tissue repair. They drive systemic inflammation. They create the conditions in which cancer, cardiovascular disease, and neurodegeneration become more likely.

Six Drivers, Compounding Over Decades

Cellular senescence doesn’t happen randomly. It’s driven by six distinct biological processes that accumulate over time, each one capable of pushing healthy cells toward the dysfunctional state. Understanding them matters not just intellectually, but practically — because each driver has known accelerants, and each driver has known interventions.

The crucial word for all six of these is rate. Each one proceeds at a speed that is not genetically deterministic. Each one has known accelerants: chronic stress, poor sleep, sedentary lifestyle, inflammatory diet patterns, excess adiposity, and smoking. Importantly, each one responds to deliberate biological intervention. You are influencing all six of these drivers right now, through how you're living. The question is whether that influence is working for you or against you.

You Are Not a Machine. This Works In Your Favor

There’s a deeply embedded mental model most people carry about aging, and it goes something like this: the body is like a car. It has a finite lifespan. Parts wear out. With good maintenance, you might extend the useful life, but fundamentally it degrades under use. The older it gets, the closer it is to the end.

This model is biologically false. And the fact that it’s false is the most practically important thing in this entire field.

When steel is repeatedly stressed over time, it experiences metal fatigue. The cyclic stress damages its internal structure at the atomic level, and it eventually fractures. This is why bridges and aircraft need regular inspection and retirement. Repeated stress makes machines weaker. That’s their nature.

Human biology operates on the opposite principle. When your bones are exposed to cyclic loading (the compressive forces of running, jumping, lifting), they don’t fatigue, they remodel. They become denser, stronger, and more resilient to future loading. When your heart is regularly stressed by sustained aerobic exercise, it doesn’t wear out; it grows more capable, with a larger stroke volume, more efficient energy use, and a lower resting heart rate. When your muscles are challenged against resistance, they don’t simply deplete; they hypertrophy, building new contractile tissue in response to the demand.

Repeated, appropriate stress makes biological systems more capable. This is called the stress-adaptation principle, and it is the entire foundation of building biological resilience deliberately. Unlike a machine, where maintenance can only slow decline, a human body can actually build new capacity at virtually any age, including well into the seventh and eighth decades of life.

Biological Resilience: Increasing Repair Capacity and Slowing Accumulation

Aging is inevitable. The slow march of entropy and the accumulation of biological damage happen no matter what you do. However, you can slow the rate of accumulation through two primary mechanisms: 1) You can improve your cell’s ability to repair themselves, and 2) you can increase their tolerance for accumulation. This is the concept I call Biological Resilience.

What does this mean in practice? It means building the total capacity of your biological systems to such a level that the inevitable accumulation of ageing-related damage crosses the threshold into disease much later than it would otherwise, or in some systems, perhaps not at all within a normal human lifespan.

Building Resilience Across Body Systems

We can target our cells and build their biological resilience by focusing on our body systems. Our body is organized as follows: cells, tissues, organs, systems. Fortunately for us, when we focus on a system, we ultimately end up targeting the cells. This is important because biological resilience is not necessarily a whole body thing; instead it is the result of the resilience of each of our primary biological systems. As such, our total biological resilience is the cumulative resilience of our independent systems. Below are a few examples of said systems.

Social Resilience: An Underappreciated “System”

What the Evidence Actually Shows: A Domain-by-Domain Case

The Cardiovascular Story

VO2 max — the maximum rate at which your body can use oxygen during sustained exercise — is the single strongest predictor of cardiovascular longevity in the literature. More predictive than blood pressure, cholesterol, or BMI. In sedentary individuals, it declines at approximately 1% per year after age 25. Over thirty years, that’s a 30% reduction in aerobic capacity — a sedentary 55-year-old with the cardiovascular system of someone 20 to 25 years older.

The research on moving from the lowest to the second-lowest quintile of aerobic fitness shows an approximately 50% reduction in all-cause mortality risk. That is a larger reduction than any pharmaceutical intervention currently available. And unlike statins, VO2 max improvement also builds cardiovascular reserve, mitochondrial density, capillary networks, endothelial function, and telomerase activity simultaneously.

The protocol is not complicated: sustained zone 2 aerobic training — the effort level at which you can hold a conversation but are genuinely working — for at least 150 minutes per week, supplemented by higher-intensity intervals that push the VO2 max ceiling. The cardiovascular system remains highly responsive to this stimulus throughout life, including deep into the seventh and eighth decade.

The Musculoskeletal Story

Most people think of muscle primarily as what makes you strong or athletic. The longevity literature has a different view: skeletal muscle is the body’s largest metabolic organ, accounting for approximately 70 to 80% of insulin-stimulated glucose uptake. More muscle means more glucose storage capacity, better insulin sensitivity, and directly lower metabolic disease risk. Less muscle — the condition called sarcopenia, which affects more than 27% of adults over 60 — is a direct driver of insulin resistance, type 2 diabetes, frailty, and dependence.

Muscle also functions as an endocrine organ. Contracting muscle releases signalling molecules called myokines — including BDNF, irisin, and IL-6 in its acute anti-inflammatory context — that regulate inflammation, support brain health, and modulate immune function. A muscle that doesn’t regularly contract doesn’t send those signals. Losing muscle doesn’t just weaken you. It quietly removes one of the body’s primary anti-aging communication systems.

The intervention is resistance training with progressive overload — consistently adding challenge over time — paired with protein intake sufficient to support muscle protein synthesis. The target in the longevity literature is approximately 1.6 to 2.2 grams of protein per kilogram of bodyweight daily, distributed across meals to maximise each anabolic signal. After about age 40, the anabolic response to protein becomes blunted by a process called anabolic resistance, which is why the protein targets in longevity nutrition are meaningfully higher than what was recommended when health authorities were primarily concerned with prevention of deficiency.

The Neurocognitive Story

One in three women will develop some form of dementia in their lifetime. One in six men. Alzheimer’s disease deaths have doubled over the past 25 years. And yet: approximately 35% of dementia risk is modifiable through lifestyle. More than any single dietary intervention. And in people carrying the highest-risk genetic variants (APOE ε4)physical activity reduces Alzheimer’s risk by 40 to 80%.

The biology of this is increasingly understood. Exercise promotes BDNF — brain-derived neurotrophic factor — which drives neuroplasticity, the formation of new synaptic connections. It activates neurogenesis in the hippocampus, the brain region first damaged by Alzheimer’s. It reduces amyloid burden. It improves the clearance of metabolic waste from brain tissue through the glymphatic system, a process that happens primarily during deep sleep, which is itself reduced by chronic sleep deprivation.

The cognitive implications of this are significant: sleep debt is not just fatigue. It is literally a failure to clear from the brain the amyloid plaques and tau tangles that accumulate as the primary pathological hallmarks of Alzheimer’s disease. Prioritising sleep is not a lifestyle preference. It is a nightly neurological maintenance protocol.

Convergence at the Cell

Here is what makes the longevity science both elegant and practical: every domain-level intervention (exercise, diet, sleep, stress management) operates through the same six cellular drivers. The cardiovascular adaptations of aerobic training aren’t separate from the cellular aging story. They are the cellular aging story. Exercise activates telomerase, promoting telomere maintenance. It drives mitochondrial biogenesis through a protein called PGC-1α, creating new, healthy mitochondria to replace the aging dysfunctional ones. It activates the endogenous antioxidant system through the hormesis principle: mild oxidative stress producing an adaptive upregulation that more than compensates for the immediate free radical generation.

The convergence extends further. The anti-inflammatory effects of the Mediterranean dietary pattern operate through the same cellular mechanisms as the myokine signalling of muscle contraction. Sleep’s role in DNA repair directly addresses Driver 3. Stress management’s effect on telomere preservation addresses Driver 1 through the cortisol-inflammation pathway. These are not parallel interventions that coincidentally produce similar outcomes. They are different routes to the same cellular targets.

This is also why the compounding logic of longevity practice is so important. Each of these interventions applied consistently over time produces exponentially larger effects than the same intervention applied sporadically, because all six drivers operate through accumulation. The direction of compounding is everything. A sedentary lifestyle compounds against you at the cellular level every day. A consistent exercise, sleep, and dietary practice compounds in your favour. The delta between those two trajectories, measured over a decade or two decades, is the difference between a 60-year-old body and a 75-year-old body at the same chronological age.

Epigenetic Age: The Number That Moves

One of the most practically significant developments in the biology of aging over the past decade is the epigenetic clock. By measuring the DNA methylation patterns (chemical modifications that sit on top of the genetic code and regulate which genes are active) at hundreds or thousands of specific sites across the genome, researchers have developed mathematical models that can estimate biological age from a blood or saliva sample.

These clocks — the Horvath Clock, PhenoAge (Levine), and the more recent DunedinPACE measure — are more accurate predictors of mortality and morbidity risk than chronological age alone. They capture the cumulative biological effect of everything that has happened to a cell’s regulatory machinery over a lifetime. And they respond to lifestyle change.

In multiple studies, sustained lifestyle interventions, consistent exercise, dietary improvement, stress management, and sleep optimisation, produce measurable reductions in epigenetic age. Not just improvements in biomarkers that correlate with biological age. Actual movement in the methylation patterns that define it. Biological age, properly understood, is not a fixed number. It can move in both directions. And the interventions that move it in the right direction are exactly the ones the rest of the evidence was already pointing toward.

What this means practically: hs-CRP levels, VO2 max trends, grip strength, telomere length, and epigenetic age tests are not abstract scientific measures. They are the gauges on your personal biological aging dashboard, and they respond to the same inputs that determine how you feel, how you perform, and how you function across the decades ahead.

The Practice: Building It Into a Life

Everything described above converges into a set of behaviours that are, individually, familiar to most people in principle. What longevity science clarifies is why they matter at the biological leve, and why consistency across all of them, simultaneously, produces effects that are substantially larger than any single intervention.

The irreducible core of a longevity practice looks like this. Aerobic training, at minimum 150 minutes per week, the stimulus that drives mitochondrial biogenesis, activates telomerase, improves endothelial function, and reduces the inflammatory burden simultaneously. Resistance training with progressive overload, at minimum two to three sessions per week, protecting musculoskeletal reserve, producing myokine signalling, supporting bone density, and maintaining the metabolic health that every other system depends on. A dietary pattern that is high in protein, high in whole-food polyphenols, low in ultra-processed foods and refined carbohydrates, the Mediterranean pattern is the most evidence-supported template, though the principles matter more than the specific label. Sleep, consistently, at a target of seven to nine hours, with consistent timing, the nightly DNA repair and amyloid clearance window that nothing else can substitute for. And deliberate stress management and social engagement, not because they’re nice to have, but because chronic cortisol is a proven accelerant of biological aging and social isolation carries a mortality risk comparable to heavy smoking.

What makes this framework different from the generic advice most people encounter is not the behaviours themselves. It’s the understanding of what they’re doing at the cellular level, and why that understanding changes both motivation and execution.

What Isn’t True Anymore

A few things that most people still believe, which the evidence has substantially moved on from:

That your lifestyle choices are just about risk reduction. They’re not. They are the primary biological inputs that determine the rate of your cellular aging, every day, at the level of telomere shortening, mitochondrial biogenesis, inflammatory load, and epigenetic modification. The choices you make today are not hedging against some future outcome. They are directly changing what is happening inside your cells right now.

That your family history determines your fate. It determines your risk level and tells you where to focus. APOE ε4 carriers who exercise regularly have lower dementia risk than many non-carriers who don’t. Family history is a signal about where your inherited biology is most vulnerable, which makes it a precise map for where deliberate lifestyle investment will produce the largest returns.

That it’s too late to start. The cardiovascular system, the musculoskeletal system, and the brain all demonstrate meaningful adaptive response to appropriate stress across the entire human lifespan. Studies on resistance training in people in their eighties produce measurable muscle hypertrophy. Studies on aerobic training in sedentary adults in their sixties produce measurable VO2 max improvement within weeks. The biology responds. The only question is whether you’re making the request.

That supplements are the leverage point. The biology of hormesis, mitochondrial biogenesis, and endogenous antioxidant upregulation makes clear that the most powerful inputs are behavioural, not pharmaceutical. This is not a dismissal of targeted pharmacological intervention where evidence supports it, statins, metformin, and GLP-1 agonists all have real evidence in longevity-adjacent applications (depending on context). But they work best as additions to the behavioural foundation, not replacements for it.

Tools

I developed a few online tools you can use to determine your longevity and your rate of aging. These are simply my interpretation of the data and turned into easily accessible tools, they are not clincally validated, but directionally and proportionally correct (in my opinion).

Longevity Calculator

Biological Age Calculator

References

Below is a non-exhaustive list of references used for this article. Additional papers were reviewed but these are the primary sources for many of the concepts.

Ancient populations & atherosclerosis

Thompson RC, Allam AH, Lombardi GP, et al. Atherosclerosis across 4000 years of human history: the Horus study of four ancient populations. The Lancet. 2013;381(9873):1211–1222. doi:10.1016/S0140-6736(13)60598-X

Cellular senescence & the biology of aging

López-Otín C, Blasco MA, Partridge L, Serrano M, Kroemer G. The hallmarks of aging. Cell. 2013;153(6):1194–1217. doi:10.1016/j.cell.2013.05.039

Epigenetic clocks

Horvath S. DNA methylation age of human tissues and cell types. Genome Biology. 2013;14(10):R115. doi:10.1186/gb-2013-14-10-r115

Levine ME, Lu AT, Quach A, et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY). 2018;10(4):573–591. doi:10.18632/aging.101414

Belsky DW, Caspi A, Corcoran DL, et al. DunedinPACE, a DNA methylation biomarker of the pace of aging. eLife. 2022;11:e73420. doi:10.7554/eLife.73420

VO2 max & cardiovascular longevity

Mandsager K, Harb S, Cremer P, Phelan D, Nissen SE, Jaber W. Association of cardiorespiratory fitness with long-term mortality among adults undergoing exercise treadmill testing. JAMA Network Open. 2018;1(6):e183605. doi:10.1001/jamanetworkopen.2018.3605

Sarcopenia & muscle as a longevity organ

Cruz-Jentoft AJ, Bahat G, Bauer J, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age and Ageing. 2019;48(1):16–31. doi:10.1093/ageing/afy169

Rantanen T, Harris T, Leveille SG, et al. Muscle strength and body mass index as long-term predictors of mortality in initially healthy men. Journal of Gerontology: Medical Sciences. 2000;55(3):M168–M173. doi:10.1093/gerona/55.3.M168

Dementia risk, physical activity & diet

Shih I-F, Paul K, Haan M, Yu Y, Ritz B. Physical activity modifies the influence of apolipoprotein E ε4 allele and type 2 diabetes on dementia and cognitive impairment among older Mexican Americans. Alzheimer’s & Dementia. 2018;14(4):462–472. doi:10.1016/j.jalz.2017.09.013

Samuelsson J, Najar J, Wallengren O, et al. Interactions between dietary patterns and genetic factors in relation to incident dementia among 70-year-olds. European Journal of Nutrition. 2022;61(2):871–884. doi:10.1007/s00394-021-02688-9

Iso-Markku P, Kujala UM, Knittle K, et al. Physical activity as a protective factor for dementia and Alzheimer’s disease: systematic review, meta-analysis and quality assessment of cohort and case–control studies. British Journal of Sports Medicine. 2022;56(12):701–709. doi:10.1136/bjsports-2021-104981

Dementia lifetime risk data

Seshadri S, Wolf PA, Beiser A, et al. Lifetime risk of dementia and Alzheimer’s disease. Neurology. 1997;49(6):1498–1504. doi:10.1212/WNL.49.6.1498

Brookmeyer R, Abdalla N. Estimation of lifetime risks of Alzheimer’s disease dementia using biomarkers for preclinical disease. Alzheimer’s & Dementia. 2018;14(8):981–988. doi:10.1016/j.jalz.2018.03.005

Telomeres & exercise

Ludlow AT, Zimmerman JB, Witkowski S, Hearn JW, Hatfield BD, Roth SM. Relationship between physical activity level, telomere length, and telomerase activity. Medicine & Science in Sports & Exercise. 2008;40(10):1764–1771. doi:10.1249/MSS.0b013e31817c92aa

Mitochondrial biogenesis & PGC-1α

Lira VA, Benton CR, Yan Z, Bonen A. PGC-1α regulation by exercise training and its influences on muscle function and insulin sensitivity. American Journal of Physiology — Endocrinology and Metabolism. 2010;299(2):E145–E161. doi:10.1152/ajpendo.00755.2009

Inflammaging

Franceschi C, Garagnani P, Parini P, Giuliani C, Santoro A. Inflammaging: a new immune-metabolic viewpoint for age-related diseases. Nature Reviews Endocrinology. 2018;14(10):576–590. doi:10.1038/s41574-018-0059-4

Note on Figure 3 sources: The specific risk-reduction percentages shown in Figure 3 (−23% for dietary intervention, −35% for physical activity, −40 to −80% for APOE ε4 carriers) are drawn from Samuelsson et al. 2022 and Shih et al. 2018. The broader meta-analytic literature (Iso-Markku et al. 2022) supports the direction and approximate magnitude of the physical activity finding; the specific figures should be treated as illustrative estimates from the cited source studies rather than pooled meta-analytic values.

Most entrepreneurs don’t think about the concept of creating valuable customers, or at least they don’t think about it from that perspective. They think about generating revenue and selling things with decent profit margins, and sometimes they think about ways to stand out from our competition. But what they don’t often think about is the fact that all these ideas can be boiled down to having highly valuable customers.

Warren Buffet understands this concept well, but he doesn’t use this term. Let’s take a quick look at his investment history, and I will show you that this is what he actually invests in.

Coca-Cola is one of his most famous investments. Buffet started accumulating stock in Coca-Cola in 1998 and increased his position until he owned 10% of the business by 1994, which he still holds today. He spent $1.2 billion to acquire this stock, which now pays him $750-800 million a year. Coca-Cola does this by creating valuable customers.

Does that seem like a strange thing to say? I mean it sells a cheap product in a highly competitive space. What if I spun those words and said things like “competitive moat” or “brand loyalty?” Would those resonate?

Think about how you choose to consume soft drinks. If you are like me, you have one or two soft drinks that you will drink and you will do almost anything to only drink that. For me, it is Coke Zero. I will occasionally order a Coke Zero when I am out at a restaurant. However, if that restaurant carries Pepsi products I will skip the soda entirely and just drink water. Think about that. Coca-Cola has created a customer in me who is so valuable that he will turn down the competitor even if they are the only option.

Still not convinced? Let me show you the data of Coca-Cola’s annual sales per customer.

It is estimated that the average adult in the United States drinks between 100 and 400 cans of a Coke product every year. Translate that over the course of a lifetime, and the average customer consumes 10,000 to 60,000 cans of a Coke Product in their lifetime. If you average $1 per can, that is $10,000 to $60,000 per customer.

Coca-Cola has built an amazing business creating valuable customers. It built valuable customers by creating a drink that people are fiercely loyal to and by making it incredibly difficult to compete with based on flavor and availability.

Entrepreneurs like you and me may not be building the next Coca-Cola, but we can borrow the core of what it does and instill that concept in how we think about building our business. We can create valuable customers.

Valuable customers are not found; they are created.

Give to Get

Creating valuable customers doesn’t start with a discussion about pricing or margins. While those things definitely matter and we will discuss them in detail, that isn’t where the discussion should begin. The discussion about creating valuable customers begins before they even spend a dollar with you.

Here is a secret about creating valuable customers: the value exchange begins with you. It begins with you giving almost everything before you ever get anything.

Before you collect a single dollar from a customer, if you can provide value to your potential customers and prepare them to be customers before they ever are, they are better customers and more likely to succeed with your service. You have equipped them to fit into your business and crush it.

Think of it like the NBA draft. You get to put all your potential customers through workouts before you draft them. You get a team of winners as customers by giving them 90% of what they need to succeed before they even walk in your door (virtually speaking).

Many of us have this idea that information alone is what people are looking for, and if you give them information, they will not buy your product. However, in reality, the exact opposite is true. Customers will utilize the information you give them to judge the credibility of your business and vet your ability to deliver on the promise you sell. Not only that, it prepares your clients to know exactly what to expect once they purchase.

In one businesses I owned, we provided one-on-one nutrition and fitness coaching at scale at around the $150-200 per month price point, which makes it accessible to a large audience. In this business, we run a free social media group that gives away all our “secrets.” We had free courses, calculators, tools, workouts, cookbooks, and we answered questions freely and openly whenever our audience asked. No information real information was behind a paywall. That business provided more than 2 million free ebooks, answered 3 million questions, and provided over 4 million free macro calculations via one of our online tools. This worked quite well for a long time in giving our potential clients insights into who we were, what we offered, and it also prepared them to get started as a client.

Imagine acquiring customers who have already done the initial work of onboarding themselves. Faster results. Less infrastructure. More efficiency. Greater profits.

The business Acquisition.com closely utilizes this concept through a completely different business model and at a completely different size of business. It is a private equity firm that acquires minority or majority positions in companies and helps them scale. They also focus very heavily on top-of-funnel media and education content and essentially give away their turnaround playbook online. They show businesses how to acquire leads, create compelling offers, and structure your business for growth. They use this content to help prepare potential businesses for eventually working with them. Not only do they get a much higher volume of deal flow, but they also attract companies that understand their language and philosophy and have instituted at least part of the playbook they, as the investment firm, are going to plug into the business they acquire. Again, faster results, less infrastructure, more efficiency, and greater profits.

Valuable customers are not found, they are created.

You make valuable customers by making them more informed customers first.

The Money Equation of Value

Now that we have acquired clients who skip the first few steps and are already aligned with our mission, it’s time to create the most amount of value for our customer and ultimately our business.

In business, value equals money. And the goal of any business is to make money. This means you have to charge money for the value you provide. While the goal of any business is to make money, the goal of a good business is to make profit. This means you have to charge more money for your service than it costs you to provide that service.

The goal of a great business is to deliver the most value possible to its customers while making the most profit. This means you have to charge enough money that your business earns enough to pour their heart and soul into every interaction with every customer every single day while also keeping the price at a point where the customer feels they are getting more value than the price they are paying.

There are countless books on pricing strategy and consumer psychology—how to use price anchors, why exact prices often outperform rounded ones, and other tactics designed to influence purchasing behavior. While these methods can be effective and certainly have their place, this article isn’t about those techniques. Instead, we’re going to zoom out and tackle a more fundamental question: how should you think about pricing in the first place? We’re not here to split hairs over whether to charge $97 or $100, or whether a three-tier pricing model should include $149, $169, and $189. Those are optimization questions for another day—if they ever truly matter. We are figuring out if we are charging $10 or $100,000 dollars. It’s about big-picture thinking, not micro-adjustments.

We need to think about price in orders of magnitude, not whether our price ends in a 7 or a 0. We are deciding whether we are selling Casio’s or Rolex Daytonas. We are solving the most fundamental pricing problem there is: what should we charge our clients so we can deliver insane value.

The sneaky truth about Rolex watches is that they are actually worse at keeping time than a $20 Casio. Things like temperature, your movement, magnets, and a host of other things actually make Rolex watches run fast and you have to adjust their time every few weeks or months. You buy a Rolex because of the narrative around value, not due to the intrinsic value of the watch.

We are not figuring out what other people are charging. We are not looking to our competition to set our price. We are figuring out what price we are going to charge.

Start With Value

The single best way to sell your service is to ensure that it is substantially more valuable than what you charge.

Value is not about what you, the business owner, perceive the value to be. Value is about what the consumer perceives the value to be. Just because you slap “valued at $997” on the sales page doesn’t make it worth $997.

One of the best pitches I have heard in my life was from an estate attorney I met with to talk about getting wills in place. He charged almost $500 an hour and said it would take about 10 hours to get our wills in place, which seemed a bit shocking to me at first. I literally asked him, “$5,000 to write some papers saying my money goes to my family when I die seems a bit insane, doesn’t it?”. His response to me was, “Sure, we can whip something up in ten minutes and file it with the state; just know that if we go the quick, cheap route, the tax bills on your estate will be astronomical. Just making sure that your 401k accounts are set up correctly will reduce the tax bill your kids or family will pay by about $700,000 dollars. I don’t know about you, but $5,000 seems like a small fee to save $700,000 in taxes”.

That is a 140x return. That is an offer so good that you have to say yes to it.

Another way to look at this is that it’s never about money and always about value. Let’s say I jumped on a call with a prospect for a $200-a-month service, and the client indicated they couldn’t afford $200 a month. It was just outside of their budget; they couldn’t swing it. Now, imagine in that conversation I told them that I had the keys to a $250,000 Ferrari that they could have for $20,000. That potential client would find a way to get $20,000 by calling a bank or a friend so they could buy that Ferrari and then probably sell it and make the $230,000 of value left in that situation. It is never about money. It is always about value.

The question now is, how do you create and determine value? Let’s stay consistent and break this down to a simple formula that has two parts: the solution and the magnitude of the problem. This means our formula looks like this:

Value = Solution X Magnitude of the Problem

Notice something very specific about this formula…there is a multiplication, not an addition sign. This is intentional. This is because there is leverage here.

Let’s start with the first component, the solution. This concept is relatively straightforward. The value of your offer or service is directly proportional to how completely you solve the problem. Let’s say you have an offer or a service that provides a 50% complete solution. This means that your solution gives you a 50% Every step you take away from a complete solution devalues your offer and your business.

Solution = Completeness of the Solution

This is why people are willing to pay $30,000 dollars for bariatric surgery but not willing to pay $200 a month for weight loss coaching. Surgery provides as close to a 100% solution as you can possibly get. On the other hand, a coaching offer that just gives someone an Excel sheet with a workout program and a grocery shopping list solves about 5% of the problem.

This is where you make meaningful business decisions on how you determine and set your value. If you want to control the value of your business you need to get as close to a 100% solution as possible. Completely solve problems with complete solutions.

The second component of this equation is the magnitude of the problem. This can either be incredibly straightforward or more nebulous. A great example of a straightforward value equation is a general contractor. Imagine you want to build a house, but you don’t know how a hammer works or what the difference between a speed square and a level is, so you have to hire it out. You call a general contractor who can build and deliver you a completely finished house and do 100% of the work. All you have to do is write the checks. That contractor has a 100% complete solution, and he will charge you the house’s market value (material + labor cost). If he builds a house worth $500,000, then he has provided a 100% solution to a problem that is worth $500,000 dollars. If he only provides you 50% of the house, he can only charge you $250,000 A more nebulous example is something like therapy or counseling. There is no real “market value” for mental health; the value is more arbitrary. In these situations, the value is something you must create in your potential customers’ mind through your brand, ads, copy, lead nurture, and sales process. Effectively, you control the narrative on value.

This means if you want to increase your value and your pricing, you have two options: either improve your solution or tackle a bigger problem. I believe that the most effective way to think about this value equation is to start by determining the magnitude of the problem you are solving and then developing the solution to that problem. Because even if you are not 100% on your solution percentage, you are at least setting the value of your product in the right order of magnitude.

Solve Bigger Problems, Make More Money

You make way more money by solving bigger-magnitude problems. That is just the way math works. Our value equation highlights this perfectly. You can squeeze every ounce of effort out of your business and go from 80% to 95% of a solution for a $10,000 problem, but you will always have a cap of $10,000. Eventually, you will have to go after larger-magnitude problems if you want to find a new level of success.

Eat, Sleep, Breathe Lifetime Gross Profit per Customer

Once you understand the true value of your product, the next most important thing to understand about pricing your product is Gross Margin and Lifetime Gross Profit per Customer. And I urge you to price it at a “scalable” level from the start because changing pricing once you have established an audience and a customer acquisition engine is one of the most emotionally draining experiences you can have as an entrepreneur (This is just one of my many battle scars).

Since we can’t know what our true customer lifetime value will be from day one, we have to make some assumptions when pricing initially and we can focus primarily on gross margins. If you run a true service-based business setting, your gross margin is relatively straightforward. Just figure out your cost of acquiring a client and what your cost of servicing your client is (all costs) and add those together. That is your true “cost of goods and services.” Now to set your price based on gross margin just divide your cost by what you want your gross margin (1-cost) to be, which will give you your price.

Here is an example of how this works. Let’s assume it costs you $75 to acquire a single customer and $100 to provide a complete service to that customer. Let’s also assume you decide to set your gross margins at 80%. This means that you need to price your offer at $875.

Cost Per Acquisition: $75

Cost to Service Client: $100

Ideal Gross Margin: 80%

Price = Cost of Goods Sold/(1-Gross Margin)

Price =($75 + $100)/(1-0.80)

Price = $875

Valuable customers are not found. They are created.

You make valuable customers by making them more informed customers first.

You create valuable customers by pricing appropriately.

You price appropriately based on the magnitude of the problem you solve and how completely you solve that problem.

Changing Your Pricing: Always Go Up, Never Go Down

Service-based businesses are fundamentally different from product or software businesses. Instead of selling inventory or code, you’re selling two core assets: your time and your expertise.

How those assets are viewed depends on perspective. From the customer’s point of view, they’re paying for access to your knowledge and your time. Their goal is to solve a problem, which usually falls into one of four categories:

• They don’t know what to do and need expert guidance.

• They know what to do but can’t implement it consistently and need support.

• They want to fast-track their results by avoiding trial and error.

• They want to hand the task off entirely to save their own time.

From your side as the service provider, you are doing one of two things:

• Sharing your expertise, which took you years of study, reps, and experience to build.

• Giving your time directly, helping clients move faster and more effectively toward their goals.

In other words, when you run a service-based business, you are offering either the expertise you’ve developed through years of work and learning, or your time and attention to help clients make faster progress and achieve better results with less uncertainty. This means you’re either transferring the knowledge you’ve earned or accelerating someone else’s success by showing up with them, for them, and beside them.

This is what makes pricing decisions so important.

In product businesses, offering a discount doesn’t impact the product’s value. It simply reduces your margin or subsidizes production costs. In a service business, though, a discount directly reduces the perceived value of what you offer. You are no longer just cutting prices—you are, in effect, saying your time and your knowledge are worth less.

This is especially problematic because service businesses don’t scale like software or products. As you grow, you don’t get economies of scale in the same way. More clients often means more complexity, more team management, and more cost to deliver the same quality of service. While software may help improve efficiency, it rarely eliminates the human capital required to deliver high-quality outcomes.

If you’re building a non-SaaS service business, your end game isn’t to acquire a billion users or reduce your delivery costs to zero. It’s to create a highly profitable business that delivers so much value your clients never want to leave. And once you understand that, it becomes clear that discounting does not drive meaningful or sustainable growth.

Discounting may feel like an easy win, but it often turns into a trap. When you lower your price to make a sale, you sacrifice your margins. To compensate, you need more clients, which means higher marketing costs. But now, every client you bring in is less profitable. I’ve run this experiment myself—and I have the numbers and the battle scars to prove it. In nearly every case, you’ll never bring in enough new clients to offset the loss in revenue from discounting.

There’s also a more subtle, but equally important, problem with small discounts. If you’ve truly nailed the value-to-price equation and your offer delivers ten times more value than what you charge, a small discount doesn’t actually make a difference. If you’re providing $1,000 in value for every $100 a client pays, lowering your price to $90 changes the ROI from 10 to 1 to 11 to 1. That shift doesn’t determine whether someone buys. If it does, it’s likely a sign that your offer isn’t strong enough, your product isn’t delivering the value you think it is, or your sales team isn’t communicating that value clearly.

When your value is obvious and well-positioned, a small discount won’t move the needle—and it shouldn’t have to.

Beyond the economics, price cuts send a message. They tell your team that you’re willing to trade value for volume. They tell your market that your original price wasn’t justified. And they give your sales and marketing teams a shortcut to avoid solving real problems with positioning, messaging, or execution.

Meanwhile, higher prices send a very different message. They communicate confidence. They force clarity in your offer. And they attract clients who are more serious, more committed, and less price-sensitive.

Many service businesses eventually become the Whale Businesses we discussed earlier - a small group of long-term, high-value clients often accounts for the majority of your revenue. For example, if you run a coaching or consulting service priced at $150 to $200 per month, and you have clients who’ve stayed with you for more than five years, those clients aren’t leaving over a 10 percent price increase. They’re staying because your service is embedded in their lives. The cost of switching is high, and the value you provide is worth more than the marginal increase in price. This is the same reason most people don’t change cell phone providers over a few dollars a month.

To summarize, lowering prices does a handful of things to your business:

• Provides shortcuts to your marketing and sales teams for closing deals.

• Sends the message to prospective customers that your original prices are too high for what you are providing.

• Saves your best customers money and lowers the margins on bad customers.

• Requires you to sell more to offset the loss in revenue.

• Highlights the cost, not the value

Conversely, raising prices has the opposite effects on your business:

• Requires you to solve the real sales problem

• Sends the message to prospective clients that your business is improving

• Creates more valuable customers

• Creates a more economically efficient business

• Highlights the value and keys requires you to focus on the value-to-price discrepancy

So here’s the core principle: raise your prices when you’ve earned it, but never lower them just to close a sale. Pricing isn’t just a financial decision—it’s a strategic one. It affects your margins, your positioning, your client base, and your internal culture. When you lower prices, you risk creating long-term problems in exchange for short-term relief. When you raise prices strategically, you push your business toward clarity, confidence, and sustainability.

The decision is yours. But if you’re committed to building a business that lasts, one thing is clear: your pricing should reflect the value you deliver—and the future you’re building.

Valuable customers are not found. They are created.

You make valuable customers by making them more informed customers first.

You create valuable customers by pricing appropriately.

You price appropriately based on the magnitude of the problem you solve and how completely you solve that problem.

The pain of learning how to sell your product or service at a higher price is less than the pain of devaluing your entire business by lowering the price.

Summary

The best businesses don’t just find valuable customers—they create them. By increasing customer lifetime value (LTV), you generate more revenue per customer, reduce acquisition costs, and increase profitability.

• Valuable customers are educated customers—give them value before they buy.

• Higher-ticket offers increase LTV—upselling and cross-selling matter.

• You should price based on the problem you solve, not the cost to deliver.

A good entrepreneur will go a layer deeper and tell you about their lifestyle, hobbies, interests, political leanings, and where those people spend their time.

A great entrepreneur will tell you about the problems their customers are trying to solve. Very few of them will ever stop and ask themselves, “I wonder what the revenue from my clients is going to look like?”

The question goes much deeper than the basic question of customer lifetime value (LTV). Sure, your customer lifetime value may be $1500, but if you have 10 customers, that LTV could mean that each customer pays you $1500, or it may mean that 9 customers pay you $100 and 1 customer pays you $14,100.

Do you really want a customer base where you lose money on 9 customers and make money on 1 customer? Maybe that does make sense for your business… or maybe it doesn’t. But the real question is, do you even know what the revenue and profitability of your customer base looks like?

If I were to ask you right now to draw a graph to show the distribution of revenue of your customers, could you do it?

If you can’t, you are not alone. Most business owners and entrepreneurs can’t.

If you don’t know, let’s at least give it a shot.

What do you think it looks like?

No, really. Stop, grab a piece of paper and graph out what you think your revenue distribution by customer looks like. This will tell you a lot about your business.

Here, I will even give you space in this book to actually write it down. Use a pen. Make it permanent. That way when you come back here you can see the progress you’ve made in understanding your business.

While there are an infinite number of potential distributions of revenue, most service-based businesses fall into one of the four types of “revenue distribution models.” There are technical names for each of these models, but those names don’t matter; we will use names that describe the type of business you own.

Whale Business

A Whale Business describes a business that may have a lot of customers (or may only have a few) but generates the majority of its revenue from a small handful of clients. These types of businesses often generate more than 50% of their revenue from 5-25% of their clients. While I have not been able to find any clear economic data to support this, I would venture to guess that a very large portion of service-based businesses, especially B2C businesses, have this type of customer base. In my own experience, the three service-based businesses I have owned have all followed this type of revenue distribution. In fact, here is the actual data from one of the service-based businesses I’ve owned that has generated over $30M in sales.

Whale businesses are often businesses that are structured as follows:

1. They have a free lead magnet or incredibly low ticket offer capturing massive leads.

2. They have one or two moderately priced products that are subscription based, or they offer one-time payments for services but the service is a recurring type service in nature.

3. They have a large portion of their client base that are returning clients, meaning even if they churn their subscription, they come back.

For years, I thought that the businesses I ran were unique in that they followed this distribution, but it turns out this is how the revenue for a lot of service-based businesses shakes out. A few years ago, I was at a dinner with a private equity investment group that expressed interest in purchasing one of the businesses I owned, and we were discussing this exact topic. Their group owned several businesses in the online horoscope reading, tarot card reading, and spiritual guidance space. Their revenue distributions matched ours almost identically despite being almost 10 times the size of our business at the time.

Many law firms, accounting firms, and other professional service firms also have revenue distributions like this. They have a small, concentrated group of customers who, over time, contribute the majority of the overall revenue to the business.

These types of consumer behaviors exist across varying industries and at all levels of scale.

Whale Businesses generally arise through two primary mechanisms: 1) you create a core of extremely loyal customers, 2) you are the only game in town.

Most of us end up creating Whale Businesses through the first mechanism.

Books about building unicorn companies focus heavily on the second mechanism. While these businesses are amazing, they are often based on incredible timing, some luck, massive amounts of capital, and often… a little bit of legal rule bending. In this book, we are going to focus on creating a core of loyal customers, which we will discuss in Play IV.

Running a Whale Business can have some specific implications if you are looking to scale your business. Specifically, a Whale Business must be viewed very carefully from the perspective of customer acquisition costs and gross margins. From my experience when trying to understand how to acquire clients at any meaningful scale, it is important to utilize the median customer lifetime value in your customer acquisition costs.

Small Fish Business

A Small Fish Business is the opposite of a Whale Business. A Small Fish Business has very few high-paying clients but a lot of lower-paying clients. These businesses usually generate a large majority of their income from the higher volume, lower price items.

If we strictly view this from a service-based business perspective, these types of businesses are often information product businesses that have a handful of single use products and mostly automate delivery. Their goal is to sell lower priced products to as many people as possible and automate fulfillment as much as they can. Small fish businesses require massive “scale”. They must sell thousands upon thousands of units to generate any meaningful profit.

Another feature of businesses like this is that they are often “one-and-done” businesses. They effectively saturate a market with their product and the market moves on. Businesses that rely on the Small Fish Business strategy have two options for sustaining past initial market saturation: 1) hold on long enough for a new generation of buyers, 2) create additional products to sell to your audience and shift your business into a Whale Business or a Varied Service Business.

Varied Service Business

A Varied Service Business has a relatively homogenous revenue distribution, with most of its clients contributing revenues that are varied and depend on the clients’ needs. These businesses generally attract a wide variety of customers who use their service just once or a few times and for one-off projects that vary in scope and cost.

These businesses generally have services that scale with the customers’ needs. Examples of businesses like this include software development, advertising agencies, and even businesses like contracting or home building.

One Product, One Time Business

One-product, One-Time Businesses are exactly what they sound like. They serve a single-use product or service that likely will never be purchased or used again.

Examples of businesses like this might include service-based businesses that offer one-time-use services or businesses that have set contract lengths that clients strictly adhere to.

One-time-use service businesses might be law firms that do estate planning or wills (most people only make one or two wills in their lives) or a flat-fee business consulting service that does on-site training (most businesses hire this as a one-time “reset” for their business).

Why Your Revenue Distribution Matters

The distribution of revenue matters significantly for customer acquisition because it directly affects how your business will allocate resources to attract and retain clients.

In a “Whale Business,” where the majority of revenue comes from a small percentage of high-paying clients, customer acquisition efforts need to focus on cultivating and maintaining relationships with these top clients. You extract most of your profit from a handful of loyal customers. Instead of chasing lots of new customers, find the ones who pay you lots of money and get them to pay you even more. This strategy often involves personalized marketing, higher-touch service, and longer sales cycles, as the lifetime value of each client is crucial to the overall profitability.

On the other hand, in a “Small Fish Business,” the goal is to attract a large volume of low-paying clients, meaning customer acquisition must be optimized for scale and efficiency. Automated marketing systems, lower customer support costs, and streamlined onboarding processes become critical in maintaining profitability, as the lifetime value of each client is significantly lower.

Understanding the revenue distribution also affects how a business calculates customer acquisition costs. For example, in a Whale Business, using the median customer lifetime value (rather than the average) can provide a more realistic view of the costs and returns from acquiring new clients. This is because a few high-value customers may skew the average lifetime value, leading to misinformed decisions about how much to invest in customer acquisition. In contrast, businesses with a more even revenue distribution or a high volume of low-paying clients may need to focus on minimizing CAC to ensure they remain profitable at scale. Ultimately, aligning customer acquisition strategies with revenue distribution ensures that your business is acquiring the right types of clients in the most cost-effective way possible.

Every few weeks, a new wave of alarmed headlines rolls through: “People are regaining all the weight after stopping Ozempic.” Physicians are asked to weigh in. Social media debates erupt. And somewhere in the commentary, the implicit suggestion emerges that GLP-1 receptor agonists (GLP-1RAs) have somehow betrayed us…that the weight regain reveals something uniquely dangerous or fraudulent about these medications.

To be direct: I am genuinely puzzled by the framing of this as a revelation. Of course they are. A thorough read of the weight loss literature over the last several decades gives us a remarkably clear answer on this question. Weight regain after large, rapid weight loss is not a feature of GLP-1 medications. It is a feature of large, rapid weight loss.

Give someone weight loss medication and stop it: weight regain.

Undergo bariatric surgery: weight regain

Undergo intensive calorie restriction and then stop dieting: weight regain

Engage in high-volume exercise for short periods and then stop: weight regain.

Decades of research have pointed this out. This is not new. We also know why it happens and how best to address it. The problem is… we don’t actually address it. Not in a structurally meaningful way.

Let me walk through what we actually know.

The data on GLP-1 rebound is real, and it is significant

Let’s not minimize what the clinical trials have found, because the numbers are striking. In the STEP-10 trial, over 40% of lost weight was regained within just 28 weeks of stopping semaglutide, while in SURMOUNT-4, more than 50% of weight loss with tirzepatide rebounded over 52 weeks.

Meta-analyses have now quantified this systematically. Among participants with overweight or obesity across 11 randomized controlled trials, GLP-1RA discontinuation was associated with a pooled mean weight regain of 5.63 kg, approximately 5.81% of body weight. A separate analysis comparing agents found that participants taking liraglutide regained a mean of 2.20 kg after discontinuation, while those on semaglutide or tirzepatide regained 9.69 kg, a gap that roughly tracks with the greater absolute weight lost on the newer, more potent agents.

The trajectory of regain also follows a predictable pattern. At one year post-cessation, approximately 60% of the weight lost during treatment is regained, with modeling suggesting weight ultimately plateaus at around 75% of the total lost, meaning some benefit persists, but is substantially attenuated.

The rebound isn’t specific to the scale; obesity-associated metabolic sequelae return: systolic blood pressure rises, fasting plasma glucose increases, and HbA1c climbs back toward pre-treatment levels.

And in the real world, discontinuation is common. A retrospective study of patients who discontinued GLP-1RA treatment found that nearly half of those who had previously lost weight would exceed their original weight within a year of stopping.

So yes, the problem is real. But here is where I think the public conversation goes badly wrong.

This is not unique to GLP-1 medications

The weight regain narrative around GLP-1s treats them as uniquely unreliable. But if you simply look backwards through the obesity treatment literature, you will find the same story told again and again.

The chart above illustrates the general pattern across three very different approaches. The absolute magnitude differs. The long-term trajectory does not.

Previous-generation weight loss medications. Orlistat, sibutramine, phentermine, fenfluramine, rimonabant all have been shown to produce meaningful weight loss during treatment and near-universal weight regain upon cessation. The same pattern. A systematic review and meta-analysis examining 37 studies across weight-loss medications including GLP-1, orlistat, phentermine, fenfluramine, and others found consistent weight regain after stopping treatment, regardless of mechanism of action.

Bariatric surgery. The most structurally aggressive intervention we have for obesity is not immune either. Weight regain is prevalent in approximately 49% of bariatric surgery patients overall, with Roux-en-Y gastric bypass showing the highest prevalence at roughly 64% of cases. In the landmark Swedish Obese Subjects (SOS) trial, the most rigorous long-term bariatric data we have, mean weight change was -23% at two years post-surgery, but recovered to -17% by year 10 and -18% by year 20. Surgery delivers the most durable weight loss of any intervention we have, and it still shows meaningful regain. And crucially, the mechanism is the same: the most common drivers of post-surgical weight regain are maladaptive eating behaviors, inadequate physical activity, and physiological compensatory mechanisms — not surgical failure.

Dietary and lifestyle interventions. This is where the evidence is perhaps the most instructive, and the most underappreciated in the current GLP-1 debate.

The typical weight loss and weight regain pattern in studies employing very low-calorie diets (VLCDs) shows initial losses of 15–25% of body weight in the first 3–4 months, followed by regain of 40–50% of the lost weight within 1–2 years after the program ends. A meta-analysis directly comparing VLCDs and standard low-calorie diets found that although VLCDs induced significantly greater short-term weight losses, long-term outcomes were comparable — because VLCD-treated patients regained 62% of lost weight at follow-up, versus 41% for those on moderate caloric restriction. The more dramatically you lose, the more dramatically you bounce.

The Look AHEAD trial, one of the largest and longest lifestyle intervention trials ever conducted, makes the same point at the population level. The intensive lifestyle intervention group achieved a mean weight loss of 8.6% at year one, the classic peak of maximal weight loss seen in multicomponent lifestyle trials, followed by gradual regain through year five before stabilizing at roughly 4–6% sustained loss. This was with continued intensive behavioral support. When that support structure falls away entirely, as it does when any intervention ends, the trajectory is steeper. In the absence of follow-up care, individuals who lose weight typically regain one-third of that loss in the year following treatment, with return to baseline weight frequently observed within three to five years.

This is not a new observation from the GLP-1 era. Losses of 15–20% of initial weight, achievable with very low calorie diets, have long been understood to be followed by rapid weight regain — even when participants are provided weight-maintenance therapy afterward. The field has known this for decades. The GLP-1 medications simply achieve those magnitudes of weight loss in far more patients, and far more reliably, which means we are now seeing the inevitable downstream consequence at a population scale.

The pattern is so consistent across interventions, populations, and eras that it should no longer surprise anyone: large, rapid weight loss followed by a return to prior habits leads to weight regain. This is what happens when weight loss outpaces durable behavioral change.

The bigger problem: weight cycling may leave you metabolically worse

Here is where the conversation needs to go deeper, and where I think the stakes are genuinely underappreciated.

It is not just that the weight comes back. It is that the weight that returns may not look the same as the weight that left.

When we lose a substantial amount of weight rapidly, regardless of mechanisms, we lose both fat mass and lean mass (muscle, bone, organ tissue). The proportion varies depending on the intervention and, critically, on physical activity levels. But under conditions of caloric restriction without adequate resistance training, a meaningful fraction of what is lost is lean tissue. In the STEP 1 and SURMOUNT trials, approximately 30–40% of the weight lost on GLP-1 therapy was lean body mass.

This is not unique to GLP-1s, it is a consistent finding in large dietary restriction studies as well. However, the magnitude of weight loss achievable with modern GLP-1 agents means it occurs at a scale we have not routinely encountered outside of surgical weight loss.

The problem emerges during regain. Weight cycling alters body composition, resulting in faster fat recovery and slower muscle reconstruction, a pattern of fat accumulation and muscle loss that disrupts metabolic function and promotes ectopic fat deposition.

Why does this happen? The honest truth is, building muscle tissue during weight regain requires a tremendous amount of effort and focus among adults. Moderate-to-high intensity resistance training with adequate volume in a structured way is absolutely required. However, most people do not engage in this for extended periods of time.

This is not a theoretical concern. A prospective cohort analysis examined 622 participants at high risk of type 2 diabetes and found precisely this: those who lost more than 5% of body weight and then regained it over a two-year period returned their fat mass to baseline levels, but lost approximately 1.5 kg of fat-free mass in the process, even after adjustment for confounders. The conclusion: weight cycling may be associated with a progressive loss in fat-free mass and gain in fat mass.

This points to something important that occurs with repeated cycles of large weight loss and weight regain: at the same total body weight, after a weight loss and regain cycle, the composition has shifted. Most individuals end up with more fat, less functional lean tissue. And critically, weight regain following GLP-1 cessation is likely to come back with greater increases in fat mass rather than lean body mass, further compounding this problem.

The clinical implications are significant. Returning to the same body weight with less muscle and more fat means a worse metabolic phenotype: lower resting metabolic rate, worse insulin sensitivity, greater susceptibility to future weight gain. If this cycle repeats (loss, regain, loss, regain), each iteration potentially leaves the patient a step further from where they started, compositionally speaking. This is the real issue. Not that people regained weight. That some of them may have ended up metabolically worse than when they started.

The literature has given us the answer: behavior change and physical activity are non-negotiable

This is not an article about the sky falling. It is also not meant to suggest we are unable to do anything about it. Instead, there is a clear path forward, we just need to acknowledge it.

The literature has been fairly unambiguous about what modifies these outcomes. The answer is sustained behavior change. Within that, physical activity, particularly resistance training, is the most consistently protective factor. Put simply, regardless of the mechanisms of weight loss, resistance training and longer-term behavior change is essential for maintaining improvements in body weight and body composition over time. Resistance training is relatively straightforward: lift weights at moderate-to-high intensity for ~150 minutes a week, spread across a few days.

The behavioral dimension is more complex. Weight regain on GLP-1s, on post-bariatric patients, on post-dietary intervention patients generally have a commonality: a return to the habits and food environment that drove the weight gain in the first place. The intervention creates the window. The behavior determines whether you climb through it and stay there.

There has to be intention around changing the environment and your habits and behaviors within those environments.

What this should actually change

The GLP-1 rebound story is being told as a failure of these medications. It is better understood as a very old problem that these medications have made newly visible at scale. This isn’t a problem with the medication, it is a problem with human behavior. It is a problem that will exist regardless of the intervention and we need to address it.

We have never successfully solved the problem of large, rapid weight loss followed by a return to prior habits. Not with surgery. Not with older medications. Not with aggressive dietary restriction. The pattern is documented so thoroughly, across so many interventions and populations, that treating each new manifestation as a surprise is no longer intellectually defensible.

This was never a problem with a singular solution. Some single tools are more impactful than others, but there isn’t a single solution here.

What the GLP-1 era should be prompting is not alarm. It should be prompting recognition that we need tools to support the behavioral and environmental changes people need to maintain improved body weight and body composition. Medication, surgery, or even diet programs can be powerful tools, but none of them build the physical fitness infrastructure that makes weight maintenance biologically tractable. They also do not rewire the food environment that patients return to when the prescription lapses.

We need more professionals, more successful businesses, more training, more leadership, more coherence, and better discussions about creating the infrastructure to improve outcomes across intervention tools, including pharmaceutical, surgical, and dietary interventions.

We have to acknowledge that we have created excellent approaches to losing weight, but we treat it as a “phase”... not a long-term strategy that includes professionals, infrastructure, and support to meaningfully change behavior and maintain that behavior change.

Author Note: This article is not a commentary on whether people should or should not take weight loss medications, nor is it a commentary about whether people should take them for a short period or forever. It is a commentary on how to improve the long-term success rate of any weight loss intervention.

References

GLP-1 RA Cessation & Rebound

1. Wilding JPH et al. Once-weekly semaglutide in adults with overweight or obesity (STEP 1). N Engl J Med. 2021;384:989–1002.

2. Wilding JPH et al. Weight regain and cardiometabolic effects after withdrawal of semaglutide: the STEP 1 trial extension. Diabetes Obes Metab. 2022;24(8):1553–1564.

3. Rubino D et al. Effect of continued weekly subcutaneous semaglutide vs placebo on weight loss maintenance: the STEP 4 randomized clinical trial. JAMA. 2021;325(14):1414–1425.

4. Aronne LJ et al. Continued treatment with tirzepatide for maintenance of weight reduction in adults with obesity: the SURMOUNT-4 randomized clinical trial. JAMA. 2024;331(1):38–48.

5. Karakasis P et al. Metabolic rebound after GLP-1 receptor agonist discontinuation: a systematic review and meta-analysis. eClinicalMedicine (Lancet). 2025.

6. West S, Scragg J, Aveyard P, Oke JL, Willis L, Haffner SJP, Knight H, Wang D, Morrow S, Heath L, Jebb SA, Koutoukidis DA. Weight regain after cessation of medication for weight management: systematic review and meta-analysis. BMJ. 2026;392:e085304. DOI: 10.1136/bmj-2025-085304

7. Sun Q. Weight regain after cessation of GLP-1 drugs [editorial]. BMJ. 2026;392:r2586.

8. [Authors] Discontinuing glucagon-like peptide-1 receptor agonists and body habitus: a systematic review and meta-analysis. PMID: 40186344.

9. [Authors] Trajectory of weight regain after cessation of GLP-1 receptor agonists: a systematic review and nonlinear meta-regression. eClinicalMedicine (Lancet). March 2026.

10. [Real-world study] Real-world weight change pattern after glucagon-like peptide-1 receptor agonist discontinuation: a 1-year observational study. Obesity Science & Practice. 2025.

Body Composition & Weight Cycling

11. Yates T, Biddle GJH, Henson J et al. Impact of weight loss and weight gain trajectories on body composition in a population at high risk of type 2 diabetes: a prospective cohort analysis. Diabetes Obes Metab. 2024;26(3):1008–1015. PMID: 38093678

12. Bosy-Westphal A et al. Effect of weight loss and regain on adipose tissue distribution, composition of lean mass and resting energy expenditure in young overweight and obese adults. Int J Obes. 2013;37(10):1371–1377.

13. [Review] Weight cycling and its effects on muscle mass, sarcopenia and sarcopenic obesity. Reviews in Endocrine and Metabolic Disorders. 2025.

14. [Review] Weight cycling based on altered immune microenvironment as a result of metaflammation. Front Immunol / PMC. 2023.

15. Neeland IJ, Linge J, Birkenfeld AL. Changes in lean body mass with glucagon-like peptide-1-based therapies and mitigation strategies. Diabetes Obes Metab. 2024;26(S4):16–27.

GLP-1 + Exercise / Lean Mass Preservation

16. [Case series] Preservation of lean soft tissue during weight loss induced by GLP-1 and GLP-1/GIP receptor agonists. PMC. 2025. PMID: 41122508.

17. [Review] GLP-1 agonists and exercise: the future of lifestyle prioritization. Front Clin Diabetes Healthc. 2025.

18. Apovian C, Yerevanian A, Dushay J. Preserving lean body mass in patients taking GLP-1 for weight loss. Mass General Brigham Advances in Motion. 2025.

Bariatric Surgery & Weight Regain

19. Sjöström L et al. Effects of bariatric surgery on mortality in Swedish Obese Subjects. N Engl J Med. 2007;357:741–752.

20. Sjöström L. Review of the key results from the Swedish Obese Subjects (SOS) trial. J Intern Med. 2013;273(3):219–234.

21. [Lancet Regional Health Europe, 2025] Health outcomes and their association with weight regain after substantial weight loss in Sweden: a prospective cohort study. (SOS 27-year follow-up)

22. [Meta-analysis] Weight regain after bariatric surgery: a systematic review and meta-analysis of observational studies. Surg Obes Relat Dis. 2023.

23. [PMC review] Weight regain after bariatric surgery: scope of the problem, causes, prevention, and treatment. PMC. 2023.

24. King WC et al. (LABS study) Comparison of the performance of common measures of weight regain after bariatric surgery. JAMA. 2018;320(15):1560–1569.

Dietary / Lifestyle Interventions & Weight Regain

25. Look AHEAD Research Group. Cardiovascular effects of intensive lifestyle intervention in type 2 diabetes. N Engl J Med. 2013;369:145–154.

26. Look AHEAD Research Group. Eight-year weight losses with an intensive lifestyle intervention: the Look AHEAD study. Obesity. 2014;22(1):5–13.

27. Look AHEAD Research Group. Four-year weight losses in the Look AHEAD study: factors associated with long-term success. Obesity. 2011;19(10):1987–1998.

28. Tsai AG, Wadden TA. The evolution of very-low-calorie diets: an update and meta-analysis. Obesity. 2006;14(8):1283–1293.

29. Saris WHM. Very-low-calorie diets and sustained weight loss. Obes Res. 2001;9(S4):295S–301S.

Our Finances

Perhaps the most consequential erosion of agency has occurred in our financial lives.

Over several decades, we collectively built a system that systematically undermined financial self-reliance — not through any single decision, but through the gradual normalization of debt as the primary mechanism by which ordinary people access ordinary life. This did not happen by accident. It was the predictable result of a credit-based economy that financially engineered leverage into nearly every major purchase, and in doing so, quietly redefined what it means to afford something.

The arc is worth tracing. There was a time when houses were saved for, and the goal of ownership meant accumulating enough capital to buy outright or carry a modest loan. Today, thirty-year mortgages are standard, and fifty-year terms are emerging — not because homes became more valuable, but because prices rose to meet whatever financing could be extended. Cars followed the same pattern. What was once a significant purchase, often made in cash or on short terms, has become a $700-per-month obligation stretched across six or seven years for the average buyer. Even leisure has been financialized: recreational boats that once represented genuine luxury now carry price tags exceeding the median home value of a decade ago, available on twenty-year financing. The asset class barely matters. The structure is always the same: extend the term, lower the monthly number, make the unaffordable feel accessible, and move the true cost out of view.

The effect on the individual is not merely financial. Debt at that scale and duration is a constraint on agency in the most literal sense. It determines where you can afford to work, whether you can afford to leave, what risks you can take, and how much of your future decision-making has already been committed. A person carrying a thirty-year mortgage, two car payments, and a student loan is not simply in debt; they are locked into their life. The optionality that enables genuine self-determination has been traded, often incrementally and without full awareness, for access to things that were reframed as necessities.

The college debt crisis followed the same logic at institutional scale. We convinced an entire generation that a degree, regardless of field, cost, or institution, was the non-negotiable price of admission to a stable life. Institutions responded by raising prices far beyond inflation, knowing that federally backed loans would absorb the cost. Students took on debt that was poorly underwritten against future earning potential. Then we spent years debating whether that debt should simply be forgiven.

Social Security was built on a related premise: that individuals could not be trusted to plan for their own retirement, so the government would collect, hold, and redistribute on their behalf. Whatever its merits as a safety net, it also functionally relieved generations of the habit of long-term financial thinking. Not to mention it has taken that money and yielded real returns compared to putting those dollars into the public markets. We have continued layering programs, subsidies, and structural incentives that make leaning on collective systems more rational, at least in the short term, than building personal financial resilience. When the system reliably pays out more than the effort required to opt out of it, most people rationally choose the system.

The result is a population that is, on average, financially less capable, less resilient, and less free than it was fifty years ago, despite being wealthier in aggregate.

Our Politics

Our political lives have become one of the most vivid illustrations of agency’s collapse.

You are being sorted. Not by your own considered reasoning, but by an algorithm that has learned exactly which emotional lever to pull, and when. Social media platforms, cable news, and political advertising have become extraordinarily efficient at placing people into ideological boxes.

The clearest evidence of this is the predictability of political belief. Tell me where someone stands on a single major issue — abortion, fiscal policy, immigration — and I can predict their position on nearly every other issue with over 90% accuracy. Political identity has become so totalizing that genuinely independent thinking on any individual issue is now the exception, not the rule.

People are not arriving at these positions through deliberation. They are being routed there by systems optimized not for their understanding, but for their engagement.

This is the death of political agency: not that you hold strong views, but that those views were largely constructed for you.

Our Relationships

Human relationships are degrading across almost every dimension: personal, professional, familial, and romantic. For most people, the mechanism for this degradation is the same: the digital filter.

Walk into a room of younger adults and observe how many are present in the room versus present on a screen. In my experience, it is rarely below half. The phone is not just a distraction; it is a substitute environment, one that offers the simulation of connection with none of the social or psychological demands of a real connection

Professional relationships have followed the same trajectory. Consequential decisions, the kind that used to require a room, a conversation, and the accountability of eye contact, are now made over email. In my observation, they are worse for it. Something is lost when there is no one in the room.

Families substitute shared digital spaces for shared physical ones (e.g. FaceTime). Romantic relationships among younger people are increasingly initiated through swipe-based platforms that have industrialized attraction into a volume game.

I noticed the earliest signals of this shift twenty years ago, the first time I logged into Xbox Live as a teenager and listened to what happened to human discourse when it passed through a digital filter and a layer of anonymity. The social norms that govern in-person interaction, the ones that make relationships possible, dissolved almost instantly.

That was a preview. We live in that preview now.

The digital filter does not just change how we communicate. It changes who we become in communication. It allows us to be products of a curated digital environment rather than active, accountable participants in our own relationships. Relationship agency, the willingness to show up, to initiate, to be present, to have conflict, and to repair, is dying.

Our Minds

I work primarily in knowledge work, and I have watched the outsourcing of cognition happen in real time.

It began before AI. Email replaced memos, search replaced memory, and calculators replaced arithmetic. But the commercial availability of large language models has accelerated the trend by an order of magnitude. In nearly every domain I touch, analysis, interpretation, synthesis, and decision-making, the reflex is now to offload to a model.

And there is a defensible logic to it. These systems are fast. They are capable. They can synthesize large bodies of information and produce coherent output faster than any individual analyst. In narrow, well-defined tasks, they are often better.

The muscle that is never used does not stay ready; it atrophies. Increasingly, we are not just using AI to augment thinking; we are using it to replace thinking. We hand the model a complex problem and accept its output without the friction of having wrestled with it ourselves. We do not own the answer or the skill of arriving at the answer. We have borrowed it.

I notice this in myself. After only a few years of AI being commercially viable, I feel the pull; the low-grade reflex to open a model before I have genuinely attempted a problem on my own. That reflex frightens me more than the model itself. It suggests that even people who are aware of the dynamic are not immune to it. I am a bit scared that my work days will have forced breaks because I reach my token allotment for the morning…

The loss of cognitive agency may be the most consequential of all, because it is the one from which all others might eventually be recovered. A mind that can still reason independently can rebuild financial discipline, reject political manipulation, and choose to be present. A mind that has fully outsourced itself cannot.

Why Is This Happening — And What Can We Do?

I do not believe there is a coordinated effort behind any of this. No central puppeteer. No unified agenda. What I believe is simpler and, in some ways, more difficult to address: high agency is genuinely hard, and our modern environment is engineered, not maliciously, but structurally, to make the low-agency path easier at every turn.

Maintaining high agency requires sustained effort, discomfort, and self-reflection. It requires tolerating uncertainty rather than outsourcing it. It requires accepting that your outcomes are, to a meaningful degree, yours to determine. This can be frightening, because it also means your failures are yours to own.

Meanwhile, every system around us is optimized for frictionlessness and engagement. The news maximizes anxiety to maximize attention. The platforms we spend our days on maximize comfort to maximize time on-site. The financial systems and social programs maximize short-term relief with consequences that compound slowly and invisibly: this is the entire basis of consumer credit. The path of least resistance runs directly through dependency.

I am also willing to acknowledge something uncomfortable: maybe a lower-agency future is what the majority of people actually prefer. Maybe the effort required to maintain genuine autonomy is a price most are not willing to pay. I do not think that is the right answer, but I am trying to be honest about what I observe.

For those who do not want that future, the solutions at the individual level are not complicated, even if they are difficult. They require deliberate friction.

Turn off the news. Spend time without your phone. Have difficult conversations in person. Cook your own food. Exercise your body. Save money before you spend it. Make a decision without consulting an algorithm. Write something by hand. Call instead of texting. Host a dinner instead of watching something.

None of this is revolutionary. But each choice is a small act of reclamation.

Agency is, to a meaningful extent, self-reinforcing. The more you exercise it, the more natural it becomes. The inverse is also true.

The Investment Thesis

I am not alone in observing this shift, and I do not think it is entirely bleak.

Precisely because the majority is drifting toward low agency, the minority who are not will represent a disproportionate share of economic value creation over the next decade. High-agency individuals start businesses, solve hard problems, allocate capital well, and compound their advantages over time. In a world trending toward dependency, the people who retain genuine autonomy become increasingly rare and increasingly valuable.

My own capital and attention are being directed accordingly. I am making deliberate bets on businesses and operators who attract, develop, and empower high-agency people. My particular focus is on smaller and privately held businesses, where institutional capital is thinner, and the advantage of backing the right operator is most pronounced.

The thesis is simple: in capitalism, agency wins. It always has. As the average level of agency declines, the premium on those who retain high levels of agency will only grow.

The beauty of both business and basketball is that losing isn’t something that might happen; it is something that will happen. No basketball player has ever won every game of their career. Losing is part of playing the game; in fact, it is the price of entry. In business, the same holds true—losing isn’t the exception, it’s often the default.

What matters is understanding that loss, in both arenas, is not failure but feedback. It is part of the process of improving your craft. Reflecting on my own journey—both personally and as an accidental entrepreneur—I can say with complete confidence that my losses taught me far more than my wins ever did. In many ways, the most valuable thing I’ve done is lose.

John Wooden once said, “Losing is only temporary and not all-encompassing. You must simply study it, learn from it and try hard not to lose the same way again. Then you must have the self-control to forget about it.”

Those words capture the mindset required to endure and grow. Because things will go wrong. Products will miss the mark. Ads will fall flat. Clients will leave. Chargebacks will happen. Employees will walk away—sometimes taking business with them. These moments are inevitable. What matters is how you respond to them.

Each loss carries information. Each setback sharpens your understanding. Over time, they compound into judgment, resilience, and clarity—the very traits that define long-term success.

This era was marked by:

• Subsidizing customers (Instacart and Uber)

• Buying customers through ads regardless of profitability (Netflix and Peloton)

• Chasing customer acquisition even if it led to an unsustainable business model (MoviePass and Pets.com).

Instacart was founded on the premise that the company would acquire customers at a loss and subsidize the delivery of food for the first several purchases and recoup the money and profits when they become routine users of the service. The original business model was built on spending capital to acquire customers at a loss. In a conversation on episode 73 of the All-In podcast about the unit economics of Instacart, Chamath Palihapitiya, the founder and CEO of the investment firm Social Capital, discussed how he used to order one mango at a time from Instacart as a joke to demonstrate how broken the company’s initial unit economics were. Palihapitiya did it to highlight the absurdity of companies trying to force scale by effectively buying customers at a net loss until the company reaches scale. The initial unit economics of Instacart are still such that the company loses money acquiring customers and loses money on the initial deliveries.

Such tactics were the main tools of the fast scaling, unicorn type companies during the 2010 decade. There are countless examples in addition to Instacart. Companies like Uber, Lyft, Lime Scooters, Peloton, and Casper mattresses all have utilized capital to buy customers at a loss in order to chase topline revenue.

Although, in some regards, these companies are considered massive success stories, the other perspective is they are not models for sustainable businesses. In fact, there was an entire story arc in The Office that highlighted the absurdity of this concept. This story arc was focused around Michael Scott leaving his position as a manager of a regional paper company, Dunder Mifflin, and starting his own paper company. Except his business model was to just buy paper from the same supplier as his old company and sell it at a much lower price to lure customers away from his old business. Eventually, Michael Scott realized that the Michael Scott Paper Company couldn’t survive financially because their ultra-low pricing model was unsustainable. With most of Dunder Mifflin’s clients having already switched over, the only way to regain them was for Dunder Mifflin to buy out the company. The game worked until the game was broken.

Buying customers at a loss is a way to buy customers, not a way to build a sustainable business. In many cases, this simply sets up “the death spiral” for a business, which looks something like this:

1. Spend huge amounts to acquire customers.

2. Raise money to continue acquiring customers as customers churn due to lack of profitability

3. Growth slows due to high churn so they have to raise at a lower multiple.

4. No one wants to invest more money.

5. Company has to downsize.

6. Product suffers.

7. Customers leave even faster.

8. Company goes bankrupt.

Forced growth through buying customers can help a business scale incredibly quickly and while this “force function” of growth by buying customers at outrageous acquisition costs can work to gather eyeballs, it places very little focus on what determines the long-term sustainability of a business: profitability. However, maybe even more fundamental than profits is the fact you haven’t done any work to figure out what the natural churn rate of your business is, what is driving customer churn, how you can improve it, and ultimately, what your operational efficiency point is. You have no idea what the true terminal size of your business is.

If you aim to flip your business to the next round of investors at a higher valuation and a peak multiple, the force function is a powerful tool. If you aim to build a sustainable, profitable business that changes lives for decades, the force function is the biggest distraction imaginable. You aren’t actually building a business. You are building a marketing and sales funnel. If you have been in the entrepreneur game for any length of time, you know marketing and sales funnels are fickle and a slight breeze can cause them to go from money printers to money pits incredibly quickly.

The collateral damage of this approach when it goes poorly cannot be understated. An article from early 2024 titled “Cloudy with a Chance of Downfalls: The Year Ahead for Startups,” published in The Hustle, highlighted this quite nicely. Here is a direct quote from the article,

WeWork, once worth $47B, filed for bankruptcy. Convoy, the Bezos-backed trucking company valued at $3.8B, shut down. Health startup Olive AI shuttered after peaking at a $4B valuation.

And many other startups followed suit by selling for a fraction of their valuations or closing up shop:

• Hopin, the virtual-events startup once valued at $7.8B, sold its core business for $50m.

• Once valued at $2.5B, scooter startup Bird filed for bankruptcy last month.

• Fintech startup Plastiq, which raised $226m in funding, went bankrupt in May.

According to data compiled by PitchBook for The New York Times, nearly 3.2k private venture-backed startups failed in 2023 after raising a combined $27.2B in funding.

It turns out, dumping money into a business with broken economics and poor customer retention is not a winning formula. Scaling a business without a solid model for acquiring and retaining customers is more like gambling than true entrepreneurship.

I freely admit am not a conventional business builder. I don’t think like most of them and I am not wired like most of them. Client acquisition and client churn are some of the primary areas where my brain is definitely wired differently. My opinion is that if you run a service or subscription-based business, your focus on churn should be as great, if not greater, as your focus on new sales. Client acquisition ebbs and flows. Customer sentiments change, trends change, and economic cycles change. Sometimes, it is easy to acquire clients; sometimes, it is nearly impossible to acquire clients.

In this part of the article, I will show you exactly why you should spend as much energy on client retention and client churn as acquiring new clients and how you can actually lower your client churn. Once you understand the effect small improvements in churn have on your growth and bottom line, it will fundamentally change the way you view your business, your clients, and your future.

Never neglect churn. The ceiling of your business is determined more by your churn than your ability to sell.

Small Margins, Big Difference

I believe every single person can acquire 50-75 clients for their business. No matter your product or your pricing, getting to 50-75 clients can be boiled down to a simple math problem.

Let’s stack two major market forces against us: pricing and market size. So, let’s say you decide to start a business in an industry and niche that sells a higher-priced product, and there is not a huge market for the product. Let’s say the price is $1,000 a month. This means you probably have one of the smaller potential markets to sell to, and with the higher price product and more niche market, your customer conversion rate for client acquisition may be much lower than the “average” conversion rate across industries. Let’s just set it at 0.25%… which is much lower than typical (which is around 0.5-2.5%).

This means, to acquire 50 clients, we just need to reach 20,000 people. If we do this the most inefficient way possible, we go door-knocking, and you can knock on 100 doors a day. That is 200 days of selling to acquire 50 clients.

Now let’s continue with this story and say that you have a service that is so amazing at solving the person’s problem that they can’t imagine ever canceling their subscription. They are clients for life. During those 200 days of selling, you generated $50,000 a month of revenue that lasts forever. The next year, you take some of that revenue and higher two salespeople to repeat the process, and they each add 50 clients, bringing your total to $150,000 a month. That means within 12 months, you have created a business that brings $1.8 million a year and will do so for the rest of your career. And you never have to go out and sell anything again.

Now let’s assume you can’t keep every client forever and you lose some clients - you have a 20% client churn rate per month. That isn’t a great churn rate but it also isn’t the worst churn rate; many service based businesses have churn rates around that number. Let’s do the math on this.

Those first 50 clients you acquired … after 30 days, you are down to 40 clients; after 60 days, you are at 32 clients; after 90 days, you are at 25 clients; at 120 days, you are at 20 clients; at 150 days you are at 16 clients, at 180 days you are at 12 clients, at 210 days you are at 10 clients. Your monthly revenue is now down to $10,000 a month, and you don’t have enough revenue to pay salespeople to go door-knocking, so you personally have to go back to door-knocking on another 16,000 doors to replace those 40 lost clients.

This story shows how client churn massively affects a business’s revenues. In one scenario, 24 months creates a multi-million dollar business that lasts a lifetime, while the other creates an infinite loop of being a door-to-door salesman your entire life.

If you don’t focus on churn, your business will churn you.

Extreme examples are great for highlighting why something might be important, but what about the real world? What should you expect regarding client churn and business growth? The insight I gained about client churn from operating and growing service-based businesses for nearly two decades comes down to this idea: small margins, big differences.

I have tracked the daily, weekly, monthly, and yearly churn of every client I have ever acquired. That is data on over 50,000 clients, not including returning clients. This has given me a huge amount of experiential knowledge and a good feel for how clients churn in service-based businesses, especially in the health and wellness space for moderately priced products (~$100-$500 a month).

Client churn can fluctuate anywhere from 5% to 20% depending on the quality of the service you provide, the time of year, and the type of contracts your clients are in (monthly, quarterly, yearly, etc.). Getting client churn to zero is likely impossible, but you can definitely engineer your business to minimize churn.

Now, most people might think that focusing on reducing client churn by 2, 3, or 4% is not the best use of their time, especially if they can spend more time and energy on acquiring new clients. Fair enough, this is probably a valid perspective, especially early on in the business. But there are two important ideas to consider: 1) sales volumes don’t always go up, 2) churn always happens.

Let me paint a very realistic example for you, because this is generally how business growth looks in the real world… at least in my world.

Imagine you run that service-based business we talked about above, and you have signed up your first 50 clients, each paying you $1,000 a month. You decide that you are so good at selling that you are going to keep doing sales and also do all of the service fulfillment yourself. This means you get to take home all the current profit, but you are also running around with your hair on fire and stretched thin. In this scenario, your service doesn’t improve (because you don’t dedicate any time to its improvement), and you are providing just enough service to keep most of your clients happy, and you are losing ~12% of your clients each month. But since you are still using part of your time to do sales you are still bringing in ~6 clients a month, which means you brought in an extra 72 clients over the next 12 months. However, at a 12% churn rate, you are losing just over 6 clients a month on average, so after 12 months of running your business like this, you are at 45 clients. Your total monthly revenues are down $5,000 a month. Your business has shrunk and your profit margins are dwindling.

Now, let’s paint a slightly different scenario. You decide to hire a full-time salesperson to keep bringing sales in, and that person, with a full-time effort, is able to bring you 6 clients per month, every single month for the first year. Hiring this person allows you to get your time back and really focus on product and servicing your clients. This brings your client churn down to 8%, which to you doesn’t seem like a huge improvement but it’s definitely a little better than 12%.

Over the next 12 months your sales person continues to bring those 6 clients a month in and after 12 months you have 62 total clients. Your business’s revenue has grown $12,000 a month. Your business has grown and your margins are booming.

While these scenarios may not seem very different at first glance, just do the math. That is a $ 17,000-a-month difference between those two in revenue. That is $204,000 a year with one very small change to your business.

These two examples are exactly how service-based businesses work in the real world.

How do I know?

Because I have lived this exact example more than once, and I don’t want you to have to learn the lesson the hard way.

Never neglect churn. The ceiling of your business is determined more by your churn than your ability to sell.

Small changes to your churn rates result in massive differences in total revenues and profitability over time.

How to Lower Churn in Your Business

Now that we have discussed why churn is so critical, it’s time to discuss tactics. This means we need to answer the question of what we can do about it.

When it comes to reducing churn, a lot of books will teach you about how to:

• Structure contracts and lock people into a service.

• Make it hard for them to cancel.

• Downsell them to something so cheap they no longer notice it on the credit card statement.

• Build a Planet Fitness model where 80% or more of your clients are “zombie” clients.

We are not going to come anywhere near touching any of those ideas. In fact, we are going to go as far in the opposite direction as we can think of. We are going to learn how to retain customers the real way.

Retaining customers the real way involves just a handful of core ideas:

1. Solve the customer’s problem.

2. Become indispensable

3. Reward loyalty and longevity.

4. Create a real community.

5. Focus on growing with your customers.

Here is how you do that.

Solve the Customer’s Problem

The first place to start a discussion about client churn is to remember that your business is about your clients, not about you. As business builders, we often get so focused on ourselves and what we are doing and how amazing our business is that we can forget why our business actually exists: to help people.

As an entrepreneur, one of the best questions you can ask yourself daily is, “What can I do to improve my service to ensure I am solving my clients’ problems?” and consistently update your service to solve their problems. As your business grows and evolves, your clients’ problems may change. This may be a result of changing demographics in your clients, you starting marketing to different types of clients, or maybe the world changes and your clients’ needs change.

Let’s take a marketing agency, for example. If you ran a marketing agency in 2005, your clients probably needed help figuring out how to utilize Google AdWords to market their businesses online. By 2010, your clients probably needed help with both Google AdWords and this new ad platform called Facebook Ads.

Going a step further, within that marketing agency, your clients probably didn’t just have a problem making and running ads; they probably had problems understanding if ads were working for them. So, you probably needed to build ways to track ad data and report it to your clients so they would know how effective the ads were.

Going even deeper, the clients of that marketing agency probably weren’t exactly sure what their customer acquisition funnel looked like across their entire business. So you probably needed to build tools to help your clients see exactly where their customers were coming from, how efficient their customer acquisition process was, and where their sales teams should be focusing in that process.

Imagine as a marketing agency that you have the ability to not only make creative and run ads for your clients, but you can be so integrated into their business that you understand their sales funnel better than they do, can show them where their bottlenecks are, and you can even help them solve those bottlenecks. At this point, you have become an indispensable part of their business. For this client, leaving the marketing agency would be detrimental to their business; they would now do anything to remain a client.

Become Indispensable

One evening, I had a very normal conversation with my wife at dinner. We were talking about how long we would live if the zombie apocalypse/nuclear winter ever came. I spent a few minutes talking about how I would outlast the zombies and how, if you do the math, zombies only have enough calories available on the planet to live a few years, so really, you only need to survive that long. After thinking for a few minutes, my wife said, “Would Target still be open? Because if there is no Target, I’m just walking out and letting the zombies eat me because I refuse to live in a world without Target.” After I had a good laugh about that, I started to realize that it is actually one of the main goals of any business.

The way you create sticky clients is by making your product or service so good that people would rather walk into the zombie horde or nuclear apocalypse than live without it.

That is a great sound bite and a lofty goal, but how do you do that?

Every single month I pay my cell phone bill, my electric bill, my natural gas bill, and my insurance bills. No matter what.

I am more likely to volunteer to go be a participant in a study on dental surgery than I am to cancel any of those services in my life. I can’t run my businesses without my phone or electricity. I would freeze in the winter without natural gas. I would run the risk of a major financial crisis without insurance.

If you can build a business that sells a product or a service that is truly indispensable to people, your likelihood of having very low client churn is incredibly high.

How indispensable your service or product is comes down to two things: 1) the type of service you provide, and 2) how well it actually solves a customer’s problem.

The harsh reality of business is that not all business opportunities are the same. Running a utility company has the advantage of being indispensable as long as they can do the bare minimum. They have a relative monopoly on providing basic, life-saving services like electricity and natural gas. They are essentially irreplaceable due to lack of an alternative. On the other hand, some business opportunities feel highly replaceable. Your barber, family practice physician, personal trainer, or marketing agency has meaningful competition; if they do just the bare minimum, they can be easily replaced. If you run a business that falls in the latter of those business opportunities, you must find ways to deliver results at a high level that solve your clients’ problems to such a degree that they never want to leave.

Marketing agencies are an excellent example of this. The experience of working with the average marketing agency looks something like this:

1. They get your contact information from an ad, a bought list, or a referral.

2. They do an amazing job of pitching their service for months before you finally sign up.

3. They charge you 15-25% of your total advertising spend to manage your ads and create a strategy.

4. Things start off well. They come with some initial fresh ideas for your marketing efforts. Often the agency owner is in those initial meetings.

5. After a few months, ad performance starts to decline. Your account is handed off to an Account Executive who meets with you every few weeks and regurgitates reports about your ads’ performance.

6. Each month, they ask you to spend more ad money…” because the algorithms do better with higher spending.” So, you increase your ad budget, which means they also get paid more.

7. Around 6-12 months in ad performance is struggling. You are barely breaking even on the cost of the ads and with the 15-20% fee you may actually be losing money. But it’s ok because these are “loss leader” programs.

8. There is no real strategy anymore on ads. It is basically just A/B split testing on headlines and images… and maybe some video if you are willing to pay for a video shoot.

9. You finally call it quits. You end up closing the contract with the agency and rebuild your advertising program from scratch, in house. You’ve lost 12 months and $200,000 in advertising spend and are now starting over.

This is a business that will have high client churn. But sadly, this is the standard in business. The focus on the initial sale is what matters to them, not how to build a sustainable customer base.

Now, how would we build a marketing agency that is indispensable to a customer? It begins with being deeply invested in your customer’s success and aligning incentives. Here are some ways you can structure your service and your pricing model as a marketing agency to become indispensable.

1. Charge fees based on the quality of work, not the amount of dollars spent on advertising.

2. Fully integrate with the businesses marketing and sales team. Continue to develop ad strategies that blend in with their business development goals.

3. Structure your agency as a “training agency.” In fact, you could even set up your service that your goal is to take your current agency employee and train them so well to understand the customer’s business that your own employee eventually functions as their “outside advertising director.”

4. Fully align your advertising cost structure with the customer’s business such that you produce an increase in the customers Lifetime Gross Profit Per Customer.

Create a business that provides a product or service that is so good that your customers would rather run into the zombie horde than leave as a customer.

Reward Loyalty and Longevity

Human beings are deeply social creatures. We crave belonging to groups. This is why we have political parties, diet cults, loyal fan bases for teams (even the ones that haven’t won in 100 years), and even the cliques we remember from middle school.

However, not only are we deeply social creatures who have an intense desire to belong to a group, but we also crave recognition for belonging to that group. This is why we wear jerseys of our favorite team, put political bumper stickers on our car, and why our relatives tell us about the new diet they started at the family get-together, even though we never even asked them.

These are features of our evolution. They are hard-wired into us as a species, deeply ingrained in us. And they are something we can really tie into if we want to build a customer base of clients who never leave.

One way to do this is to lean into this desire and reward people for being loyal and staying around for long periods of time. We discussed this briefly in our discussion on referrals and having referrals create a social cache for people, but now it is our turn to do that for our clients.

These rewards will be different for each business, but they can be as simple as sending handwritten cards to clients who reach certain longevity milestones or making custom t-shirts for their “X visit” as a customer. They can be as elaborate as “inner circle” events, public acknowledgments, or ceremonies highlighting your longest tenured and most successful clients. The exact specifics of how you do this matter much less than the simple fact that you make it a priority to reward loyalty and longevity.

Create a Community

Customers who belong to a community of other customers are far more likely to stay customers than if they are by themselves. This is the entire model of some of the largest companies of the world: Meta, Snapchat, TikTok. These businesses are founded entirely on communities and boast some of the lowest churn rates of any businesses at that size.

Communities drive retention for a handful of reasons.

The first reason is that people want to be where their friends are (we are social creatures). Having online or in-person communities creates a sense of belonging that people do not want to miss out on. Even when people are spending money on something, they want to do it with their friends. Actually… scratch that. When people are spending money, they especially want to do it with their friends.

The second reason is that people want the social clout of being in the “in” group. This idea alone is why many people will continue to pay for subscription services, even if it isn’t worth the money they are paying. Streaming services like Netflix or HBO are great examples of this. In the late 2010s, very few people cared about most of the shows on HBO, but they had a subscription and kept paying for it so they could talk about Game of Thrones with their friends. No one wants to show up to happy hour with their friends and be the one person who can’t contribute to the 45-minute discussion about The Red Wedding.

The third reason is that communities allow you to hear the conversations your customers are having. Businesses that have community forums, chats, social media communities or in-person events get the added bonus of hearing the things their customers are saying to each other about their business. Imagine getting all your customers together in one room and being able to listen to the things they say about your business. The value you get from listening and being able to update your business to increase retention and decrease churn is enormous. Communities give you the opportunity to listen, so do it.

The fourth reason is that having customers in a community often lets them hear about new products, offers, upgrades, or renewals faster, more directly, and more organically than if you were to use paid ads or send out emails. In fact, I’ve utilized this to incredible effect in one of my own businesses. One year over a Black Friday weekend, we leveraged an online community we built to acquire over 2,700 new customers in a four-day span, which was more than our leading competitor acquired over the course of two quarters in that year. Roughly 85% of those new customers came directly from our social community and 15% came from email campaigns or direct ads.

The fifth reason is that communities help disseminate content and offer venues where customers can share success stories with other customers. For example, imagine you run an online fitness or coaching business and you have a community of thousands of clients who interact together online. Now imagine we bring in a new cohort of customers who are unsure about their likelihood of success and are considering canceling after their first two weeks of being a customer. But, they are in this community with thousands of happy customers. How much more likely are they to stick with the program and your business if they can hear from other customers about their own personal success?

Don’t Forget to Grow With Your Customers

While sales are the lifeblood of any business and it is always important to acquire new customers constantly, it is critical to remember that just like your business is always growing and evolving, your customers are too. You will want to grow with your customers.

Your customers will grow in two primary ways. First, their needs will grow and evolve as they grow and evolve, and second, their needs will change as their lives change.

Our customers’ changing and evolving needs often arise from the value of your core product or service offering. Let’s revisit the marketing agency example. Imagine you have a business customer who initially signs up with you to handle their entire digital advertising needs. You absolutely crush it. You write incredible ad copy, produce amazing ads and winning campaigns, and you drive a massive return on investment with their ads for several years. Now this business is looking to add new customer acquisition channels and they are looking to develop PR, branding, and organic content at scale. Your agency may be able to help fill those roles by building out a team that can handle that next level of service they need. Effectively, you grow with your customers by building the next product or service they might need.

Our customers’ lives change over time and therefore their needs may change. Here is one example: Imagine you are a young general contractor who is starting their career by building starter homes for young families. You spend 10-15 years building a handful of starter homes a year for families in their twenties and thirties. During that time you do incredible work for these clients and maintain great relationships with them. After 10-15 years, these families are now looking to upgrade their homes to larger, higher-end, custom homes. Since this is a major investment for them, they want to go with a contractor they have experience with and one they trust. They call you to help them build their next home. If you have been planning ahead, you are prepared to service these larger needs of your clients, and you stand to much greater profits. Instead of having to go find all new customers to tap into a new market of home building, you have a captured audience who is asking you to level up with them.

Never neglect churn. Your ceiling is determined more by your churn than by your ability to sell.

Small changes to your churn rates result in massive differences in total revenues and profitability over time.

Make a product so good customers never want to go anywhere else.

Getting Your Customers Back

A major part of customer retention often goes unspoken and unrecognized. It involves getting your customers back.

There is a famous saying in marketing culture that it costs three times as much to sell to a new customer than it does to sell to a previous customer. From my experience, this is orders of magnitude off. Over the course of my career I have found the cost of acquiring a new customer is 10, 100, or even 1,000 times higher than the cost of selling a previous customer. Let me show you what I mean.

Imagine you run an online service business. Let’s just say it is a bookkeeping business. This business charges $250 per month for the service and the average initial client commitment is 12 months. It costs you, the business owner, around $500 to acquire a single customer. This means that you generate $3,000 per customer on their initial contract at a cost of $500 to acquire them.

Now fast forward your business 24 months.

This client churned around 12 months ago, and their lives have gone through some ups and downs. They are thinking about how satisfied they were when they were your client. Since you are a savvy business owner, you send out a New Year’s email campaign to your previous clients with a compelling offer to sign up so they can be prepared for the upcoming tax season. The offer was compelling enough that the client returns and enrolls for another 12 months.

Boom, another $3,000 in revenue.

Except this time, you didn’t spend $500 in ads to get them to sign up. You paid the cost of holding that email address for a couple of years and the cost of your time to write and send the email with the updated offer, which is probably about $1.50 in software fees and an hour or two of your business’s time. In this business, it was 333x cheaper to sell to a previous customer than to acquire a new one. Additionally, you know this is a high-quality client who will pay their bills and commit to the program.

New customers are harder to acquire, cost more to acquire, take longer to acquire, are harder to build trust with, and are less profitable than returning customers. Obviously you can’t neglect getting new customers, but you also shouldn’t neglect your previous customers either.

This sounds great in theory, but does this actually work in the real world?

In one of the businesses I helped build, 17.5% of all customers returned during a 3.5-year span. It was not a small number, either. This was 7,000 clients over 42 months. This means we brought back 165 customers a month or 5-6 clients per day - all at very low the cost of holding their email addresses. Imagine generating those kinds of sales on a daily basis with $0 in ad spend?

These strategies are worth it. The juice is definitely worth the squeeze.

In addition to having an incredible product or service, one of the most efficient ways to build a sustainable business is by creating strategies and systems that acquire customers from previous customers.

Now you are sold. That 333x reduction in customer acquisition cost was so attractive that you’ve decided that you need to spend some time and effort on building strategies and systems that help you get your lost customers back. But how many customers can you actually get back, and how do you actually get these customers back? It does not involve complicated email campaigns, god-like copywriting skills, or elite sales tactics. Instead, this can be accomplished this by focusing on two core ideas:

1. Be irreplaceable by making your service or product so good they want to come back.

2. Improve and update your service or product to solve the departed customers’ next set of problems.

Selling to returning clients can add back revenue at a fraction of the cost.

Be Irreplaceable

The example I gave you above about returning 7,000 clients over a 3.5-year period came down to one singular focus. We were hellbent on making our service so good people wanted to spend as much time with us as they could afford to. This meant that we relentlessly focused on the quality of the service and the relationships they built with our service providers and more importantly, the relationships our clients built with themselves while being in our coaching program. We effectively created an environment where people functioned as the best version of themselves while they were enrolled in our program. This led people to want to spend as much time as that version of themselves as possible.

This sounds simple and utilizes a specific aspect of consumer psychology: loss aversion. People often fear loss more than they enjoy the upside of a win. People prefer known quantities, especially when it comes to spending money. In fact, I would argue that most consumers are more likely to return to a business they know is average than risk spending money on a business they do not know.

Think about this from your own perspective. We all have our favorite go-to restaurant. You know the one. It’s good, not amazing. It’s consistent. You know exactly what you are going to get every time you go. You would probably rate it a 7 out of 10. Date night is coming up, and you need to choose a place to eat, and there is a new restaurant in town. It is a bit more expensive than your go-to. You have heard from two friends that ate there. One friend said it was awful and they would never go back. The other friend said it was great and would rate it an 8.5 out of 10. With that information, would you rather spend a lot of money on a new restaurant that might be a massive disappointment but also slightly better than your go-to restaurant or stick with what you know is a guaranteed “good” meal?

Most people would opt for their go-to restaurant. Most people are more afraid of losing something small than gaining something small. This also holds true in most scenarios, with the rare exceptions of people swinging for the fences in life or there is a massive upside.

Always Be Improving

No service or product is perfect for every client. Sometimes, your core service or product meets the true needs of 75-80% of your core audience, but you miss the mark on the 20-25% of clients, or those clients simply grow into new problems. This leads us to the second idea we focused on to bring customers back: updating our product to solve a problem. Specifically, update your product to solve issues that they noted previously and then tell them you listened.

No product or service is ever perfect. And clients who cancel a service do so for one of two reasons: 1) the service isn’t meeting their needs, or 2) the value of the service is not matching the dollar amount they are paying.

If you can solve those issues, you can reach out to clients and let them know that you have updated your service and can now directly meet their needs, or you can update them on the updated value equation and show them that your product not only meets their needs but provides so much value that they would be crazy not to come back.

Updating your service or creating a new service or making your service more valuable in response to your customers also achieves one of the single most important things a service-based business can do… you show them that you are listening and that you care enough about them to do the hard work to make sure you can meet their needs.

Selling to returning clients can add back revenue and eyeballs at a fraction of the cost.

Get customers back by making a product so good they want to come back and updating your product to solve their next set of problems.

Summary

The key to long-term growth isn’t just getting new customers—it’s keeping the ones you already have. Businesses with strong customer retention grow faster, more profitably, and with less effort.

• Lowering churn is essential—if customers leave too quickly, you’ll always be chasing new sales.

• Building customer loyalty through community and engagement helps retention.

• Returning customers are orders of magnitude cheaper than acquiring new ones.

As I write this updated version, we are no longer in the middle of a world crisis. We are on the other side of one. COVID-19 has receded into the category of historical event, the kind of thing that gets a chapter in textbooks and a handful of retrospective documentaries. Hospitals are no longer triaging in parking lots. Ventilator counts are no longer daily headlines. Most people have genuinely moved on.

But here’s the thing about moving on: it doesn’t change the underlying math.

When I wrote the original version of this article in 2020, I was attempting to crystallize something I had been turning over in my head for years, a slow-moving collision between the healthcare system we have built and the population it is being asked to serve. COVID didn’t create that collision. It just forced everyone to look at it directly, for a moment, before looking away again.

I have spent most of my adult life working at the intersection of biomedical science, healthcare, technology, and entrepreneurship, whatever that means. Over the last several years, specifically, I have been actively building technology, businesses, and education platforms around how we can better address the health crises that currently impact our society and that are the inevitable consequences of the path we are on. Outside of set work hours, I spend much of my cognitive free time thinking about the future health of our species. This is not a hobby. It is, at this point, something closer to an obsession.

To quote Agent Smith in the Matrix: “I am inevitable.” We have marched down certain pathways of cause and effect, and we must begin thinking clearly and building systems to address the effects that are coming our way. The original article was my attempt to lay that out. This is the updated version, same architecture, current data, and one additional section I didn’t write the first time around, because in 2020 I was still focused on the problem. Now I want to talk about who fills the gap.

Part 1: The Burdening

In science and medicine, definitions are important, as is precision. So let’s begin with one.

Burden can be a noun or a verb. As a noun, it is something that is carried, a load, a duty, a responsibility. As a verb, it means to load heavily, or to cause someone hardship or distress. The general thesis here is that the burden being placed on the healthcare systems in the United States, and in the world at large, is unsustainable. Furthermore, the healthcare system as it currently exists is being asked to address problems it was not designed to solve.

To fully address this I want to break it down into several parts based on first principles: the current capacity of the U.S. healthcare system, the health status of the U.S. population, and the economics of the U.S. healthcare system. Let’s take them in order.

Part 1.1: The Current Capacity of the U.S. Healthcare System

One of the more interesting things that resulted from COVID-19 is that people became acutely aware, probably for the first time, of what the actual capacity of our healthcare system looks like. The headline that circulated was: “There are only 1 million hospital beds in the entire country.” Unfortunately, that was only one piece of the story.

To understand the true capacity, we need to dig deeper. Hospitals are just one component of the healthcare system. In addition to hospitals, there are clinics (primary care), outpatient care centers (urgent care), and specialized care centers (nursing homes, psychiatric care, birthing centers). Here is the current high-level picture:

These numbers haven’t changed dramatically since 2020. What has changed is our understanding of how thin the margins really are and how much thinner they are getting.

Part 1.1.2: Hospitals and Carrying Capacity

Hospitals were created to serve a very specific function. They were built to provide short-term care for people with severe health issues arising from injury or disease. That is what they are optimized for. That is what they do well.

The distribution of hospitals across the U.S. is dominated by community hospitals, which make up the vast majority, roughly 5,100 of the ~6,100 total. Non-profit community hospitals account for more than 50% of that total. The number of hospitals has actually been declining since the 1970s, not growing, driven largely by consolidation and economics.

Now let’s look at what’s inside those hospitals, because this is where things get sobering.

There are approximately 924,000 total hospital beds in the U.S. Of those, about 790,000 are in community hospitals. Of those, approximately 107,000 are ICU beds. Breaking down the ICU beds further:

Here’s the perspective check. I live in the suburbs of Spokane, Washington, not a major city. The greater metro area has a population of about 520,000 people. In the event of a major health crisis requiring intensive care, we have enough ICU capacity in this country to handle roughly 20% of a metropolitan area that doesn’t even crack the top 100 in the U.S. That should stop you for a moment.

It gets more uncomfortable. The average hospital occupancy rate since 2000 runs roughly 66%. That means at any given time, of the ~924,000 hospital beds in the country, about 616,000 are occupied and only 304,000 are available. ICUs tend to run at even higher occupancy, and on a normal day there are likely fewer than 20,000 ICU beds available for a country of 340 million people.

What COVID revealed, what I was trying to articulate before COVID made it viscerally obvious, is that the carrying capacity of our hospital system works well for handling predictable, steady-state acute illness. It breaks under population-scale surges. If you took just 6% of the New York Metro population at peak COVID, you would fill every hospital bed in the country. Just 0.05% of that population would fill every ICU bed.

That is not a solvable problem by building more hospitals. Community hospitals cannot be architected to handle 10x or 20x surge events. The economics simply don’t work. This is a structural reality, not a policy failure, and it points to something more important: the solution to the chronic disease burden cannot be found inside hospital walls.

Part 1.1.3: Primary Care

Taking a significant liberty to oversimplify: if hospitals represent the acute care arm of the system, primary care represents the chronic disease management arm. Primary care physicians carry the theoretical responsibility for the ongoing health of the population, prevention, early detection, chronic disease management, the whole longitudinal arc of a person’s health over a lifetime.

As of the data we have, between 209,000 and 220,000 primary care physicians practice in the United States. That works out to roughly one primary care physician for every 1,500 Americans. In practice, given that physicians see an average of 16 to 17 patients per day and carry patient panels of around 2,200, the system processes approximately 460 million primary care visits per year, a number that grows as the population ages and the chronic disease burden expands.

The gap between supply and demand here is not a projection anymore. It is happening now. The number of designated primary care Health Professional Shortage Areas rose from 7,718 in 2024 to 8,467 in 2025, and the population covered by those designations increased from about 76.3 million to 92.3 million. The AAMC projects a shortage of up to 86,000 physicians by 2036, including between 17,800 and 48,000 in primary care specifically.

The experiment of “just train more doctors” has been running for a decade and it is not panning out. More physicians enroll in medical school than ever before. New medical schools open every year. And yet: in 2024, family medicine programs left 636 residency positions unfilled out of 5,231 as students chased higher-paying specialties. CBS News Only 24.4% of U.S. physicians currently practice in primary care, well below the accepted benchmark of 50%. ChenMed Harvard, Yale, and Johns Hopkins don’t even have full family medicine departments. If you are a medical student at an elite institution and you show interest in primary care, you are still, in 2025, likely to hear from peers and professors: if you’re so smart, why would you choose that?

The structural incentive problem is not going away. And even if it were solved tomorrow, training a physician takes a decade. The demand curve is not going to wait.

Part 1.2: The Health Status of the United States

Let’s start with the broadest number and work inward.

The United States spent $5.3 trillion on healthcare in 2024, $15,474 per person, accounting for 18% of GDP. CMS When I first wrote this article, the number was $3.5 trillion and I called it staggering. It has grown by $1.8 trillion in roughly five years. From a modest 5% of GDP in 1960, it rose to 13.3% by 2000 and has continued its upward trend to reach the current 18%, a growth trajectory that far outpaces other developed nations and leaves the United States with the highest health spending as a GDP share among OECD countries. Statista Projections carry that number to 20.3% of GDP by 2033.

According to the CDC, 90% of that cost is attributable to chronic and mental health conditions. The leading chronic diseases in the United States are heart disease, cancer, diabetes, and kidney disease, and obesity sits underneath most of them as the primary modifiable risk factor.

The relative risk data on this is worth dwelling on. In some populations, the relative risk of cardiovascular disease runs roughly 1.2 in individuals who are overweight and 1.5 in individuals with obesity. The relative risk of diabetes runs roughly 1.5 in individuals who are overweight, 2.5 in those with obesity, 3.5 in class II obesity, and 5.1 in class III obesity. One landmark study of roughly 100,000 people found that obesity reduced the number of disease-free years by approximately a decade, an effect greater than smoking, physical inactivity, and socioeconomic status combined, by a factor of two to four.

Part 1.2.1: The Obesity Picture in 2025

When I wrote the original article, the adult obesity rate in the U.S. sat at 42.4% and projections had us hitting 50% by 2030. The data since that time has told a more complicated story.

Current data places the adult obesity rate at approximately 40.3%, slightly lower than the peak but still higher than it was a decade ago. That modest plateau is real, but it comes with important caveats. The prevalence of severe obesity increased from 7.7% in 2013 to 2014 to 9.7% in 2021 to 2023, a 26% relative increase over the decade. - While overall rates may be leveling off, the severity distribution shifts in the wrong direction.

In 2024, all U.S. states and territories had an obesity prevalence of 25% or higher, with the Midwest at 35.9% and the South at 34.5% leading the nation. CDC Obesity rates are increasing among children and adolescents, with just over 21% of U.S. children and adolescents ages 2 to 19 having obesity, a rate that has more than tripled since the mid-1970s.

The thing I want you to sit with is this: the disease complications that arise from obesity lag behind the development of obesity. This happens for two reasons. First, most chronic disease develops through a lifetime accumulation of risk, and obesity acts as a magnifier and accelerant of that risk. Second, the diseases that follow obesity run on a physiological clock, type 2 diabetes developing over years and sometimes decades of smoldering subclinical pathology before it surfaces clinically. The same holds for cardiovascular disease, kidney disease, and much else.

This means that while we carry a substantial chronic disease burden today, we have not yet hit the peak. The obesity of 2010 is becoming the cardiovascular disease of 2025. The obesity of 2020 is becoming the disease of 2030 to 2035. Our population ages, obesity rates remain near historic highs, and the disease wave follows with a 7 to 12 year lag. We are watching a slow-motion surge build in real time.

Part 1.3: The Economics

This topic warrants a much longer treatment than I will give it here, but the summary matters.

Health spending totaled $74.1 billion in 1970. By 2000, health expenditures reached about $1.4 trillion, and by 2024 the amount spent on health more than tripled to nearly $5.3 trillion. Healthcare accounts for 24% of all government spending and stands as one of the largest categories of consumer spending. The rate at which healthcare consumes GDP has been one of the most consistent trends in American economics for sixty years, climbing from 5% in 1960 to 18% today, the greatest share of GDP in the entire world by a significant margin.

Over the 2024 to 2033 projection period, national healthcare expenditure growth averaging 5.8% is expected to outpace GDP growth averaging 4.3%, pushing the health share of GDP to 20.3% by 2033. We are heading, on current trajectory, toward a reality where one in five dollars generated by the entire American economy goes to managing disease. Most of it preventable. Nearly all of it chronic.

Part 1.4: Summary of Part 1

The current capacity of the healthcare system handles the predictable, steady acute medical care needs of the population reasonably well. It does not have the capacity, nor the design, to handle major surge events, as COVID made viscerally clear, nor to absorb the chronic disease burden of an aging, metabolically burdened population over the coming decades.

We have a growing and aging population, a population carrying high and entrenched chronic disease burden, and a disease wave building behind two decades of rising obesity. The physician pipeline will not solve this. Training more doctors does not fit the timeline of a problem that arrives faster than physicians can be produced. And even if it did, the physician model as currently structured, 15-minute appointments, volume-based incentives, reactive rather than preventive, reaches for the wrong tool.

The economic math points toward 20 to 25% of GDP going to disease management within the next decade. That number should prompt every person in or adjacent to healthcare to ask one serious question: is this sustainable, and if not, what changes?

Part 2: Of Powderkegs and Risk Escalation

The COVID crisis offered an opportunity to see our situation with unusual clarity. I want to revisit that framing because while the acute emergency has resolved, the structural conditions that made it dangerous remain fully intact.

Let’s review what we are actually dealing with.

The population that filled ICUs during COVID was not random. It was highly predictable. The individuals most likely to require intensive care, most likely to need ventilator support, most likely to die, were older adults with obesity, cardiovascular disease, diabetes, and chronic lung disease. Not because COVID singled those people out, but because those conditions had already spent years quietly degrading the physiological reserve those people needed to survive an acute respiratory insult. COVID was the spark. Chronic disease had been laying the kindling for decades.

This is the powderkeg, and it is important to understand what it is actually made of. The fuel is not insufficient ICU capacity, though that is real. The fuel is a population whose chronic disease burden has grown so large and so entrenched that any acute stress on the system, whether a novel pathogen, a natural disaster, or a bad flu season, cascades into a crisis because the baseline health of the population provides almost no buffer. We do not primarily have an ICU bed problem. We have a population health problem that shows up as an ICU bed problem when things go wrong.

Between 130 and 140 million Americans currently carry obesity. Roughly the same number carry established cardiovascular risk. About 37 million Americans have diagnosed diabetes and another 90 plus million have prediabetes. Tens of millions more carry chronic lung disease. These are not people who are one bad diagnosis away from needing a hospital. They are people who need better options for managing their health over the course of their lives, and right now the system offers them very few. The access points that exist are episodic and reactive. A physician visit every few months, a lab panel, a prescription renewal. There is no sustained infrastructure for the kind of longitudinal, behavioral, day-to-day support that actually moves the needle on chronic disease. And because that infrastructure does not exist, people do not know where to turn. They do not know what kind of professional can help them, what that help actually looks like, or how to find it. So they do nothing, or they cycle through the acute care system, using resources designed for episodic emergencies to manage conditions that are fundamentally chronic and longitudinal. The emergency department was not built to be the primary care setting for a diabetic patient who has no other access point. The ICU was not designed as the endpoint for a decade of unmanaged hypertension and metabolic disease. And yet that is increasingly what we are asking those institutions to do, not because patients are making bad choices, but because we have not given them better ones.

This is what I mean by risk escalation, transferring ownership of risk and accountability for that risk up the chain. Every year that we fail to meaningfully address the chronic disease burden at the lifestyle and behavior level, we push more of that risk upstream into the clinical system. Every year that primary care remains under-resourced and inaccessible, we push more of that risk further upstream into emergency and acute care. Every year that emergency and acute care absorbs demand it was not designed to handle, we edge closer to a system that breaks not because of a pandemic, but simply because the baseline load exceeds the design capacity.

COVID did not create this dynamic. It revealed it. And the uncomfortable truth is that building more ICU beds would not have fixed it. You cannot build your way out of a population health problem with acute care infrastructure. The math does not work, the economics do not work, and the timeline does not work. If we doubled ICU capacity tomorrow, we would fill it, because the population generating demand for that capacity is not shrinking. It is growing, aging, and accumulating more chronic disease burden every year.

The real intervention point is not downstream in the hospital. It is upstream in the daily lives of the population, in the choices, habits, environments, and support structures that determine whether a person arrives at sixty with metabolic resilience or with a decade of compounding chronic disease already on board. That is where the powderkeg gets defused. Not in the ICU.

Part 3: The Gap and Who Fills It

This section did not exist in the original article. In 2020 I was focused on describing the problem. In 2025 I want to talk about the solution, or at least the beginning of one.

Here is the central observation: an enormous gap exists between the physician’s office and the patient’s daily life. That gap is where the actual determinants of chronic disease live. It is where food choices happen, where movement habits form and erode, where sleep gets sacrificed and stress compounds. It is where a person either builds the physiological resilience to stay healthy for decades or gradually accumulates the risk that eventually surfaces in a clinical setting as a diagnosis.

Medicine has almost no presence in that gap. And that is not a failure of medicine. It is a recognition of what medicine was built to do. Physicians are trained to diagnose and treat disease. They are not trained, and do not have the time or the structural mandate, to coach people through the daily behavioral choices that would prevent disease in the first place.

So who does?

The answer that I keep coming back to, the one that the data, the economics, and the structural logic all point toward, is this: personal trainers, nutritionists, and health coaches are the next line of professionals that the healthcare system desperately needs and does not yet know how to use.

I want to be precise about this. I am not suggesting that a personal trainer replaces an endocrinologist or that a nutrition coach substitutes for a registered dietitian doing medical nutrition therapy. Scope of practice exists for important reasons and the lines should hold. What I am saying is different: the clinical system fails to occupy the space upstream of clinical disease, and the professionals best positioned to occupy that space are the ones already operating there.

Think about what a skilled personal trainer actually does. They meet a client where they are. They build a relationship over months and years. They understand that body composition, movement quality, and metabolic health are deeply intertwined. They provide accountability in a way that no 15-minute physician appointment ever can. They show up in the daily lived experience of the client in a way that no clinical professional does.

Think about what a skilled nutritionist or health coach does. They help people build habits that stick. They navigate the behavioral and psychological dimension of why people eat the way they eat and live the way they live, the dimension that medicine largely ignores because it does not fit neatly into a diagnosis code or a prescription pad.

National healthcare expenditure growth is expected to outpace GDP growth every year through 2033, pushing the health share of GDP to 20.3%. Health Affairs Most of that spending covers chronic disease. Most of chronic disease is lifestyle-influenced. The professionals with the deepest, most sustained access to lifestyle are not physicians. They are coaches and trainers.

The integration imperative is real. Some health systems have begun embedding health coaches in primary care settings. Lifestyle medicine as a formal specialty has grown substantially over the past decade. A handful of insurers are piloting reimbursement for coaching services tied to chronic disease outcomes. GLP-1 medications like semaglutide are generating genuine results in obesity, but a medication is not a behavior change. The evidence consistently shows that pharmacological and behavioral interventions work best in combination. The pill alone does not change the habits, the environment, or the lifestyle that generated the disease. The coach does.

The opportunity here for anyone operating in the fitness, nutrition, and wellness space is not incremental. It is structural. The healthcare system cannot solve the chronic disease problem from inside the clinic. The gap is real, it is enormous, and it waits to be filled by professionals with the right training, the right positioning, and the right integration with the clinical system.

Building the credentialing, the referral pathways, the outcome frameworks, the standards of practice that make that integration possible, that is the work of the next decade. It is also, I would argue, the most important work in health right now.

Closing

At this point it is important to step back and look at this from an event-agnostic perspective. The acute crisis of COVID has passed. The structural crisis it revealed has not. We have a healthcare system built for one thing being asked to do another. We have a population whose chronic disease burden grows faster than the clinical system can absorb it. We have a physician pipeline that cannot be built fast enough, and a financial model heading toward consuming a quarter of the entire American economy.

Risk escalation, kicking the can down the road, only works until you run out of road. Then you pick the can up at the end of it, all at once.

The next line of professionals is not a nice-to-have. It is a structural necessity. The personal trainers, nutritionists, and health coaches who understand the depth of this problem and position themselves accordingly are not filling a niche. They are filling a gap that medicine itself cannot close.