I’ve recently been meeting with many of my faculty members to discuss career development topics. One thing that struck me this year is that I feel like I’m having the same conversations with faculty every year, but nothing seems to change. I finally realized that, instead of just repeating myself and, to be honest, making little headway, I needed a new approach. Academic medicine is somewhat unique compared to other professions because promotion explicitly depends on building a reputation. Promotion guidelines literally specify, “Does this individual have a regional, national, or international reputation?” But even outside academia, I think most people, regardless of profession, care about their reputation and want to know how to build it. But after hundreds of conversations with faculty, I’ve realized the barriers are twofold, and I haven’t been addressing them adequately. It’s not just a lack of understanding of what needs to be done; more importantly, I think many people have an inherent aversion to the topic, which further hinders the transition from contemplation to action.

The elephant in the room

We first have to address the elephant in the room. For many people, this entire discussion feels uncomfortable and incongruent with their core values. Hence, we must address the “why” before we get to the “what.” While yes, some people crave the spotlight, many would really prefer to do good work and hope that will be enough. Just mentioning this topic makes many people cringe. Self-promotion feels uncomfortable, especially for physicians. To be honest, I only started engaging with social media because my publisher essentially told me I had to. So I think the key insight is to reframe the goal first. Whether we care about “reputation” or not, deep down most of us hope our work will have an impact. We want our ideas, discoveries, or inventions to travel beyond our immediate circle and make the world a little better. This is why many of us do our jobs in the first place. And when framed this way, perhaps the reason “reputation” matters becomes clearer, and the entire conversation becomes more comfortable. The goal isn’t really personal recognition. The goal of building a reputation is to extend your work's reach and impact. Just like it’s always easier to ask for something on someone else’s behalf than your own, let’s think about this exercise as doing something on behalf of your ideas, rather than yourself.

So where do I start?

Assuming I’ve now got you on board, or at least curious, we can move on to what I view as the first step: figuring out what you actually want to be known for. After all, it’s hard to build a reputation around something if you haven’t first figured out what that something is.

A few years ago, I spoke with a faculty member who was concerned she was ill-equipped to frame herself as an expert on topic X. Many others she could name knew more about the topic than she did, so she felt a bit lost. I pushed her to think differently. Rather than asking whether she knew more about X than everyone else, what did she actually do particularly well? It may not be the topic itself, but a unique skill related to how she works in this space. Where did she bring unique value? Could she build her work and future presentations around that?

While we all identify with what we do, our field or job title. But I think it’s more important, and a lot more interesting, to first identify our individual core strengths. Your expertise tells people what you know. Your core strength helps them understand why they should seek you out specifically.

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I can use my own story as another example. At the beginning of the pandemic, I appeared on Freakonomics Radio to talk about lungs and ventilators, which ultimately led to Breathing Lessons, my book about lung health. The opportunity came when I explained a complex topic, and I thought that might be where my core value lay. But over time, I realized my strength might be more nuanced than that. I am even more interested in how to break down complex topics to find hidden drivers, often the ones driven by human nature. Once I reframe the problem, the real solution becomes obvious.

I’ve applied this formula over and over in very different settings, whether that's trying to understand why so many patients with lung disease go undiagnosed or, as in this post, helping people think through their career development. The topics seem disparate, but my approach is similar. The more you understand your underlying strength, the more other people begin to understand what you uniquely bring to the table.

The Big Leap

So how do you find your own core strength? I do not pretend to be an expert. One of the real experts on this topic is Gay Hendricks, who writes about it in his book The Big Leap. In it, he describes four zones in which we spend our time, but the distinction I find most interesting is between the Zone of Excellence and the Zone of Genius.

Your Zone of Excellence is the bucket of things you’re extremely good at. You may have spent years developing these skills. The better you get at them, the more people ask you to do them. This is a particularly easy trap for successful people. If you are good at something, you’ll probably get asked to do a lot of it, and you can build an extremely successful career doing things in your Zone of Excellence.

But Hendricks argues that your Zone of Genius is different. It is the intersection of the things you most love doing, that come unusually naturally to you, and where your effort seems to create disproportionate value. He argues that if you can spend as much time in your Zone of Genius as possible, you’ll be happier and more fulfilled. The challenge is that these abilities may be difficult to recognize precisely because they don’t feel particularly difficult.

We tend to assume our Zone of Genius, or superpower, should be something impressive. But in fact, it may feel almost ordinary to you. And importantly, your expertise is probably not your superpower. You may be a doctor, a lawyer, or a scientist specializing in X, Y, or Z. Those descriptors tell people what you do or know. They don’t necessarily tell them what you do unusually well.

A physician might think of himself as an intensivist. Yet what distinguishes him is actually his ability to make good decisions with incomplete information. In another case, a lawyer may specialize in complex litigation. But her real strength is finding the one argument that changes how everyone sees the case. While teaching may be the identity, what makes her exceptional is recognizing exactly where a student became lost and finding another way in. The core strength isn’t really specific to the work. It’s specific to the person.

How do I identify my superpower?

So how do you figure out yours? Hendricks suggests paying attention to what you love doing most. Where does a relatively small amount of your effort seem to produce an unusually large result? Among the questions he suggests thinking about are:

“What do I most love to do?”

“What work do I do that doesn’t seem like work?”

“In my work, what produces the highest ratio of abundance and satisfaction to the amount of time spent?”

“What is my unique ability?”

Once you understand what you do unusually well, you can start making different choices about where to spend your time. Ideally, that also means spending more time doing work you find genuinely fulfilling. And over time, people will begin to associate you with that particular ability. A problem comes up, and someone thinks, I know exactly who we should call. That is the beginning of reputation. Many talented people exist in every profession. But reputation isn’t simply about being known. It’s about being known for something, which starts with understanding what you uniquely bring to the table.

The Upshot

Finding your zone of genius gives you a way to be more intentional about your career and spend more time focusing on activities that bring you joy. When you seek out work that draws on what you do unusually well, you will spend less time on things you are merely good at, and create more opportunities for others to see the particular value you bring. Then, building a reputation isn’t simply about getting more people to know you. It’s about giving them a reason to think of you. And when the right people know what you uniquely bring to the table, your ideas and your work can travel further than they ever could otherwise.

At work, my colleague Robert Dickson thought it would be fun to do something different this month with our weekly conferences, so we decided in August to feature a “How I Do It” series. Included in this was a talk by my colleague, Dr. Wassim Labaki, on the power of a good figure. It was so good that I wanted to share it here. But to be clear, Dr. Labaki deserves the credit for the content. He began with a story about Florence Nightingale. And for as many years as I’ve been in medicine, I can’t believe I hadn’t heard the story before.

Most know Nightingale as a nurse. You probably don’t know that she was also rigorously trained in mathematics by her father. She ultimately became the first woman elected as a fellow of the Royal Statistical Society. But perhaps more importantly, she not only understood numbers but also the power of how they’re presented. By the time she got to the Crimean War, she already understood that a number, on its own, persuades almost no one. But pair those numbers with the right picture, and numbers can win hearts and minds.

She once lamented, “Whenever I am infuriated, I revenge myself with a new diagram.” I have made hundreds of figures over the course of my career. Not once have I ever thought of it as an act of revenge. All too often, figures are the thing I build last, after the real work of the science is done. But I digress. Back to Nightingale.

She went to the Crimea in 1854 as a nurse and discovered something horrific. For the most part, soldiers were not dying of battle wounds. They were dying of cholera, typhus, and dysentery due to filthy field hospitals, contaminated water, and wards so overcrowded that infection moved through them like weather. Nightingale kept meticulous mortality records by hand, month by month, cause by cause. She reported the tables, but nobody in London was reading them. So she changed her approach.

It became known as the rose diagram or a polar area chart. She created one wedge per month, with each wedge's size determined by the number of soldiers who died and its color by the cause: preventable disease in blue, battle wounds in red, and everything else in black. You didn’t need to know a thing about statistics to look at it and see that the blue wedges swallowed the entire chart. This figure reached the War Office. It even reached Queen Victoria. And it became part of the case for the sanitary reforms that followed, ultimately credited with saving tens of thousands of lives.

And this brings us to several key concepts. I’ve spent years now assisting academic journals in editorial capacities, reading papers, and advising authors on improving their manuscripts. A good figure does something a results section never will: it travels. A great figure will get pulled into someone else’s talk, screenshotted into a tweet, and will become the one thing the reader remembers. It is often the thing we build last, but it really is the thing we need to think about first. We often think of writing a paper as the final thing to do, after we do the experiment or build the model. But selling the idea and communicating the insights are just as important as the work itself.

But what is it that really makes a figure memorable? How do we create that kind of figure? It turns out that the answer is often not more information, but rather less. In my opinion, the best figures have a point of view. They know what they are trying to show you. Yes, I know that sounds obvious. But we often ask a figure to do too much. We leave it to the reader to decide what matters to them.

So after you look at the data, start with the message. Decide first what you want the reader to see, then decide how to show it. Use color intentionally. Make the important comparison easy to find. And perhaps most importantly, don’t confuse completeness with clarity. A figure doesn’t need to contain everything you learned. It needs to show the thing you want someone else to understand. Yes, in some cases, we simply need to present all the data for completeness and scientific honesty. But in other cases, a good figure really can help the reader focus on the key messages you want to convey.

There is a wonderful simplicity to Nightingale’s diagram when viewed through this lens. She had mountains of data. She could have presented mortality rates, tables, monthly comparisons, denominators, and calculations. Instead, she made one fact visually overwhelming: soldiers were dying from preventable disease.

Which made me realize that making a good figure isn’t really a design problem. It is a framing problem. To make a great figure, you first have to decide what matters. You must find the signal in everything you’ve collected, then decide what deserves the reader’s attention. The figure is simply the final expression of that thinking.

We spend an enormous amount of our professional lives trying to persuade other people of things. But evidence rarely speaks for itself. Nightingale understood that more than 150 years ago. She figured out what people weren’t seeing and found a way to make them see it. The best figures don’t simply show us the data. Rather, they help us understand what the data means.

Thank you to Dr. Wassim Labaki for the talk and the inspiration behind this piece.

I don’t usually share personal photos, and I’m pretty sure this is my first Substack essay about sports. But I had the opportunity to attend the England–France bronze match at the FIFA World Cup this weekend with my football enthusiast son. Going in, I knew expectations for the game were low. The teams were exhausted. Harry Kane was pulled from the starting lineup. Analysts predicted neither team had their heart in it for a third-place match. But what I experienced was one of the most entertaining sporting events I’ve ever witnessed.

There was an energy to the match that was difficult to describe. Both teams attacked relentlessly. They played with pace, imagination, and confidence. There was very little hesitation. Instead of protecting a lead or waiting for the perfect opportunity, they seemed willing to create one. Every few minutes, there was another breathtaking run, another impossible pass, another goal. The crowd knew it was watching something special. Walking out of the stadium, I couldn’t stop thinking about why.

I’ve watched enough elite sport to know that the highest level of competition isn’t always the most enjoyable to watch. Championship games can become cautious affairs. The final World Cup match was scoreless until extra time. Every mistake carries enormous consequences. Players become understandably conservative. Coaches emphasize structure over creativity. The margin for error becomes so small that avoiding mistakes becomes the dominant strategy. The bronze match was a different game entirely. It was chaotic and fun, with the most goals scored in the entire tournament. The greatest disappointment had already occurred. Neither team would be lifting the World Cup trophy. But perhaps there was also something liberating about knowing that the worst had already happened. With less left to protect, they simply played.

Oddly, the game reminded me of one of my favorite scenes from the 1997 movie Gattaca. As boys, Vincent (Ethan Hawke) and his genetically gifted brother would swim out into the ocean to see who could go farther. Vincent always won. When his brother finally asked how, Vincent answered simply: “I never saved anything for the swim back.” I’ve thought about that line many times over the years. It isn’t really about swimming. It’s about the freedom that comes from fully committing to the moment instead of constantly conserving energy for every possible future outcome. Watching England and France, I wondered whether the same thing was happening. Neither team seemed to be playing as though they had something precious left to protect. They were simply willing to commit fully to every attack, every run, every opportunity.

It made me think about how often this scenario plays out in our professional lives. Medicine trains us to avoid mistakes. Science rewards rigor, skepticism, and careful interpretation. Leadership often requires thoughtful deliberation before action. Those are important instincts, and they serve an important purpose. But somewhere along the way, many of us begin to confuse avoiding failure with pursuing excellence. We hesitate to share an idea until it’s perfect. We wait another year to apply for the grant. We pass on writing the opinion piece because someone else probably knows more. We decline the invitation to speak because we’re worried we aren’t quite ready. We choose the safer project instead of the ambitious one because the safer one is less likely to fail.

Sometimes that restraint is wise. Sometimes it’s simply fear wearing the clothes of prudence. The irony is that the work we remember most, the discoveries that change practice, the leaders who shift culture, and the careers that take unexpected turns rarely come from people who spend all their energy trying not to lose. They come from people who were willing to pursue something meaningful, even knowing that failure was possible.

And I couldn’t help wondering whether freedom is one of the most underappreciated performance enhancers we have. Not freedom from preparation or discipline, but freedom from the constant fear of making a mistake. The confidence to attempt the difficult pass. To take the shot. To create instead of simply protect. Perhaps that’s what made the match so memorable. It wasn’t just extraordinary talent. It was the freedom with which that talent was expressed.

The Upshot

We all need rigor. We all need discipline. But there are moments when the brakes we’ve carefully installed become the very thing preventing our best work. The goal isn’t to abandon caution. It’s to recognize when caution has quietly become our default setting. Whether it’s a football match, a research project, or an important decision, some of life’s most extraordinary moments happen when we stop saving everything for the swim back and commit fully to the one we’re in.

Every once in a while, it may be worth asking ourselves a simple question:

What would I do if I wasn’t so worried about failing?

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A patient recently came into my office and sheepishly asked if we could discuss the AI review of his case. He happened to be a physician himself and had done exactly what millions of patients are now doing. He entered his symptoms into an AI platform, received a thoughtful explanation of the possible diagnoses, and came prepared with questions. But physicians are doing exactly the same thing. Platforms such as OpenEvidence and UpToDate AI have quickly become part of many clinicians’ daily workflow.

In fact, what made me smile is that I had also used AI to review aspects of their case, so now I was curious to compare notes. What surprised me was how different our notes were. Neither of us was right or wrong. We just approached the problem very differently. His list of what might be wrong with him was fairly broad: nutritional deficiencies or an autoimmune disorder. This isn’t what I was concerned about at all. By that point, I had already identified the one abnormal finding that concerned me most and was using AI to think through the most appropriate next step. This is probably my most common use for AI platforms, to determine what tests to order when a potential diagnosis lies outside my expertise as a pulmonologist.

In neither case had the AI had done a poor job. I just realized the questions we had asked of it were very, very different. My patient had asked what was most likely causing his symptoms. It was a perfectly reasonable place to start. Yet it wasn’t the question occupying my mind. By the time I turned to AI, I had already spent considerable time deciding what the problem actually was. I wasn't asking it to diagnose my patient. I was asking a much narrower question: given this particular abnormal finding, what should I do next?

That encounter stayed with me because it mirrored something I had been discovering in my own use of artificial intelligence. Like many physicians, I’ve gradually incorporated AI into my daily work. I use it to summarize papers, explore unfamiliar topics, challenge my thinking, and occasionally to help organize complex clinical problems. I remain amazed by how these systems retrieve information instantly, synthesize enormous bodies of literature, and often produce thoughtful, well-reasoned responses. More than once, I’ve found myself thinking, “That’s an excellent answer.” But I've noticed something about my own conversations with AI. I rarely stop after the first answer. The first answer almost always leads me to another question.

Suppose I ask AI why a patient is short of breath. It will generate a careful differential diagnosis with appropriate supporting evidence. But if I then ask what diagnosis would be catastrophic to overlook, the emphasis changes. If I ask what findings don’t fit the leading diagnosis, I receive a different analysis. If I ask what assumptions I’m making, or what additional history would most change the differential diagnosis, the conversation evolves yet again. Nothing about the patient has changed. The only thing that has changed is the question.

We often think expertise is measured by knowledge. Medical education certainly reinforces that belief. Students memorize anatomy, physiology, pharmacology, pathology, and thousands of clinical facts. Licensing examinations reward correct answers, and board certification reinforces the importance of mastering an ever-expanding body of information. It’s easy to conclude that experienced physicians are simply people who know more than everyone else. But after two decades in practice, I no longer think that’s what distinguishes the best clinicians.

After two decades in practice, I’ve come to think we’ve misunderstood whta expertise actually is. The best doctors don’t necessarily have better answers. They ask better questions. That realization may sound deceptively simple, but I think it lies at the heart of clinical reasoning. Experienced physicians are constantly reframing the problem in front of them. What diagnosis explains all of the findings rather than just most of them? What would I regret missing? Why doesn’t this piece of the story fit? What additional information would change my thinking? Every answer generates another question, and every question reshapes the differential diagnosis. Medicine is rarely a straight path toward certainty. More often, it is a process of gradually reducing uncertainty while always remaining open to the possibility that we are wrong.

The emerging literature is fascinating. Large language models perform extraordinarily well on standardized medical examinations and increasingly sophisticated diagnostic reasoning tasks. But they also reveal something important. Their answers depend heavily on the information they're given and the way the problem is framed. In other words, they excel at answering questions that are well posed. AI answers the questions you ask. Physicians spend years learning to recognize the question they should have asked.

I do think that AI has ultimately made me a better physician. Ironically not because it has given me better answers, but because it has encouraged me to ask more questions. When an answer seems convincing, I now find myself immediately asking what alternative explanations deserve consideration, what evidence argues against my leading diagnosis, and what assumptions I may not even realize either of us are making. AI has become a catalyst for intellectual humility. It has reminded me that confidence and correctness are not the same thing.

The Upshot

Increasingly, I believe expertise will not be defined by possessing more information. It will be defined by knowing how to frame the problem. Artificial intelligence has made knowledge more accessible than at any point in history. But clinical judgment is shaped by something more than information alone. It develops through years of caring for patients, seeing the same disease present in countless different ways, making difficult decisions with incomplete information, and carrying the memory of the cases that changed how we think. Whether AI will someday acquire something analogous to that experience remains to be seen. For now, it has reminded me that the questions we ask are often more important than the answers we receive.

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Recently, I was talking with a group of friends about research when someone mentioned that one of the most accomplished senior investigators I know views research as a creative outlet. The comment surprised me, not because I disagreed with it, but because I had never thought about research in those terms before. Research was something I associated with rigor, analysis, and discipline. Creativity belonged somewhere else. It belonged to artists, writers, musicians, and designers. Yet I found myself returning to the observation over the next several days because it seemed to explain something I had struggled to understand about myself for years.

I have never felt like the stereotypical researcher. Perhaps it was all the glassware I broke in organic chemistry lab. Perhaps it was the realization that I am fundamentally incapable of following a recipe exactly as written. Even now, I tend to see instructions as suggestions. Throughout my life, I have been drawn to activities that involve making things. Sometimes that has meant writing. Sometimes it has meant crafts, home projects, art, or gardening. I have always enjoyed the process of imagining how something could be improved, redesigned, or viewed from a different perspective.

For much of my career, I viewed those interests as separate from my scientific work. They were hobbies. Diversions. Things I did when I was not doing research. Looking back, I am not sure that distinction is accurate.

One of my earliest mentors once asked whether I thought I could come up with my own research ideas. At the time, I remember thinking that I probably could, but that it was difficult to know which questions mattered until I understood a field deeply enough. Years later, I realize that conversation was really about something else entirely. It was about where ideas come from.

The longer I have spent in academic medicine, the more I have come to appreciate how little we talk about that question. We spend years teaching scientists how to evaluate ideas. We teach statistics, epidemiology, study design, and critical appraisal. We teach people how to identify bias, recognize methodological flaws, and determine whether a conclusion is supported by the evidence. These are essential skills. They are the foundation of good science. But they are not the same thing as generating an idea in the first place. As a mentor, I should be talking about this more.

How does someone identify a question worth pursuing? Why do some investigators repeatedly see opportunities that others miss? Why do certain people seem able to generate hypotheses with remarkable consistency while others struggle to move beyond incremental extensions of existing work?

I suspect we underestimate the role of creativity.

The word itself makes many scientists uncomfortable because it sounds imprecise. Yet when I look at the researchers I admire most, creativity is often one of their defining characteristics. They see connections that others do not. They approach problems from unexpected angles. They borrow ideas from one field and apply them to another. They are often curious about subjects far beyond their immediate area of expertise.

Benjamin Franklin is remembered as a scientist, but he was also a printer, writer, inventor, diplomat, and entrepreneur. He moved effortlessly between disciplines and seemed incapable of limiting his curiosity to a single domain. Thomas Edison approached invention less as a series of isolated breakthroughs and more as a lifelong process of experimentation and tinkering. What made these individuals remarkable was not simply intelligence. It was their ability to draw connections across seemingly unrelated areas of knowledge.

The more I think about it, the more I wonder whether creativity is not about creating something entirely new. Very little in science emerges from a vacuum. Most discoveries build upon observations that already exist. Perhaps creativity is better understood as the ability to recognize relationships that others miss. A new hypothesis often begins with two ideas that previously appeared unrelated. The breakthrough comes from realizing they belong together.

Research suddenly looks very different when viewed through that lens. Scientific discovery is not simply the accumulation of knowledge. It is also the organization of knowledge. It requires pattern recognition, analogy, synthesis, and reframing. It requires the ability to ask whether an observation from one domain might help explain something in another. In hindsight, these connections often seem obvious. Before the discovery, they rarely do.

Looking back at my own career, many of the ideas that ultimately proved most valuable did not emerge while reading another pulmonary paper. They emerged while writing, teaching, leading teams, talking with colleagues from different disciplines, or trying to explain a complicated concept in a simpler way. The scientific insight often arrived later. What came first was a connection.

This realization has fundamentally changed how I think about hobbies and “side interests”. For years, I assumed they were separate from my work as a scientist. Increasingly, I wonder whether they have been helping me to develop one of the most important scientific skills all along. Every book, hobby, project, and conversation expands the pool of ideas available for future connections. Most will never lead anywhere. But a few will. The challenge is that we rarely know which ones in advance.

The Upshot

The timing of this discussion feels particularly relevant. We are entering an era in which knowledge itself is becoming increasingly accessible. AI can retrieve information, summarize literature, generate outlines, and answer questions in seconds. Many of the tasks that once signaled expertise are becoming easier to automate.

Yet AI has also made me think more carefully about where ideas come from. Information is not the same thing as insight. Knowing facts is not the same thing as recognizing which facts matter. The challenge is no longer simply finding answers. Increasingly, it may be asking better questions.

Creativity may still represent one of the most valuable human skills in an age of abundant information. The ability to connect ideas, draw from diverse experiences, and recognize possibilities that others overlook is becoming more important, not less. Seemingly unrelated interests matter more than we realize. They expand the pool of experiences from which new ideas emerge.

New ideas rarely appear out of nowhere. More often, they emerge from the unexpected intersection of things we already know. AI may make knowledge more accessible than ever before. What remains uniquely human is deciding what is interesting, what is important, and what might be possible.

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While we tend to think of careers as individualistic pursuits, they are ultimately strongly shaped by other people. Through who gets invited in, who gets introduced, and who gets named in rooms where decisions are made. We would all like to believe that good work rises on its own. And I believe that it does, eventually. But early on, something else matters more. Before you are known for your work, you are likely known for something else.

Let me explain. It took me a while to fully understand this. I had to go full circle, from mentee to mentor. Early in my career, I was very fortunate. I had a great mentor. I’m fortunate that we remain close friends and collaborators. But as we all know, mentees will never truly succeed without the next step - sponsorship. This is what changes career trajectories. Mentors help you develop. Sponsors ensure you are present where decisions are made. Sponsors recommend you before you feel ready. They attach their credibility to yours and, at times, give up their own opportunities or create new ones so that you can step in. The best ones don’t just get you invited to sit at the table; they create a seat for you that wasn’t there to begin with.

I was lucky. My mentor was a fabulous sponsor. But not everyone is sponsored equally, even within the same environment. Some of that reflects structural realities we are increasingly aware of. Gender, personality, and familiarity all shape who is pulled forward. These forces are real.

But there is also a more immediate factor. Early in a career, sponsorship often follows reliability. The individuals who are advanced first are not always the most brilliant. They are the ones a mentor trusts to deliver.

When I began working with my mentor, I was an unknown. I practically begged for projects, finishing book chapters and papers that had been sitting on the shelves. I completed them thoroughly, with minimal help, in record time. I followed my mentor at meetings, stood nearby during conversations, and waited for the moment when I might be included. I never failed. I never said no. I said yes to projects that were not always visible or particularly appealing. I showed up and followed through, without fail. Was I always building my CV? No. But I was learning. The kinds of things that are difficult to teach without living them. But equally important, I was building my mentor’s trust. At the same time, I was bringing new ideas to the table, demonstrating initiative, anticipating needs, and building projects that advanced the team's broader goals.

Those early signals matter. They make it easier for someone to advocate for you because they are not only evaluating your potential. They are assessing whether you can be relied upon.

Sponsorship, in that sense, is not just a judgment of talent. It is a willingness to visibly take a risk on someone.

We tell trainees to protect their time. What we don’t say out loud is that early on, the people who say yes are the ones who get noticed. Of course, once you are established, learning when to say no becomes essential. Protecting your time matters. Early in a career, however, the opportunity to demonstrate reliability often carries more weight than selectivity. Saying yes is not always about getting an opportunity that will directly advance your career. Sometimes, it is about recognizing that each opportunity gives others a chance to observe how you think and work. Those observations accumulate and eventually shape how others speak about you when you are not present.

Mentorship, viewed this way, is not simply an individual relationship. It reflects the culture of an environment. It determines who gets the chance to build trust early, and who gets overlooked.

In some environments, people operate in isolation. There are few mentees, little continuity, and limited effort to bring others forward. In others, mentorship is embedded. Introductions are made without prompting. People are discussed in rooms they have not yet entered. Access expands more naturally, and more people have the opportunity to be seen, tested, and ultimately trusted.

I have been fortunate to experience the latter. My academic “father” and “grandfather” remain part of my professional life, continuing to offer guidance and advocacy in both visible and subtle ways. That continuity has shaped how I think about my own role now as a leader.

Because if early careers are built on signals of reliability, then leadership is about making sure more people have the chance to send those signals. That means paying attention. Who is ready for more responsibility, even if they are not asking for it. Who needs an introduction? Who is being overlooked?

Part of mentoring well is identifying potential before it is obvious. Part of leading well is creating environments where more people can show how they think, how they work, and whether they can be counted on. Which means I am constantly looking for those early signals, creating opportunities for people to demonstrate them, and moving them into positions of responsibility as soon as they are ready. Because in the end, the measure of a career, the measure of my career, is not only what I’ve accomplished, but whether others are better positioned because I helped create space for them.

The Upshot

Early in a career, people are not just evaluating your work. They are deciding whether you can be counted on. The ones who move forward first are not always the most brilliant. They are the ones who show up, follow through, and make it easy for others to trust them. That trust is what sponsorship is built on. It is what makes someone willing to take a risk on you.

For those in positions to mentor, the responsibility is not just to advise. It is to notice early, create opportunities, and move people forward once they have earned trust. Careers accelerate when someone is willing to bet on you. Leadership is about widening the circle of who gets that chance.

There are patients you take care of, and then there are patients who stay with you. I lost one of those today. Not just a patient, but someone I had known for nearly 20 years. She was in Florida for the winter. I hadn’t seen her in a while. With COPD, that can mean things are stable, or at least stable enough. But she was never really routine.

She texted me constantly. She asked more of me than almost anyone I’ve ever taken care of. She was sharp, a retired businesswoman, the kind of person who read everything and questioned everything. We didn’t always agree. She was pro-Trump. She didn’t want the COVID vaccine. We had real debates, the kind where you balance evidence with relationship, knowing that if you push too hard, you risk losing both. But she trusted me. And I respected her. Somewhere along the way, she stopped being just a patient.

This morning, I got a call from her physician in Florida, someone I’ve never met, telling me she had died suddenly of sepsis. He knew we were close. As a doctor, he knew I needed a phone call from someone who had been at her bedside, who knew what had happened. I have practiced medicine for over 20 years. I’ve lost many patients. So what surprised me was not the news, but the feeling. A small part of me suddenly felt missing. I keep thinking I’ll hear from her. Another text. Another question. I found myself scrolling my phone, to see her last text. Another point she wanted to debate.

But I won’t. And there’s no real place for that in medicine. I’m not part of her family. I won’t be at the funeral. I won’t sit in a room with people telling stories about her, the way families do when they’re trying to make sense of a loss. There’s no ritual for this part. No moment where you get to say goodbye. Just a phone call. And then… nothing.

Earlier this year, I lost another patient. Maybe we’re not really supposed to have favorites, but I’ll be honest, he was one of them. He was a pilot for a major airline, developed inflammatory interstitial lung disease, and was told would never fly again. We worked through it together. We got him off oxygen, and then triumphantly back in the cockpit. The FAA physicians told him they could count on one hand the number of pilots who had come back the way he had. He went from needing life saving oxygen around the clock to holding the lives of hundreds of passengers in his hands every day. But just like the patient I lost today, he wasn’t just a clinical success story. He was my friend. Every year he invited me to his holiday party. I don’t know why I never went. I found out months after he died that he’d suffered a heart attack. Looking back, I wish I had gone to just one of those parties.

But this is the part of medicine we don’t talk about much. Doctors are very good at building walls. We learn early how to compartmentalize, how to take the hardest moments and set them aside so we can keep moving. There is always another patient, another decision, another problem that cannot wait. And most of the time, it works.

But there are some patients who don’t stay where you put them. They follow you home. They show up in your thoughts. They text you. They challenge you. They make you better. And when they’re gone, the absence is not abstract. It is specific. It has shape. You feel it in the empty spaces where they used to be.

Recently, I saw one of my own physicians whom I’ve had the privilege of knowing for many years. I asked what I thought was a simple question, but for just a moment, something shifted. The composure gave way. A glimpse of everything she was holding. We are taught not to show that. To be composed. To be objective. To be steady. But we are not untouched. She didn’t want to appear “unprofessional.” I reminded her that long before she ever became my doctor, she was first my friend.

I think this is what happens when you do this work long enough. You do not just accumulate knowledge or experience. You accumulate people. Some pass through. Some stay. And a few become part of the way you understand the world.

We like to believe that professionalism means distance, that caring deeply is something to be managed, contained, kept from spilling over and that the boundaries we build are what allow us to do this work well. But I am not so sure.

Because in the end, those boundaries are not what I remember. I remember the patients who stayed. The ones who asked more, who pushed back, who trusted me anyway. The ones who blurred the lines I was taught to keep clear. And I wonder if that is not a failure of professionalism, but the point of it. Because no one really wants a doctor who feels nothing. And sometimes, the boundaries are not meant to hold.

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Somewhere along the way, we confused being responsive with being effective. I can get through an entire day answering emails, attending meetings, reviewing documents, making decisions, and still end my day with the nagging sense that I have not actually gotten anything accomplished. The work that requires thought, synthesis, and creativity remains untouched. Sound familiar? Deep work, the kind that requires sitting with an idea long enough for it to sharpen, has become surprisingly difficult to protect. Writing, designing, analyzing, or reframing a problem. These are not tasks you can squeeze in between responding to emails and zoom meetings.

So this past week, I tried something different. I pulled in a colleague who was working on the same project, and we decided to be deliberate about it. We booked a room together, shut the door, ordered food, and worked side by side for the day. No meetings. No email. No multitasking. By the end of the day, we both had something tangible to show for it. Not administrative progress, but intellectual progress. It worked better than I expected, and it forced me to confront a simple truth. Deep work isn’t gone and it isn’t any less needed, but the further into our careers we get, the less fiercely we protect it.

You’re Not Imagining It. It Is Harder.

My colleague and I joked this past week that what we had recreated was simply what work felt like twenty years ago, before constant notifications and inboxes that ping every few seconds. He might be right. Some of this is undoubtedly role related. Bigger positions bring more decisions, more requests, and more people who need you. But some of it is cultural. Email has shifted from asynchronous communication to something closer to live chat. Text messages carry an implied urgency. Notifications fragment attention in ways that feel minor in isolation but accumulate over time.

While I pride myself on “multitasking,” I think to some extent it’s a myth. I am often cognitively scattered the majority of my day. Constant context switching is not neutral. Research on attention suggests that when we move rapidly between tasks, a portion of our focus remains stuck on the previous task, reducing our effectiveness on the next. The cost is subtle but real. It shows up as shallow thinking, slower synthesis, and the erosion of creative capacity.

Why Deep Work Matters

Cal Newport defines deep work as the ability to focus without distraction on cognitively demanding tasks. He argues that this capacity is becoming both rarer and more valuable at the same time. That framing resonates because shallow work keeps systems running, but deep work is what moves them forward.

Many people whose work reshaped industries understood this instinctively. Bill Gates famously took regular Think Weeks, isolating himself with stacks of reading material and emerging with strategy memos that influenced Microsoft’s direction. Carl Jung retreated to a stone tower to think and write. Writers have rented hotel rooms to finish manuscripts when ordinary life proved too distracting. These were not indulgences. They were structural acknowledgments of how the mind works.

In medicine, science, and leadership, deep work is not optional. It is where new frameworks are built and complex data are interpreted rather than simply processed. The grant that reframes a field, the analysis that reveals a pattern others have missed, the essay that clarifies a messy debate does not come together in five minute increments between meetings. Without deep work, it becomes easy to stay very busy while producing little that endures.

How to Reclaim It

The solution is not willpower alone. Most people who successfully protect deep work do so by building structure around it. They schedule it deliberately and treat it as immovable. They remove distractions rather than trusting themselves to ignore them. They create rituals that signal a shift into a different mode of thinking. I had dinner with a friend last night who is working on writing a new book, and so she asked me about my experience with writing Breathing Lessons. She specifically asked me where I wrote the book. I hadn’t actually given it much thought, but she was right to think about this. Turns out, I wrote much of the book on my back porch. Moving locations from my usual desk signalled an internal shift in mindset, allowing me to better focus on the book and more easily block out other distractions associated with sitting at my “work desk”.

What has also surprised me is the power of shared deep work. Sitting in a room with someone equally committed, created accountability without requiring constant collaboration. We were not talking the entire time, but we were aligned in purpose. There was less temptation to drift, to check messages, to fracture the day into smaller and smaller pieces. Deep work does not always have to be solitary to be effective. I have also previously held “brainstorming” retreats with my research group, where we spend the day moving through a series of early ideas, weighing their potential for success, and what would be required to truly launch them into full fledge research projects. I’ve found these sessions to be fabulously productive as well.

Protecting this kind of time can feel almost countercultural in an environment that rewards responsiveness and availability. It may mean slower replies. It may mean saying no more often than feels comfortable. But if our days are entirely reactive, we become highly efficient at reacting and gradually lose the space to shape what comes next.

The Upshot

If your day is entirely reactive, you will become extraordinarily good at reacting. You will answer quickly. Decide quickly. Clear quickly. But you will slowly lose the ability to create something that was not already there. Deep work is where new ideas form, where strategy clarifies, where data becomes insight instead of output. It is where leadership actually happens.

While protecting that time may feel inefficient in the short term, over the long arc of a career, the people who shape fields are not the ones who answered the most emails. They are the ones who carved out the space to think. This week reminded me that if we want to build anything that endures, we have to make room for the silence required to build it.

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You may not know it, but for most of its history, the Environmental Protection Agency has treated public health as something that belongs in its calculations. When the agency set limits on air pollution, it counted the lives those rules were expected to save. It quantified fewer asthma attacks, fewer heart attacks, and fewer premature deaths. The estimates were debated and revised over time, but the underlying assumption held: protecting health was core to environmental regulation. Until now.

According to reporting by The New York Times, the EPA plans to stop monetizing the health benefits of reducing two of the most widespread and deadly air pollutants: fine particulate matter and ozone. Industry compliance costs will still be calculated. Lives extended and illnesses avoided will no longer appear in the cost-benefit analyses that justify clean-air rules.

An EPA spokeswoman told the Times that the agency would still “consider” health effects, but “not monetizing does not equal not considering or not valuing the human health impact.” The distinction matters, because monetized benefits are what historically made regulations defensible on paper. On paper, the change is narrow. In practice, it reshapes how air policy works

What polluted air actually does

Fine particulate matter most relevant to human health, known as PM2.5, consists of particles less than 2.5 micrometers in diameter, small enough to penetrate deep into the lungs and pass directly into the bloodstream. Ozone, a smog-forming gas created when emissions from power plants, factories, and vehicles mix in sunlight, inflames airways and worsens respiratory disease.

Long-term exposure to both is linked to asthma, cardiovascular disease, stroke, and premature death. Even moderate exposure to PM2.5 can damage the lungs about as much as smoking, according to research cited by the EPA and referenced in the Times report.

As a pulmonologist, I see it play out clinically. My patients get worse when pollution levels are high. Over longer periods, we now know that chronic exposure does not just exacerbate disease. It helps cause it.

When the EPA previously tightened PM2.5 standards, the agency estimated the rule would prevent up to 4,500 premature deaths and 290,000 lost workdays in a single year. For every dollar spent on reducing PM2.5, the EPA calculated as much as $77 in health benefits. Hospitalizations would fall. Lives would be saved.

What happens when health drops out of the math

Agency officials now argue that monetizing health benefits creates “false precision.” In internal documents reviewed by The New York Times, political appointees described past EPA analyses as providing the public with “false confidence regarding the monetized impacts” of PM2.5 and ozone.

To “rectify this error,” the documents state, the EPA will no longer monetize benefits from PM2.5 and ozone. This language is now being inserted into regulatory impact analyses accompanying new rules, including proposals to weaken limits on emissions from power plants.

While uncertainty is real, removing health benefits from the analysis does not resolve it. Cost-benefit analysis shapes outcomes. When health effects disappear from the benefits side of the ledger, regulations become harder to defend. Industry costs remain visible and exact. Public health becomes something that can be acknowledged in narrative form, but not weighed.

As Richard Revesz, former head of the White House Office of Information and Regulatory Affairs, told the Times: “If you’re only considering the costs to industry and you’re ignoring the benefits, then you can’t justify any regulations that protect public health.” What disappears here is the formal recognition that preventing illness and early death is central to environmental policy rather than incidental to it.

Who bears the cost of this decision?

The truth is that air pollution does not distribute itself evenly. It concentrates near highways, power plants, refineries, and industrial corridors. The health burden is heavier in communities that already experience higher rates of asthma, cardiovascular disease, and shortened life expectancy.

Clean air is not a lifestyle preference. It is basic infrastructure. When protections weaken, the consequences are predictable, even if they are not evenly shared. The EPA’s state mission is to protect human health and the environment. You cannot tell me that removing lives saved from its core calculations does not alter the mission. Health remains acknowledged, but it will no longer anchor the decision-making process.

The Upshot

For decades, clean-air regulation produced measurable gains. National levels of fine particulate matter fell substantially after standards tightened. Ozone declined. Hospitalizations dropped. Premature deaths were prevented. These improvements did not happen by accident. They followed a regulatory framework that treated health outcomes as central, countable, and worth defending.

The EPA’s own analyses made that explicit. The agency repeatedly concluded that the greatest benefits of air-pollution regulation came from reductions in premature mortality attributable to particulate exposure. Progress, however, has never been guaranteed. Recent evidence suggests that declines in PM2.5 have begun to plateau in parts of the country, even before accounting for wildfire smoke. Climate-driven pollution is already testing the limits of existing protections. This is not a moment of excess regulation.

Against that backdrop, removing lives saved from the analytic core of air-pollution policy is not a neutral adjustment. It weakens the very justification that made progress possible. We did not improve air quality by accident. We improved it by insisting that health belonged in the math. Choosing not to count lives now reflects a decision about what future protections will be built to defend, and which ones will be allowed to slip. This decision belongs to a broader dismantling of public health infrastructure, where protections are weakened not by overt repeal, but by removing the tools that once made them defensible.

It’s the end of the year, so as is my annual tradition, I sat down this weekend to pen the top ten things at work I am grateful for, before sharing with my faculty. It definitely wasn’t the year I thought it would be. It has been so, so much harder. It has been difficult to witness the deprioritization of public health and the harm this has caused to patients both now and well into the future. Doing science has gotten harder and encouraging young people to follow this path even harder.

So it may seem a little counterintuitive, but as this year comes to a close, I’ve decided that now more than ever I must prioritize gratitude. Not so much as a trait, but rather as a daily practice.

There’s a lot of incredible research around the concept of gratitude. One of the most influential findings in modern psychology came from a deceptively simple experiment. Participants were asked to spend a few minutes each week writing down a handful of things they were grateful for and why those things mattered. Another group wrote about frustrations and hassles. A third group wrote about neutral events.

The results were striking. The gratitude group did not just report feeling happier. They slept better. They exercised more. They had fewer physical complaints. They showed up to their lives with more energy and engagement. But nothing about their circumstances had changed. Their workloads stayed heavy. Their stressors did not disappear. Their lives were not made easier.

What changed was how they experienced the same reality. Gratitude did not eliminate difficulty. It expanded capacity.

This past year has been hard. It has been marked by uncertainty, shifting ground, and long stretches of waiting without clarity. But gratitude is not denial or pretending things are fine when they are not. It is not a refusal to acknowledge loss, fatigue, or disappointment. This year has been filled with all of those things for so many.

For me, gratitude instead is a conscious decision to widen the frame and allow more than one truth to exist at the same time.

Why gratitude matters

When we focus exclusively on threat, failure, and uncertainty, our brains stay locked in a defensive posture. This can be adaptive in the short term, but it is exhausting over time. The daily practice of gratitude helps to remind us that not everything is broken. There are still sources of strength, connection, and meaning available. Good things are still happening.

This is why gratitude has been shown to improve productivity and performance. Not because grateful people care less, but because they are not cognitively consumed by what is wrong. They retain bandwidth and can see options again.

I think the same is true for relationships and leadership. Teams in which appreciation is expressed openly are more engaged and more willing to contribute. People are more likely to speak up, to take risks, to stay. It creates a sense of community.

There is also a growing body of evidence linking gratitude to better sleep, lower stress levels, and improved physical health. Again, not because stress disappears, but because it is processed differently. The body recovers more effectively when the mind is not constantly braced for impact.

What does this look like in practice?

For every person and every organization, gratitude will look a little different. What matters is not the specific form it takes, but whether it moves from being an occasional feeling to a shared practice. Gratitude has the greatest impact when it is made visible, collective rather than private, and part of how people experience their work and one another.

To make this more concrete, I personally did two things at work this year to foster gratitude in the workplace.

The first, thanks to a very talented and hardworking individual in my group, was the creation of a gratitude hub on our internal website. Think of it as a kind of Facebook for gratitude. Anyone can create a public or private post to thank someone else for kindness, collaboration, or going the extra mile. For years, I had watched these exchanges happen behind the scenes in emails I was cc’d on. By making gratitude public and shared, we can shift it from something that happens in isolation to something the entire community can witness, participate in, and feel.

The second thing I just finished working on this week, and have not yet shared with the group, was an exercise in collective recognition. I asked everyone to submit the names of three people they work with who lift them up, along with why. I used that information to create a positive energy map for the entire group. The experience was eye-opening. It revealed a set of unsung heroes who are doing an enormous amount of emotional and connective work that sustains the organization. These are leaders without titles, people who are supporting others in ways that I had not fully recognized (which I will rectify!).

These initiatives are my gratitude in practice. We must pay attention to where energy, care, and support are actually coming from and name the people and the work.

The Upshot

Gratitude will not erase the hard parts of this year. But it can change how heavy all of it feels. One of the hardest parts of leadership is holding duality. Seeing clearly what is not working while still protecting what is. Naming loss without losing momentum. I think gratitude helps with that.

As we move into the upcoming year, I am trying to treat gratitude not as an emotion, but as a discipline. A daily practice of directing attention toward what strengthens us rather than what drains us. Toward people who carry others and work that still matters.

The real power of gratitude is its ability to help us stay connected to purpose and each other. It helps to remind us that the future is not built only by fixing what is broken, but by sustaining what is good.

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I can’t believe four years and several additional language versions have passed since the launch of Breathing Lessons. For those of you who don’t know the full story, I have been a volunteer spokesperson for the American Lung Association for a long time. But to be honest, the phones were not ringing off the hook. Then the pandemic hit. Suddenly, lots of people had questions about how their lungs worked, what a ventilator was, and why we needed so many of them. I had the opportunity to appear as a guest on the popular radio show and podcast, Freakonomics (episode is linked if you’re curious!).

A month or so later, Matt Weiland, an editor at WW Norton Publishing reached out. He had listened to the podcast and realized there was very little information on how the lungs worked for the lay public. Many of my clinical trials were shut down, so I spent the summer of 2020 writing. The book was published roughly a year later.

When I held the first copy in my hands, I hoped it might spark a broader conversation about lung health—about how these delicate organs sustain us, protect us, and reflect the world we live in. November, fittingly, is COPD Awareness Month, and November 19th is World COPD Day. So it feels like the right time to take stock.

When I wrote Breathing Lessons, my goal was simple: to help people understand how their lungs work, what happens when they don’t, and why it matters so profoundly that we take care of them. I wanted to demystify a part of the body that most of us never think about until it fails us, and to shine a light on the millions quietly living with breathlessness, those with COPD, asthma, pulmonary fibrosis, and other chronic lung conditions who too often feel invisible. I also wanted to examine why, relative to other diseases, we still understand so little about lung injury and repair. We still have far too few treatments for those living with lung disease.

What’s Changed Since Then

On the upside, in the past three years we’ve seen real momentum in respiratory medicine. We’ve seen new targeted biologic therapies approved for both asthma and COPD, including tezepelumab in asthma as well as dupilumab and mepolizumab in COPD. Also in COPD, the arrival of a novel dual PDE3/4 mechanism inhaler gives pulmonologists another new tool beyond classic bronchodilators and steroids. To be clear, we hadn’t had a new class of drug approved for COPD in the preceding decade. The FDA also just approved a new treatment for idiopathic pulmonary fibrosis, nerandomilast, the first new treatment for this disease in over a decade. This past year, the FDA also approved a targeted therapy for bronchiectasis (an abnormal dilation and thickening of the airways), brensocatib. This is the first approved therapy for this disease. As more patients begin to get access to these medications, I’ve been thrilled to see at least some patients really feel and breathe better. We hadn’t had anything new to offer in such a long time. These medications all represent concrete progress that are making a real difference for patients and offering new hope for many. I believe these advances are just the tip of the iceberg.

What Hasn’t Changed—Yet

For all the scientific progress, we are still neglecting the systems that keep our lungs healthy. The CDC continues to lose people and capacity. Surveillance networks have thinned, labs have closed, and the basic infrastructure that should protect us from the next outbreak is weaker than it was four years ago.

Environmental protections have slipped as well. Cuts to the EPA threaten the clean air standards that once seemed nonnegotiable. Dirtier air means more asthma, more heart disease, more preterm births, and more avoidable deaths. These are direct hits to respiratory health.

The NIH also remains under threat. Annual attempts to cut its budget have created an atmosphere of uncertainty that slows discovery and discourages the next generation of scientists. You cannot sustain a world-class research enterprise while steadily eroding its foundation.

And we have watched trust in vaccines fracture. Falling vaccination rates have already led to the return of illnesses we once controlled. The consequences land on patients, families, and health systems that are already stretched.

All of this reflects a larger truth. We still have not committed to protecting the air we breathe or the institutions that safeguard public health. Until we do, the scientific gains of the past few years will remain vulnerable.

If I Were Writing Breathing Lessons Today

If I were writing Breathing Lessons today, I would still begin with the fundamentals. Those lessons of how are lungs work have not changed. But what has shifted, for me, is my sense of how deeply our lungs are connected to everything around them. In 2020, I wrote about environment, inequality, and preparedness as important forces. Today, I would frame them as inseparable from lung health itself. We can no longer talk about how a lung works without talking about the air that fills it, the climate that shapes that air, the community that surrounds the person who inhales it, and the public systems that support those communities. I would also probably spend more time talking about how trust in institutions affects those who seek care, who gets vaccinated, and who carries the greatest burden of disease. Lung health is shaped by biology, environment, access to care, and the choices we make as individuals and as a society. The point I want readers to carry forward is simple. Protecting lung health is not only about understanding physiology. It requires building environments and systems that give every person a fair chance to breathe.

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I recently sat on a faculty panel at the University of Michigan about enhancing your national reputation. It was meant to be a practical session on professional visibility — how to show up in ways that make others think of you when opportunities arise. In academics, this really matters. Promotions are based on national reputation. But how do you get there, particularly when you’re just starting out? As the panel began to share their experiences, I realized that my own story really wasn’t that unique. There were common elements shared by everyone on the panel. We all had benefitted from strong sponsors and being part of large, collaborative groups where it was easier to get early visibility.

But as the discussion unfolded, what also struck me was that we weren’t really talking about reputation at all. We were talking about networking. And like so many people, I’ve always had a complicated relationship with that word. “Networking” tends to conjure the image of awkward receptions, forced small talk, and nametag juggling. Yet the most successful people I know are also the most connected. They’re not necessarily the most extroverted or strategic. They’re simply intentional about how they show up for others. As as a result, opportunities have a way of finding them.

In the end, effective networking isn’t about collecting contacts. It’s about building relationships, maintaining visibility, and remaining open to the unexpected. Authenticity, presence, and curiosity form the foundation of a network that works and still feels deeply human.

Networking Is Relationship Building

If the word “networking” makes you cringe, it’s probably because it’s been incorrectly framed. Most people think of it as a transactional exercise, exchanging business cards. Who can help me, who should I meet, what can I gain? But genuine connection grows from the opposite instinct: curiosity and generosity. The most effective networkers ask thoughtful questions, remember details, and find small ways to get to know someone better because you are generally curious about their work and them as a person.

When I first was starting out, I would plan my professional conferences not just around sessions I found interesting, but also around where I could meet the people whose work I was most interested in. I would sit at the front, try for quick introductions. But this is just the first step towards meeting people and putting yourself out there. If I could, getting seats at the table where smaller discussions were happening and I could contribute an idea, even if it was just one, was even better. This is where not just mentors, but true sponsors, become invaluable. There’s something about breaking bread—literally sharing a meal—that builds connection in a way nothing else does. Those dinners and casual conversations often lead to opportunities you can’t predict.

When you approach networking as relationship building, everything changes. You stop performing and start listening. You move from selling yourself to learning about others, which people inherently sense. Even if you only get shorter exchanges, these small, authentic interactions can accumulate into a network of trust. You become the person others think of not because you asked for something, but because you invested in them long before you needed anything in return.

Visibility Builds Trust

In a world where much of our professional life happens online, visibility is no longer optional. It’s how people know what you stand for before they ever meet you. Yet visibility often gets mistaken for self-promotion. In reality, true visibility is about clarity, not volume. It’s about showing up consistently and meaningfully so others can understand your values, your expertise, and your point of view.

Being visible means contributing to conversations that matter. It might be writing an article, mentoring a student, or sharing an idea at a meeting. Every time you participate, you’re building familiarity with who you are and what is important to you. That familiarity breeds trust. It makes others more likely to reach out, collaborate, or recommend you, not because of your credentials alone but because they’ve already seen your integrity in action. Over time, consistent visibility turns reputation into recognition. It shortens the distance between introduction and opportunity and helps people see you, not as a stranger, but as someone they already know.

Weak Ties Can Expand Your World

While we often assume that our closest friends and colleagues will open the most doors, decades of research suggest otherwise. Sociologist Mark Granovetter famously described the “strength of weak ties.” This is the idea that our acquaintances, not our inner circle, are most likely to introduce us to new ideas and opportunities. It makes sense: the people we know best tend to know the same things we do. Our weaker connections occupy different networks, exposing us to information and possibilities that wouldn’t otherwise cross our path.

The challenge is that we tend to neglect these outer rings of connection. We forget to stay in touch with a former colleague, or we hesitate to reach out to someone we met once at a conference. So how do you keep weak ties alive? In my experience, it rarely works to force it. People don’t stay connected because of perfect networking systems. Rather, they stay connected because something genuine sparked between them. I’ve found that if you consistently share what you’re thinking about, writing about, or building, people who share your interests will find their way back to you. Some of the most exciting opportunities I’ve had come from weak connections. That said, a little intentionality helps. Sending a quick note when you read an article that reminds you of someone. Commenting thoughtfully on a post. Congratulating them on a milestone. It’s amazing how small gestures can keep a connection warm until it suddenly becomes relevant again.

The Upshot

Networking has earned a bad reputation because we’ve mistaken performance for connection. The best networks aren’t built at cocktail receptions or on LinkedIn. They’re built in the way we show up for others: genuine curiosity, steady visibility, and openness to those we don’t yet know well. So be the person who invests in relationships, not transactions. Be visible enough to be trusted. And remember, sometimes it’s the faintest connections that can change the course of our lives.

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HBO Max’s The Pitt debuted last January. I felt so strongly about its premise that I drafted this piece back in February, then set it aside. Now, it feels like the right time to pull it off the shelf. The show has generated plenty of buzz, not least because its star and creator is Noah Wyle—our beloved Dr. John Carter from the 90s classic ER.

ER premiered in 1994, just before I started medical school. I remember racing home after class on Tuesday nights to watch it with classmates. We’d dissect each episode, critiquing the accuracy, imagining what our own lives might look like someday in medicine, and, in our more romantic moments, picturing ourselves as future heroes.

Fast forward three decades: I graduated, finished residency and fellowship, built a research career, started a family, lived through a pandemic. These days I find myself reckoning with something I never imagined—watching parts of the world I helped build begin to be torn apart. At the start of the year, I thought things might improve. Now, I’m less certain. Colleagues talk of retiring early. As a physician, I understand the temptation. As a mother and a patient, I fear what that means for access to care.

So when The Pitt started making headlines, I was skeptical. My husband, also a physician, nudged me to try it. I watched a few episodes. The premise is a single day in an inner-city ER, with each episode unfolding over the course of one hour. The stories were instantly recognizable: vaccine hesitancy, families struggling at the end of life, clinicians stretched too thin, systems demanding more than we can possibly give.

Yes, the intensity is compressed for television. But the themes mirror the daily reality of nearly every American doctor. At first, I couldn’t understand why the show had captured the nation’s attention. For physicians, these stories are hardly novel—we live them every day. And frankly, it often feels like the public has lost interest in the lives of doctors altogether.

Then I listened to Noah Wyle talk about the show. He wasn’t just speaking to the public. He was speaking to us—the medical community. He named what we’ve been through, what we’ve given. He said he made the show for us. That acknowledgement really hit me. To hear someone say, “I see you, I value you,” was more powerful than I realized. At a time when so many of us feel invisible or even expendable, The Pitt offered a reminder: being witnessed matters.

Because the truth is, we gave. We gave when hospitals overflowed, when PPE was scarce, when patients lined hallways. We gave even as public trust in science eroded. What weighs on us now isn’t the long hours—it’s the devaluing of knowledge, the defunding of research, the dismantling of public health infrastructure.

I am so very grateful every time I or my family need care and there is someone there, willing to provide it. To put on a steady face. To say, “It’s going to be OK.” To keep showing up.

For viewers outside medicine, The Pitt is a gripping drama. For those of us inside it, the show is a mirror. We trained through our twenties, shouldered debt in our thirties, and gave our hearts to strangers in crisis. We never expected applause, but we also didn’t expect this. So for me, the show feels cathartic—not because the plot is groundbreaking, but because someone is naming the weight we carry.

Burnout is the scar. The deeper wound is moral injury, exposed by the pandemic and magnified by today’s climate. These choices—sideling science, eroding trust—will echo back to the bedside.

And yet, there is light. Small repairs happen every day in quiet exam rooms: a hand on a shoulder, a diagnosis caught in time, a trainee who learns to listen, a patient who finally feels heard. These are the reasons we stay. This fight is also playing out on a separate level in Washington this week. The fight to protect healthcare for millions of Americans, now leading to a government shutdown. While a shutdown is not without significant repercussions, so would the loss of health insurance for millions of Americans. As a country, this is not a fight we can afford to lose.

If The Pitt helps the public glimpse this world, perhaps it can spark something more. Seeing can lead to listening. Listening can lead to policies that restore trust in evidence, invest in research, and protect time for patients. I will keep showing up, for as long as I can. And if a television show can help remind the nation why this work matters, that feels like a start.

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At some point, almost everyone has to give a presentation at work. Some more frequently than others. Throughout my career, I’ve been fortunate to have delivered a lot of them. But lest you imagine glamorous speeches in grand auditoriums, let me paint a truer picture. I’m talking about church basements where the ceiling began dripping on the audience midway through my talk, and restaurant dining rooms so cramped I had to hold the door open for waitresses the entire time to avoid being knocked flat. In retrospect, it is amusing, but it was also the best training I could have asked for. I learned how to stay focused despite distractions and how to fight for my audience’s attention.

Now that my son is of the age where he too needs to learn how to give presentations at school, I’ve been reflecting on those experiences. There is so much I wish I could help him understand about how to deliver ideas effectively.

Ideas as Gifts

Over the years I have been lucky to receive media training from some of the best in the industry. I will always be grateful for the lessons I learned from Terri Goudie, a former ABC News journalist and brilliant strategist. One of the most important things she taught me is that every presentation, whether it is a two-minute elevator pitch or a one-hour lecture, follows the same format. At the heart of it is this: a presentation should be thought of as a gift.

A few years ago I sat down with podcaster Sam Hazledine to talk about this if you’re interested in hearing more, but the general idea is that every presentation should be thought of as an incredible opportunity to gift your audience a new idea. This might be a brand-new concept, but more often it is a familiar idea reframed in a new light. In business, that could mean showing colleagues that a budget is not just numbers but a story about priorities and values. In everyday life, it might be helping my son see a school project not as boxes to check but as an opportunity to teach classmates something new. In leadership, it could mean shifting a team’s perspective of failure to an opportunity to embrace a growth mindset. Even in casual conversation, gifting an idea might be as simple as telling a friend that the traffic jam they endured was also a rare chance to slow down and listen to music they love. The content may not be entirely new, but the frame is, and that is what makes it feel like a gift.

The Rule of Threes

Some aspects of presenting feel formulaic, but they endure because they work. You have probably heard the adage: tell people what you are going to tell them, tell them, then tell them what you told them. People can remember three points. That is about the limit of working memory, and it is why everything from jokes to sermons to great speeches so often comes in threes. Summarizing before and after is not repetition. It is building guideposts your audience can follow and remember.

Researchers have long shown that working memory typically holds just three or four chunks at once. Attention is highest at the beginning, drifts in the middle, and spikes again at the end. That is why we instinctively latch on to phrases like “Life, Liberty, and the Pursuit of Happiness,” “Veni, vidi, vici,” or even “Beginning, Middle, End.” Political slogans like Churchill’s “blood, sweat, and tears” and marketing mantras like “Reduce, Reuse, Recycle” endure because they are simple, rhythmic, and complete.

End with a Story

And finally, close with a story. Cognitive science shows our brains are wired to remember narratives more than facts alone. Psychologists call this the narrative bias: people recall up to 22 times more information when it is embedded in a story. Stories fire up multiple parts of the brain, not just language centers but also areas tied to empathy and imagery. They provide context and meaning, and most importantly, they provide closure. Just as a good novel ties up loose threads, a story at the end of a presentation signals to your audience that the journey has come full circle.

One study found that audiences retain about 26 percent more information when it is delivered as a story rather than as bullet points. Ending with a story does not replace your data. It makes sure your data is remembered.

The Upshot

A few weeks ago I was brainstorming with a colleague about developing new presentations, which remain one of the key markers of success in academics. They worried they had nothing unique to offer compared with others in the field who were better known or had longer publication lists. I encouraged them not to compete on the same well-worn topics but to think instead about areas where they had true expertise. These might not be the usual headline subjects, but they were important, relevant, and underrepresented. By taking a different path from everyone else, they could create something authentic and establish a niche where few others were contributing. As we talked, they began to imagine the possibilities, and I found myself equally excited. That, in the end, is what a presentation should do: generate energy and leave people more engaged walking out than when they walked in.

A strong presentation does not overwhelm with information. It offers perspective as a gift, builds around three clear ideas, and closes with a story that lingers. If you can paint a mental picture and give your audience an emotional hook to draw them in, your presentation will not just be effective. It will be memorable.

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Americans with private health insurance have grown accustomed to free preventive care. This means no‑cost mammograms, access to HIV‑prevention medication, cholesterol checks, and dozens of other tests and counseling services. Those benefits stem from the U.S. Preventive Services Task Force, an independent panel of volunteer clinicians and scientists whose recommendations determine which services insurers must cover without copays or deductibles because of provisions in the Affordable Care Act. Bus USPSTF now faces dual threats.

In late July, the Wall Street Journal reported that Health and Human Services Secretary Robert F. Kennedy Jr. plans to dismiss all 16 task‑force members because he considers them too “woke.” While an HHS spokesperson said “no final decision has been made,” more than 100 medical groups, led by the American Medical Association, have urged Kennedy to retain the panel, calling it a “critical, non-partisan” safeguard for evidence‑based preventive care. The controversy comes as the task force’s July meeting—set to address cardiovascular disease prevention and chronic disease in children—was abruptly canceled without explanation, fueling fears of a purge reminiscent of Kennedy’s earlier removal of CDC vaccine advisers. But that’s not all. At the same time, a Texas lawsuit, seeking to gut the preventive‑services mandate, has reached the Supreme Court. Here’s how these threads interweave and why they matter for patients.

Created in the 1980s, the U.S. Preventive Services Task Force took on added significance after the Affordable Care Act required insurers to follow its recommendations. Its unpaid experts sift through medical studies to decide which screenings, medications and counseling services provide a clear net benefit. The panel’s independence has long shielded it from political pressure. Now don’t get me wrong, the system isn’t perfect. The bar of evidence is very high. I’ve had the opportunity to debate with members of the USPSTF formally and have even found myself frustrated with some of their recommendations. But, the fact of the matter is that they are independent, unbiased, and serve an important role.

But the Wall Street Journal report and ensuing backlash mark the most serious challenge yet to that independence. Kennedy’s rumored plan to fire the panel and start over has drawn sharp criticism from the AMA and other groups. In a July 27 letter, the AMA warned that the USPSTF “plays a critical, non-partisan role in guiding physicians’ efforts to prevent disease and improve the health of patients” and urged Kennedy to keep its members and resume regular meetings. For its part, HHS has said only that it is considering how the task force can “better support” the administration’s agenda.

Why This Matters

If Kennedy replaces the panel with ideologues, the scientific rigor behind preventive‑care recommendations could be compromised. Past firings—like the overhaul of the CDC’s vaccine advisory committee—have raised concerns that he may install members who share his views on vaccines and public health. Because insurers must cover services the task force recommends, appointing members who are skeptical of established science could limit coverage for interventions that save lives.

By eliminating financial barriers, this system encourages patients to seek tests and treatments that catch disease early or prevent it altogether. It has also spurred the development of new screening guidelines, such as lung‑cancer screening for current and former smokers. The panel’s independence ensures that those decisions are based on science rather than politics.

The Kennedy v. Braidwood Challenge and Supreme Court Decision

Yet even before the personnel controversy, the USPSTF faced a constitutional challenge. In 2022, Braidwood Management and several individuals sued the federal government, arguing that the ACA’s preventive‑services mandate violates the Constitution and their religious freedoms. They claimed that task‑force members must be appointed by the president and Senate; that Congress improperly delegated legislative power to the task force and similar bodies; and that requiring coverage of HIV prevention drugs (PrEP) violates their religious beliefs.

A district judge partially agreed, striking down the mandate for recommendations issued after March 23, 2010. On June 27, 2025, however, the Supreme Court unanimously held that the task force’s structure is constitutional because the HHS secretary can remove members at will and review their recommendations. The Court reinstated no‑cost coverage but sent the plaintiffs’ nondelegation and religious‑freedom claims back to lower courts. Importantly, the ruling also affirmed that the secretary—now Kennedy—has authority to reshape the task force.

Even with the Supreme Court’s ruling, the mandate’s future remains uncertain. If the plaintiffs ultimately prevail on other claims, insurers could drop coverage for any preventive service recommended or updated after 2010, including statins for heart‑disease prevention, and lung‑cancer screening. Coverage would effectively freeze at 2010 standards.

Meanwhile, Kennedy’s ability to remove and replace task‑force members means that new recommendations could be delayed or altered to reflect political priorities. Many public‑health advocates worry that firing the current panel would undermine trust in preventive guidelines and open the door for ideologically driven decisions. As the AMA pointed out, disrupting the task force’s work risks interrupting the pipeline of evidence‑based advice that physicians rely on.

The Upshot

The Kennedy v. Braidwood decision preserves, for now, the idea that an independent panel can set national standards for preventive medicine. But the controversy surrounding Secretary Kennedy’s reported plans to fire the task‑force members shows how fragile that independence is. If the USPSTF is gutted or stacked with ideologues, patients could see fewer covered screenings and more out‑of‑pocket costs. Even without legislative changes, the secretary’s authority to review recommendations means that future administrations could shape preventive‑care policy from the top.

For clinicians and patients, the lesson is clear: evidence‑based prevention needs vigilant defenders. Staying informed, speaking up for the value of preventive services and protecting the independence of the USPSTF are essential to ensuring that the health system continues to invest in keeping people well.

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I used to love Fridays. Since the beginning of January, I now dread Fridays. They seem to be the day when most executive orders are issued. So, sure enough, overnight, a new executive order was dropped, “Improving Oversight of Federal Grantmaking.” On the surface, it’s framed as a measure to improve oversight. In truth, it hands sweeping new authority to political appointees, allowing them to override expert judgment and reshape the research landscape according to partisan priorities.

The new order directs that all new funding opportunities be reviewed by political appointees or their designees. In reality, stricter oversight over new funding opportunities had already been put into place earlier this year. But this appears to extend that authority now to political appointees, potentially outside the funding agency. Peer review recommendations, once the gold standard in scientific evaluation, are no longer considered binding. Instead, decision-makers are told to use their “independent judgment” to “advance the President’s priorities.” And that’s not just for future grants. Agencies are now instructed to create formal mechanisms to cancel existing awards, even midstream, if the research no longer aligns with current political goals.

Even the most basic functions of grant funding are being politicized. Researchers will now have to submit written justifications each time they request money from a grant that’s already been approved, a process that was previously routine and based on trust. Federal staffers who manage these grants are also newly vulnerable, subject to penalties if they green-light projects that stray from the administration’s agenda.

There also appears to be a renewed push to slash indirect cost support, the unglamorous but essential funding that keeps research institutions running (see full explanation here). These costs cover everything from electricity and lab maintenance to grant administration and safety protocols. The administration claims this money is wasteful, but anyone who’s ever worked in a research lab knows these systems are what make science possible, as they support true costs that can’t be included within the grant itself. The order states that, “All else being equal, preference for discretionary awards should be given to institutions with lower indirect cost rates.”

Supporters of the order say these changes will level the playing field by shifting funds away from elite institutions. But the consequences won’t be limited to Harvard or Stanford. Public universities, mid-sized research centers, and scientists working on everything from asthma to Alzheimer’s will all receive federal grants. They all apply indirect cost rates, which vary significantly and are not significantly a function of how “elite” an institution is.

It has already been a rough year for scientists in the US and this executive order further tears at the foundation of our system. As scientists can no longer trust that a funded project will remain funded, I worry about the future of science and scientists. Long-term studies become riskier, as does betting on science as a career.

The Upshot

If it stands, the damage will be felt for years — not just in labs and academic journals, but in the everyday lives of Americans who rely on science to safeguard their health, their environment, and their future. Even for grants not terminated, undoubtedly this executive order will generate a mountain of new paperwork, requiring agencies to establish new protocols to operate within this framework. This will further slow down grantmaking operations, such that the full budget congress has appropriated to fund science ultimately will never be spent. No matter how this is framed, this executive order is a deliberate disassembly of the guardrails that have protected science from politics.

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I get it. I’ve read those articles too. Take your vacations. But let’s be honest, stepping away from work and email always feels impossible. And if you live in the US, there’s also the guilt factor. It’s just not part of our culture. We have no federal guarantee of paid time off. In contrast, the European Union mandates at least 20 days of paid vacation. France and Germany not only support taking a month off, they culturally enforce it, with stronger labor protections and social contracts that value leisure and family time. US capitalism rewards productivity and presence, with many employees fearing that vacations will make them replaceable or miss opportunities. The advance of digital tools and smartphones has also further blurred boundaries between work and home life, meaning many Americans feel pressured to respond to emails or stay available even during “time off.” In medicine, we also train in a system that rewards self-neglect, then work in one that actually depends on it. But here’s the part that we probably don’t talk about enough. If you really want to think clearly, lead well, or solve problems that don’t have easy answers, you need to stop. Not slow down, stop. And there’s a reason for that that goes far beyond stress relief. So this summer, I bit the bullet. I did something I’ve never done before. I took the two-week vacation. But why is taking time off so important?

The Default Network Mode

Here’s one angle you might not have heard before: you can’t think clearly, creatively, or strategically unless you stop working. I mean really stop. The reason lies deep in the brain, in a network most people have never heard of: the Default Mode Network, or DMN. The DMN is a set of brain regions that activate when you’re not focused on a task. It’s most active when you’re daydreaming, walking without purpose, staring at the clouds, or lying on a beach with no agenda. In other words, it kicks in when your mind finally gets a break from trying to be productive.

But this so-called “default mode” isn’t really as idle as it sounds. It’s doing essential behind-the-scenes work such as stitching together memories, reflecting on experiences, simulating future scenarios, and making creative connections you’d never arrive at through force. This is where clarity comes from. Insight. Breakthrough ideas. The ability to see the big picture.

When we’re constantly “on” doing things like responding to emails, racing between meetings, and checking boxes, our brains live in a very different network, one designed for focus and execution. That system is great for productivity, but it doesn’t allow space for reflection or originality. You can get things done, but you won’t necessarily get the your personal best possible results. You won’t think expansively or reimagine what’s possible. Even Sarah Blakely, the founder of Spanx, describes getting in her car and driving around during the pandemic, even when she was not actually going in to the office. She simply needed to give herself some downtime to let her brain think more creatively, which she was missing because she wasn’t driving in to the office!

Vacations, especially those long enough to detach from routine, allow the DMN to come online. And that’s where the real value lies. It’s not just about recharging. It’s about giving your brain the room to do its best thinking—the kind that happens only when you're not trying so hard to think. So if you’re still feeling guilty about taking time off, consider this: the very part of your brain responsible for long-term strategy, creativity, and meaning requires you to unplug. Time off can be where your best work begins.

What Does The Research Really Say?

When it comes to research about vacations more specifically, one meta-analysis of multiple studies published in the Journal of Applied Psychology found that employees who fully disengaged during time off came back more focused and less emotionally exhausted. Another, in Harvard Business Review, showed that regular vacation-takers were not only more productive but also more likely to get promoted. They also reported vacations resulted in higher levels of happiness and energy, particularly if you 1) plan a month in advance and prepare coworkers for your time away; 2) the farther from home the better; 3) met with local knowledgeable guides or hosts; and 4) set travel details before going. In other words, a “smart” vacation.

According to other studies, the "sweet spot" for vacation benefits tends to be around seven to ten days, with well‑being and recovery notably peaking around day eight. A 2012 study in the Journal of Happiness Studies found that travelers' well-being increased steadily and reached a peak on vacation day eight before gradually declining. A German longitudinal study (274 white‑collar workers), demonstrated that while self‑reported creativity showed no immediate post‑trip boost, it did increase significantly two weeks after returning, especially when vacations involved mastery (learning something new while on vacation) and emotional detachment from work. Researchers concluded that detachment is a necessary precondition, while mastery of a new skill leads to higher impact. On the health front, regular one-week vacations over several years have also been associated with a lower cardiovascular risk and a longer lifespan. Taken together, the evidence suggests that vacations of about one full week (7–10 days) not only offer immediate mood and health benefits but also lead to later cognitive gains, especially in creativity, that unfold in the weeks after your return.

The Upshot

So what happened during my vacation experiment this summer? In medicine, we’ve long equated self-sacrifice with professionalism, as if exhaustion were a badge of honor. But I swallowed my pride, set the out-of-office reply, and stepped away, sending a signal that it’s okay for others to do the same. What surprised me is that catching up after two weeks away wasn’t any harder than after one. The world kept turning. The inbox calmed down. It turns out I’m not indispensable after all.

Was I more creative when I came back? Maybe. What I do know is that I returned with a sense of clarity, finally ready to tackle the projects I’d been avoiding—the ones gathering dust at the bottom of my list. And yes, the guilt still lingered. But would I do it again? Without hesitation.

The older I get, the more I realize that taking time off to explore the world with the people I love is not a detour from my work. It’s what gives the work meaning. These are the moments that anchor me. So take the break. Plan for it. Protect it. The inbox will recover. The time you invest in yourself, family, or friends, you’ll never get back.

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Earlier this year, the White House released its FY 2026 Budget Brief. What hasn’t been making headlines lately but should be is the staggering proposed cut to NIH’s discretionary funding. The agency’s budget authority would drop from roughly $44.5 billion in FY 2025 to $27.5 billion in FY 2026. That’s nearly a $17 billion reduction—or about 40% less money for the largest public funder of biomedical research in the world. The administration has framed this shift as a recalibration toward “essential research at a more practical cost,” along with a push for “gold standard science” and “radical transparency.” But no matter how you spin it, this would be the steepest cut in NIH history.

Yes, this is a budget discussion. But where we choose to spend our money also reflects our values as a nation. It’s about what kind of country we want to be. Do we still believe in investing in discovery? When we put a man on the moon in 1969, we still did. We wanted to lead the world in innovation. We wanted to develop the treatments and cures of tomorrow. And we have. Mortality from heart disease has plummeted over the past 50 years. Life expectancy from many cancers has doubled or even tripled. Are we ready to walk away from all of that?

To put the proposed NIH cuts into context, I’ve included a figure adapted from congress.gov, showing both actual and inflation-adjusted NIH funding over time. You’ll notice something important: while the nominal budget has steadily grown since the 1990s, the inflation-adjusted budget has stayed relatively flat. In other words, even without a cut, the purchasing power of NIH dollars hasn’t kept pace with the cost of doing science.

The standard “R01” award has also been capped at $500,000 per year for more than two decades, despite sharp increases in labor, supplies, and infrastructure costs. That means labs today are doing more with less, stretching resources thinner and thinner.

To understand why these cuts are so alarming, it helps to know just how difficult it already is to secure NIH funding—even before Trump-era proposals entered the conversation. According to NIH’s own data, only about 20% of new R01 applications get funded. Renewals fare a bit better, with a success rate around 40%. At first glance, those numbers might not sound catastrophic. But when you look under the hood, the reality is far more precarious.

Most academic researchers are expected to fund at least 60% of their salary through external grants, and some need as much as 100%. A standard R01 grant typically covers no more than 30-35% of a researcher’s effort, so staying afloat often requires holding two active grants at once. And with only a 1 in 5 chance of success, that means writing and submitting three or more full R01s each year, or one for every NIH cycle.

And that’s assuming you already have the preliminary data. Preparing a single competitive R01, even with existing results in hand, often takes 80 to 150 hours or more. This time comes on top of running a lab, mentoring trainees, teaching, and publishing.

Now imagine what happens if the success rate drops to 12%—which is not a hypothetical, but the likely outcome of a 40% budget cut. At that rate, a researcher would theoretically need to submit five full R01s per year just to maintain their lab. That’s not only unrealistic, it’s impossible. There simply aren’t enough hours in the day, or people on staff, to sustain that kind of grant churn.

Make no mistake, we will lose people. Talented scientists will leave the system, not because they lack good ideas or rigorous data, but because the system will no longer be able to support them. And once that expertise is gone, it won’t be easy to get back.

Indirect Cost Cuts

Another major change buried in the President’s FY 2026 Budget Brief is the proposal to continue capping indirect cost (IDC) rates at 15% for NIH grants. If you’re not steeped in research infrastructure, this might sound like a technical detail. But for anyone working in an academic medical center, this is a red alert. Indirect costs are what keep the lights on, literally. These funds cover the facilities where research happens (labs, offices), the IT and utility systems that support them, and the administrative infrastructure needed to manage grants, ensure regulatory compliance, and oversee safety protocols. These are real and unavoidable costs, but they aren’t allowable as direct charges on most NIH grants. Without a mechanism to recover them, institutions are left footing the bill.

That’s why the proposal to cap IDCs at 15% has been so contentious. Most research institutions currently receive rates closer to 50–60%, based on negotiated agreements with the federal government. A hard cap would mean institutions lose money on every grant they accept. Over time, this would decimate the academic research enterprise.

In the meantime, a coalition of ten organizations—known as the Joint Associations Group, representing research universities, academic health centers, and other stakeholders—has put forward a counterproposal. Their plan would give institutions the option to either include a portion of these costs within the total project budget or receive a fixed percentage of the overall award to cover infrastructure. Sen. Susan Collins (R-Maine) has voiced early support. This is more than an accounting issue. It’s a fight over whether the federal government is willing to pay for the full cost of the science it claims to support. You can read more here.

Overall Restructuring

In a separate FY 2026 Budget Brief for HHS, a comprehensive reorganization aimed has also been proposed. For NIH specifically, the budget calls for a leaner organizational structure that focuses on “gold standard science” and “radical transparency,” while investing in security infrastructure. The impact of this approach can be seen in this proposed reorganization. How much of the existing structure and staff from the current institutes would be retained is unclear. Concerns from investigators in the various arenas center around whether this will translate to less focus on specific diseases (and ultimately the patients they represent).

This is what has researchers worried. Disease-focused institutes such as the National Heart, Lung, and Blood Institute and the National Institute of Mental Health play a vital role in setting priorities, supporting investigator communities, and sustaining long-term commitments to patient populations. If those structures are flattened or absorbed into larger administrative units, will rare diseases, for instance, get left behind? Will community engagement and patient advocacy have a seat at the table?

Right now, we don’t have clear answers. What we do know is that restructuring on this scale will likely create disruption before efficiency, and in science, lost momentum is hard to regain.

Switch to a Multiyear Funding Model

Also tucked into President Trump’s FY 2026 budget is a proposal to shift up to half of all NIH research grants to a multi-year funding model—meaning investigators would receive the full amount of a multi-year award up front, rather than in annual installments. While this approach offers stability and reduces red tape, when bundled with a proposed 40% cut to NIH’s overall budget, this could even more dramatically shrink the agency’s capacity to fund new science.

Under the current system, most of NIH’s budget is already committed to prior multi-year grants. Only about a quarter, the so-called “churn,” is available each year for new awards. Fully funding more grants up front without a transitional cash infusion would drain that pool even faster. STAT news reported that according to the administration’s own projections, total research grants would fall from 42,143 in 2024 to just 27,477 in 2026, while new awards would drop by more than half, from 10,086 to 4,312.

Critics warn this combination amounts to a backdoor cut. “If you keep the budget flat and move a significant portion of the portfolio from annual dollars to front-loading, it’s a 30–50% de facto cut,” said Adrienne Hallett, former NIH legislative director. While the White House frames the change as a move toward efficiency and rigor, it’s hard to square that with such a sharp contraction in how many projects can be funded. In practice, this shift could stabilize funding for a few while at the same time collapse funding for the many.

The Upshot

This isn’t just rebudgeting. This is a redefinition of what the NIH is for and who it serves. A 40% reduction in NIH’s budget, paired with multi-year grant payouts and a cap on indirect costs, doesn’t just shrink the number of projects. It shrinks the pipeline of scientists, the scope of ideas, and the possibility of breakthroughs that change lives. It puts fewer diseases in the spotlight. It leaves more patients waiting.

I also think about what this means for us as a nation: a step away from the kind of ambition that has long defined American science. For decades, NIH has been more than a funding agency. It has been a symbol of our belief that knowledge saves lives and that discovery is worth investing in.

When we put a man on the moon in 1969, it wasn’t because it was cost-effective. It was because we wanted to lead. It was about national purpose, and the belief that progress, not just profit, was a public good. NIH has always been part of that same story. So the question now is not just whether we can afford these cuts. The question is whether we still believe in that story. If we walk away from NIH, we’re not just losing infrastructure or grants. We’re walking away from patients, global leadership, and the economic engine that medical innovation has long provided. I’ll be honest, I don’t understand when we stopped caring. I along with many other scientists still deeply believe in this mission. But this I do know. If we don’t speak up now, we may not get the chance to rebuild what we have lost.

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I’ll admit, I’m not usually a first adopter. I’m usually a second-wave kind of gal. But I’m also not one to be left behind. I also multitask like my life depends on it. Because it does. So as the capability of AI tools has been increasing asymptotically this past year, I decided to spend some time over the Christmas break to take some courses and begin familiarizing myself with what’s out there. But in my quest to learn more, I thought, why not bring everyone I work with along with me on this AI journey. As a leader, I want my team to be equipped with the best tools to do the most creative work in the most productive way possible. So I called on Ann Arbor native and AI expert, Matt Stockton, founder of PragmaNexus, to lead an AI retreat for our faculty. We learned so much, that I asked Matt if I could share some of the tips we learned with all of you.

If you're anything like me, you've probably experimented with AI tools like ChatGPT or Claude. Perhaps you've asked for help drafting emails or summarizing research, and found the results intriguing but inconsistent. Perhaps the biggest take away for me is that the key to unlocking AI's potential is shifting from casual experimentation to purposeful adoption. So in that vein, here are five concrete ways AI can meaningfully enhance your productivity, distilled directly from practical insights Matt provided.

Treat AI Like Your Smartest (But Slightly Inexperienced) Research Assistant

Getting the most out of platforms like ChatGPT, Claude and Gemini means first thinking of AI not as an all-knowing oracle, but more like a highly capable graduate student who has read extensively but still needs clear, explicit instructions. When developing prompts, provide context, define your audience, set constraints (such as format and length), and offer examples. Doing so transforms vague results into focused, actionable content. One of the things we learned is that platforms like GPT generate most of their content from a “next-word prediction” algorithm, which in the past has led to a lot of highly annoying “hallucinations.” These are reasonable sounding but completely wrong bits information that can show up in responses. Fortunately, hallucinations have become less common as the models have improved, but they haven’t disappeared entirely. It’s important to understand that most of these platforms respond based on training data and predictive patterns, rather than live information. However, it can use web search when explicitly told to or when it recognizes that the question requires current or obscure information, which helps prevent against hallucinations. You can prompt this behavior by saying something like “please verify information with a web search and provide links.” It is important to specify web search when verifiability matters. Asking for live links helps you verify the accuracy of information yourself.

Use AI to Generate Structured Outputs

Avoid vague prompts like "summarize this paper." Instead, ask AI explicitly for structured outputs: tables comparing key studies, bullet-point summaries for meetings, or clearly formatted outlines for grant proposals. This small adjustment saves significant editing time and makes AI-generated content far more immediately useful. Tools like ChatGPT Projects enable you to maintain context and organize materials across sessions. You can ask for ranked information and hyperlinks to sources. For example, when analyzing research articles, request AI to generate a table listing each study's methodology, key results, sample size, and clinical significance. For meetings, you might ask AI to create a ranked list of priority action items with clearly defined deadlines and responsible parties. This structured approach significantly enhances clarity, speeds up decision-making, and ensures immediate applicability of generated insights.

Leverage AI’s Strength in Iterative Refinement

AI excels at revision. One helpful tip is to start a task by telling the platform what the task is and ask it to ask you questions about what information it needs to better accomplish your task. Once you have a rough draft, you can further refine with requests like "make this introduction more concise" or "shift the tone to professional yet approachable." You can also upload a sample of your past writing and ask the AI to match your tone and language. This is particularly helpful if you're trying to maintain consistency across a public-facing communication, such as newsletters, blog posts, or professional memos. I’ve even asked AI to mimic the rhythm and vocabulary of my own book chapters when drafting early versions of presentations—this works surprisingly well and can cut editing time in half. Once you’ve gotten a decent draft, ask the AI tool: “What would make this even better?” or “What would a professional editor do to improve this?” Often, the AI will offer insights you hadn’t thought of—like reorganizing sections, adding transitions, or eliminating fluff. Then, ask: “Revise this using your own suggestions.” It’s a quick way to elevate your output from solid to standout.

Use Cases and Specialized Tools You Should Know

While ChatGPT is a powerful generalist, there are other AI tools that can make specific tasks faster, easier, and more insightful. Here are some real-world use cases that go beyond casual experimentation and show how AI can truly improve your professional productivity. This list is tailored for academics, but still has some ideas for everyone.

• Real time trouble shooting: Have a math problem you want to solve? Your computer giving you error messages? Try taking a photo of the problem and directly uploading it into your favorite platform and prompt the platform with your problem. I’ve used this to get step-by-step solutions for my son’s math problems as well as troubleshoot error messages on my MacBook.

• Generating Custom Images: Need a conceptual diagram for a talk? Use AI image generators like DALL·E (in ChatGPT) for custom visuals. These tools can save hours otherwise spent digging through stock photo libraries. These tools have gotten significantly better in the past several months, and in particular their ability to incorporate text within the images to even generate full graphics for pamphlets or posters.

• Writing Letters of Recommendation or Other Repetitive Writing that Follows a Format: This is one of the most tedious but high-stakes writing tasks we do. AI can help by drafting a professional, thoughtful letter based on a CV or set of bullet points you provide. I’ve used ChatGPT Projects to store templates and previous letters, so all I have to do is customize the voice and details for future letters. This is a big time saver.

• Creating Presentations and Slide Decks: Prompt ChatGPT (or Claude) to generate a PowerPoint outline from a paper or idea. You can upload source documents to jump start the process. You can even ask it to format the content into specific slide types—like "Problem," "Solution," "Data," and "Call to Action." Then, just copy and paste into your slide software.

• Create Unique Visual and Audio Content Utilizing NotebookLM: If you're a visual learner or simply trying to distill a dense set of documents, Google’s NotebookLM can generate mind maps, FAQs, and structured outlines based on your uploaded content. This is particularly helpful for planning lectures, writing manuscripts, or even preparing for patient education talks. For fun, also check out the NotebookLM audio overview feature which converts your uploaded content (PDFs, slides, documents, etc.) into a podcast-style audio summary featuring two different AI voices that discuss key points conversationally. We publish weekly internal “podcasts” for our team.

• Deep Research with Search-Grounded Tools: For academics, tools like Consensus, ScholarAI, Elicit, and OpenEvidence are designed to surface peer-reviewed information directly from PubMed and other academic sources. Unlike ChatGPT, these tools are search-grounded and often include citations with links to original studies. Elicit excels at helping you identify and extract data points across multiple papers (e.g., sample size, intervention type), while OpenEvidence is especially useful for clinicians looking to make fast, evidence-informed decisions with real-time citations. Consensus and ScholarAI are specialized GPT tools available within ChatGPT. They're especially helpful when you're working on a literature review, writing clinical guidelines, or preparing background sections for a grant as they both access PubMed. Overall, these tools are in a different league when it comes to sourcing and providing citations. They’re purpose-built for surfacing peer-reviewed content, extracting structured data, and qualifying the strength of evidence — whereas ChatGPT’s general responses are often less consistent and don’t reliably provide transparent citations.

Leveling Up

The best way to learn how AI can help you is to simply start playing with it and create a culture of sharing use cases and best practices with people in your same field. The tools you are using today will likely be different even three to six months from now, so we need to embrace a continuous learning mindset. Matt provided some great resources for learning more:

• 3Blue1Brown: Large Language Models Explained (video)

  A visually intuitive explanation of how LLMs function, great for understanding the basics of next-token prediction.

• Andrej Karpathy: How I Use LLMs (video)

  A practical walkthrough on using LLMs for tasks like summarizing PDFs, writing code and enhancing productivity.

• ChatGPT Prompt Engineering Course (Andrew Ng & Isa Fulford)

  A 90-minute course on practical techniques for improving AI outputs.

• Ben’s Bites Catalog

  A curated collection of tutorials for applying AI tools.

• AI Twitter List

  Researchers, engineers, and thinkers discussing the newest in AI in real time.

• Ethan Mollick’s Blog - One Useful Thing

  Insightful writing on how AI is reshaping work, education and creativity.

The Upshot

If AI still feels like a novelty, it might be time to rethink your approach. These tools aren’t just for researchers or coders. They’re for anyone who juggles too much and needs a smarter way to work. Whether you're planning a vacation, redecorating a room, writing a speech, organizing your week, or summarizing dense material, AI can make tasks faster, clearer, and often more effective.

The real breakthrough happens when you shift from one-off tasks to integrated workflows: saving reusable prompts, organizing projects with memory, and letting tools support you like an extra brain. AI won't replace your judgment, but it will save you time. So don’t wait for the next big leap in AI. Start small, stay curious, and get comfortable experimenting. The future of productivity isn’t about doing more, it’s about spending your energy where it matters most.

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The amount of upheaval across public health, medicine, and scientific research since the start of this year has been overwhelming. Announcements have come so quickly that it’s been hard to keep track. But just because the news cycle moves fast doesn’t mean the consequences will be short-lived. In fact, the opposite may be true.

This week, I’m stepping back to look at three stories that reveal a coordinated effort to reshape the institutions we’ve long relied on to protect scientific integrity. Here’s what I’m watching and why it matters.

Vaccine Panel Purge

Health Secretary RFK Jr. fired all 17 members of the CDC’s Advisory Committee on Immunization Practices (ACIP). This group has helped to guide every major vaccine recommendation in the U.S. since the 1960s. He accused them of “malevolent malpractice,” and replaced them with individuals who, by and large, either lack experience in infectious disease or have expressed public skepticism about vaccines altogether.

If you’ve never heard of ACIP, you’re not alone. But their decisions shape everything from childhood immunization schedules to whether your insurance will cover an HPV or shingles vaccine. When you remove this anchor and replace it with ideology, the ripple effects will travel far beyond policy. Parents will start to question routine vaccines. Doctors and health systems face confusion over what will be reimbursed. And diseases we thought were largely controlled, like measles and cervical cancer, will begin coming back.

“GOLD Standard Science” Isn’t About Better Science, It’s About Control

Last month, President Trump issued an executive order titled Restoring Gold Standard Science. On paper, it claims to promote transparency in the scientific evidence used for federal decision-making, emphasizing reproducibility, integrity, and public access to data. It calls for agencies to disclose the underlying analyses behind policies, encourages acceptance of negative results, and warns against conflicts of interest. It mandates that government agencies disclose the data and analyses behind any scientific information used to shape major policies.

If you read only the headlines, this sounds very reasonable and aligns with the values espoused by the majority of the research community.

But as with everything, there is more to the story. This executive order revives the logic behind the now-defunct “Secret Science” rule at the EPA that requires raw data for a study to be considered in policy decisions. It’s a tactic that sounds reasonable until you realize its true impact: excluding vital research, particularly in public health, because it relies on confidential medical or environmental data that cannot legally or ethically be disclosed. Studies on air pollution, toxic exposure, or long-term health risks could be sidelined not because they’re flawed, but because the data they rely on is protected.

Critics across the scientific community have highlighted the dangers of this shift. Brian Nosek, executive director of the Center for Open Science, put it bluntly: “The proposed standards would result in discarding important evidence that should inform decision-making.” In other words, if implemented as written, the order wouldn't improve science. It would render large swaths of it invisible to federal agencies.

And that’s just the beginning. The executive order also dismantles scientific integrity safeguards put in place during the Biden administration. These policies were designed to shield researchers from political interference and allow dissenting voices to be heard. Without those protections, federal scientists could be punished for producing results that are politically inconvenient. Peer-reviewed research could be invalidated not on the basis of methodology, but on ideology.

When the administration talks about “gold-standard science,” what it’s really promoting is a narrower, more controllable version of inquiry that can be shaped to fit a predetermined narrative. But real science doesn’t work that way. We must hold space for debate, disagreement, and revision.

The Attack on Medical Journals Continues

In a recent podcast, RFK Jr. took aim at the world’s leading medical journals—The Lancet, JAMA, and The New England Journal of Medicine—calling them “corrupt” and declaring that NIH scientists may soon be prohibited from publishing in them. Instead, he proposed creating new in-house journals at HHS “unless current journals change radically.”

Admittedly, scientific publishing isn’t perfect. Conflicts of interest exist, and transparency should always be improved. But the solution isn’t to replace journals with government-controlled publications. Peer-reviewed journals are one of the last remaining guardrails for scientific integrity. They provide a forum where research is debated, vetted, and contextualized. Forcing researchers to abandon those outlets doesn’t just isolate American science from the global community. It also undermines the careers of young scientists who rely on reputable publications to build credibility and secure future funding.

The Upshot

Taken together, these changes reflect a seismic shift in how scientific decisions are being made, who is allowed to make them, and what kinds of evidence will be considered legitimate.

Advisory committees, peer review, and independent journals have long served as safeguards for scientific rigor and public trust. These mechanisms guide decisions on everything from routine vaccinations to drug approvals and clinical guidelines. Weakening them does not just affect researchers. It affects every patient, clinician, and policymaker who depends on reliable evidence.

What makes this moment so challenging is not just the volume of change, but the way it is unfolding. Executive orders, policy shifts, and advisory panel shakeups are arriving all at once. The language used is often technical or vague, making both the intent and the consequences difficult to understand.

But I want to be clear. These changes matter. They may not dominate the news, and they may involve committees and processes that most people have never heard of. But they will shape the kind of science we support, the kind of medicine we practice, and the kind of public health system we leave behind. This is not a time to disengage. This is a time to pay closer attention.

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