With Dolly Parton’s passing on August 25th at age 80, America lost one of its greatest lights. In an age when celebrity and wealth status often evokes controversy and resentment, Dolly stood out for all the right reasons. As an American cultural treasure who was known for her crossover musical talent and creativity, Dolly’s most meaningful legacy may be that of a humanitarian who loved and demonstrated empathy for all people.

In seeing social media tributes to Dolly over the past couple of days, I have observed that so many different social, ethnic, and affinity groups, counted her among their own:

• Country and popular music fans (of course!)

• Women and advocates for female empowerment

• LGBTQ rights supporters

• Black, Jewish, and other minority communities and their allies

• Advocates for science and conservation

• Southerners of all political stripes

Among Dolly’s greatest social contributions of the last decade of her life was her choosing to donate $1 million to help Moderna advance its life-saving Covid-19 mRNA vaccine. She also advocated forcefully at the Academy of Country Music Awards for Ukraine in the aftermath of Russia launching its full-scale imperial war against its neighbor.

In true American style, Dolly Parton was more than an entertainer with integrity. She also utilized her fame and resources to build an entrepreneurial legacy for the ages. For Dolly, the practice of capitalism was about creating ideas that brought happiness to people and expanded economic opportunity. She was as savvy about building brands as she was about creating music. Among her most notable business achievements:

• Established Owepar Music and insisted on retaining her publishing rights. She famously turned down Elvis Presley’s manager, Colonel Tom Parker, when he demanded 50% of the publishing rights to record “I Will Always Love You,” a decision that preserved a catalog now valued over $120 million.

• In 1986, she acquired a 50% stake in the Silver Dollar City theme park in Pigeon Forge, Tennessee, rebranding it as Dollywood. The flagship park evolved into a major hospitality destination, expanding to include Splash Country waterpark, DreamMore Resort, and HeartSong Lodge.

• Co-founded with manager Sandy Gallin, her production company Sandollar Productions, which generated significant Hollywood success, producing hit films and TV series including Father of the Bride and Buffy the Vampire Slayer.

• She built an extensive consumer product licensing footprint through strategic partnerships, launching lines such as Doggy Parton (pet products), Duncan Hines baking mixes, signature fragrances, and home goods.

Dolly was also an impact-oriented investor in new enterprises. In addition to the aforementioned contribution to Moderna’s vaccine research, conducted in partnership with Vanderbilt University, she took a strong interest over many years in supporting her home region of East Tennessee. A strong believer in economic development around the Nashville area, Ms. Parton prioritized business contracts for local partners, particularly in the travel and hospitality sectors, which created and sustained thousands of local jobs.

Through all of her entrepreneurial, philanthropic, and actions in support of uplifting people, Dolly Parton remained a humble servant. She reportedly refused to accept a Presidential Medal of Freedom as she rejected the notion of her acceptance being perceived as an endorsement of any particular political persuasion. Throughout her life, from her musical graces to her various business and philanthropic initiatives, Dolly demonstrated the idea that one can leave the world a better place by simply being a good person who cares about others. Most importantly, she showed that in contrast to some notable figures in today’s world, individual success does not need to come into conflict with the pursuit of the greater good. Shouldn’t that be something we all can aspire to emulate?

The good thing about science is that it’s true whether or not you believe in it.

- Dr. Neil deGrasse Tyson

If you have been following recent proceedings on Capitol Hill, you were treated to yet another round of exhausting political theater: Republican Senate committee members grilling Dr. Anthony Fauci. Rather than a genuine inquiry into pandemic preparedness, the hearings were an attempt to re-litigate the impossible decisions made during the darkest days of the Covid era. Politicians with zero epidemiological training eagerly cast blame on Fauci, prioritizing partisan soundbites over any acknowledgment of his decades of earnest public service. Here is a serious, nonpartisan professional who has dedicated his life to the interest of global health and science, surviving multiple administrations across both parties and leading the charge against HIV/AIDS, Ebola, and Zika, only to be reduced to a political punching bag by those looking to score cheap points with their base. See Dr. Fauci’s memoir On Call: A Doctor’s Journey in Public Service to get a clear understanding of the man and his thinking.

This vilification of public health officials does not exist in a vacuum; it provides oxygen to incredibly dangerous fringe movements. Take the deadly effects of Health and Human Services Secretary Robert F. Kennedy Jr.’s relentless vaccine conspiracies. For years, RFK Jr. has peddled unfounded claims linking vaccines to a host of ailments, operating under the guise of “health freedom.” The results of this rhetoric are not abstract. They are measurable and tragic, as discussed in my previous blog, Conspiracy Theories: From Healthy Skepticism to Deadly Consequences. We are now seeing a completely avoidable surge in measles cases, a disease that was once effectively eradicated in this country, leading to entirely preventable deaths. When conspiracies replace clinical data, the most vulnerable among us pay the ultimate price.

This medical skepticism is further amplified by a new class of untrained social media influencers and media personalities who have appointed themselves as rogue public health experts. Figures ranging from podcaster Joe Rogan to comedian Bill Maher frequently cast doubt on established medical consensus, despite lacking medical degrees or evidently much basic scientific literacy. Under the shield of “just asking questions” or promoting “alternative wellness,” they broadcast vaccine skepticism to millions of listeners. They substitute rigorous peer-reviewed science with gut feelings and anecdotal pseudo-science, creating an environment where a comedian’s hunch is treated with the same weight as a virologist’s clinical trial. There is no “both sides” to this debate. There is evidence and there is conjecture.

Sidebar: The popular myth that MMR vaccines cause autism all stems from one published article in the journal “Lancet” by Dr. Andrew Wakefield in 1998 that was so thoroughly debunked that he had his medical license permanently revoked. The United Kingdom’s General Medical Council disciplinary panel found Wakefield guilty of dishonesty and “serious professional misconduct.”

The supreme irony of this widespread medical skepticism is that it arrives precisely at a moment when science is delivering unprecedented miracles. The rapid development of mRNA vaccines was not a rushed, suspicious experiment, but the culmination of decades of agonizingly hard, underfunded scientific labor. Beyond pulling the world out of a once-in-a-century pandemic through the acceleration of herd immunity, the mRNA platform now offers legitimate, tangible hope for treating myriad other conditions, including personalized vaccines for cancer. We are standing on the precipice of a golden age of medicine. Yet a vocal minority, fostered by ignorance and dogma, is dragging us back to an age where the only hope we had for surviving diseases was our own individual immune systems. This was a time when the average human did not live to what we now consider to be merely “middle age.”

Science is the fundamental bedrock of modern human flourishing. It has doubled our life expectancy, eradicated ancient plagues, and drastically reduced infant mortality. It is the engine that enables space travel, powers the global air transportation network we trust with our lives every day, and engineered the miraculous, hyper-connected cell phones in our pockets. The modern skeptics use the very fruits of scientific labor, broadcasting their anti-science rhetoric on satellites and silicon chips, to undermine the institutions that made their comfortable lives possible.

Of course, the anti-science crusade isn’t just led by laymen; it is occasionally amplified and given oxygen by quack doctors and rogue scientists who are either trying to make a name for themselves or have a massive political axe to grind. Consider Senator Rand Paul, an ophthalmologist by training, who has developed a deeply unhealthy, almost pathological obsession with attacking Anthony Fauci. When individuals with letters after their names abandon their scientific objectivity to cater to a political demographic, they provide a dangerous veneer of credibility to outright misinformation. They betray their oaths and their training for the sake of the spotlight.

Perhaps the most baffling contradiction in this entire ecosystem is Elon Musk. Here is the ultimate tech guru: a man whose entire fortune and legacy are built on the hard laws of physics, advanced engineering, and cutting-edge material science. Yet, Musk actively supports and platforms an administration and political movement that routinely disavows science in critical areas like medicine and climate protection. Musk has advocated and led the charge through his catastrophic DOGE of the gutting of critical medical research funding, while also turning his back on the green movement that led to the popular adoption of electric vehicles and the rise of Tesla. The cognitive dissonance required to build reusable orbital rockets and mainstream EVs, while simultaneously aligning with forces that treat climate change as a hoax and public health as a tyranny, is staggering.

Despite all of this, I remain fundamentally optimistic about our technological future. My hope is that the rampant social media conspiracies and algorithm-driven misinformation that have poisoned our current discourse will eventually be outweighed by the next iteration of technology: Artificial Intelligence. As Large Language Models become faster, smarter, and more deeply integrated into our daily lives, they have the potential to serve as objective arbiters of truth. By instantly providing verified facts, synthesizing complex medical data, and neutrally disproving dangerous conspiracies, AI can become the ultimate counterweight to the pernicious ignorance of the modern internet. If we build these models right, they will help us navigate back to a society that values objective truths and the undeniable miracles of science.

Vida Patil is quickly becoming one of the leading voices in Silicon Valley through her Ctrl Alt Podcast. Vida’s keen curiosity about emerging technologies, startup founders, and the investors who back them, is setting the standard for those who want to be in the know!

It was therefore a real privilege to be asked to join Vida for a face-to-face discussion on my most recent visit to the Alumni Ventures (AV) Menlo Park office. Here I share some of my latest reflections and takeaways regarding the state of VC, the strategy at the AV Seed Fund, thoughts on AI, how founders should approach and pitch investors, tips for aspiring VCs, investing for impact, and much more.

Please tune in to watch/listen here!

While I had the chance to attend a couple of professional soccer/football matches when I lived in Spain, I am not much of a fan and don’t follow the sport very closely. That said, it’s pretty hard to avoid World Cup Fever when it lands right on your doorstep. With Boston (or technically, Foxborough) being one of the North American host cities for 2026, it’s been pretty hard to avoid. My first thought on the topic: while I might enjoy watching a live match, I was not going to pay the insanely corrupt FIFA organization exorbitant money for a ticket.

The second time I gave the World Cup any thought was more upbeat, however. When Scotland’s “Tartan Army” invaded Boston a few weeks back for their first two group matches, I started seeing fans all over the city and immediately drew a strong positive vibe from them. Before hardly any time had passed, it seemed like all of Boston was picking up that same vibe. In no time, my social media was flooded with videos of the Scottish fans jubilantly enjoying their New England experience (and drinking Boston’s pubs dry). By the same token, locals had really taken to this huge, happy, kilt-wearing, bagpipe-playing crew of fans who’d made their way across the pond to support their team.

Having “liked” various social meda posts celebrating the newfound lovefest between Scottish citizens and Boston residents, YouTube’s algorithms then started offering me video after video of foreigners who had come to the US, often for the first time, and were full of “positive” shock and awe at American culture, food, and way of life. This all got me reflecting. I am one of a small percentage of Americans who have spent a significant part of his life living abroad. While I have lived in two American cities in my life (Boston and Phoenix), I have also resided in four European cities (chronologically: Madrid, London, Amsterdam, and Barcelona). I have also traveled to varying degrees in over 140 countries on six continents. While this does not make me an authority on anything, this experience has lent some perspective on cross-border cultural norms and values, particularly contrasting life in the US with life in parts of both southern and northern Europe.

It has therefore been quite entertaining to me to watch clips of foreign visitors to the US, particularly Europeans, as they visited the US for possibly the first time and being amazed at certain aspects of US life (see example clips here, here, and here). Ranch dressing obsessions aside, in some of these videos, the visitors have even expressed a strong and legitimate desire to move to the US after experiencing at least a taste of what it has to offer. My feed has also found videos of expats who have already moved to the US and now sing their adopted homeland’s praises, with a common thread of “it’s nothing like what the foreign media portrays.”

It is certainly true that America’s problems can be easily identified as they tend to get amplified in the foreign press. We absolutely have an issue with gun violence and mass shootings, to start. We also have food diets that can be bewildering (both positively and negatively) for their taste and portions, often forsaking the chemically-infused highly processed nature of much of our typical meal consumptions. There are a number of viral videos from the World Cup that show the visitor’s amazement at the size and low cost of their fast food meal and quite notably the unlimited free refills provided on their favorite high fructose corn syrup-based carbonated beverages (hey, it’s all fun and games until someone overeats their way to Type 2 diabetes…).

Visitors have commented about American customer service (impressive to some, but somewhat superficial to others). Some videos show visitor shock at the liberal American use of air conditioning. While air conditioning is certainly nice on a hot day, some American businesses and public spaces frequently take this to an extreme. This is one of my all-time pet peeves, as elaborated in my grumpy summer travel blog last year, “Packing a Winter Coast for the Beach… and other Stupid Travel Experiences.”

All of these “feel good” videos seem to have proliferated in popularity with Americans who naturally take a measure of pride in visitors appreciating our cities, our food, and our culture. For those of the “right wing” persuasion, it looks like some sort of validation of “American exceptionalism” and that we truly live in the “greatest country on earth.” For those who are more politically neutral or agnostic, these videos are a pick-me-up and a reminder that we can enjoy and be thankful for what we have. Americans with political persuasions that would be commonly identified as “left wing” feel some relief that in spite of the US seemingly relinquishing its moral leadership and soft power in the world, it is still ok to be proud of our country and to respect our nation’s traditions, as imperfect as they may be.

Having lived across borders, I have identified some things where I feel in general the US gets it right, while there are other aspects of life where I feel Europe (very broadly speaking of course) has a more advanced approach. For entrepreneurs and innovators, it’s hard to argue that you can do much better than establishing yourself stateside. If you are concerned, however, about social safety nets, the US clearly comes up short compared with other advanced nations. All of this in a way can be traced back to America’s roots… i.e. “who would leave everything behind to take the boat to the new world?” Of course, it was those who either wanted to, or were forced to make a new life based to a large extent, for better or worse, on rugged individualism.

The “answer” in my mind lies somewhere in the middle. The closest I see to a happy medium in between the worst of the extremes, is largely found in northern Europe. In countries such as the Nordics, it is possible to be both a thriving capitalist entrepreneur who can become wealthy and successful, while also paying enough taxes to ensure that the collective population, regardless of socio-economic status, has access to life’s basic necessities of quality healthcare, housing, nourishment, and education.

There will forever be people who feel like the best place for them, based on their preferred lifestyle and values, is not the country where through virtue of the birth lottery, they happen to have been born and raised. People have immigrated since time immemorial to other countries in search of a life that is better suited to them. For some Europeans, the American “land of opportunity” and economic freedoms will provide that answer. For many Americans, moving abroad to a country with less violence and with more demonstrable social empathy for the downtrodden and less fortunate will be more of an appeal.

While I am no advocate for completely open borders, I do believe “the state” (as in “all” nations) must continue to allow mobility and reasonable immigration. This opens the opportunity for people to pursue their dreams and the lifestyle that best suits them. The value that immigrants bring to the US is enormous, both economically and socially. It is no wonder that when someone makes the life changing decision to move to another country, it is done out of a burning desire to find one’s happy place. That kind of motivation brings out the best in people and keeps them happy and productive.

The ultimate lesson from the fan and local interactions at this year’s World Cup is that we can see clearly with our own eyes how people of different backgrounds live and it’s possible for strangers to feel welcome and even embraced in a new land. There is no “one size fits all” country or city, but there is rather a wide variety of systems and cultures across the world that should provide nearly all people with an environment where they will most feel at home.

My Alumni Ventures Seed Fund colleague Glenn Borok recently took a deep dive into one of the most discussed topics among founders and investors: Is AI truly eating SaaS (software-as-a-service) or does the future hold room for each or even a hybrid model?

For most of the last two decades, B2B SaaS was one of the most reliable business models in technology.

You sold a seat. You renewed the seat. You expanded the account. You raised price modestly every year. If you had strong retention, low churn, and credible net revenue expansion, the market rewarded you with premium multiples. Public investors loved the predictability. Private investors loved the repeatability. Founders loved the playbook. And over time, an entire generation of enterprise software companies was built around a simple assumption: great software meant predictable revenue per user.

That assumption is now under pressure.

Not because software is going away. It is not, but the unit of value is changing. The old model sold access to tools and the new model increasingly sells completed work.

That distinction sounds subtle, but it isn’t. It is the difference between paying for a CRM seat and paying for qualified pipeline created. Between paying for a support platform and paying for resolved tickets. Between paying for an analytics dashboard and paying for the answer. Between buying software that helps a human do work and buying an AI system that performs part of the work directly.

That is the real reason the market keeps asking whether B2B SaaS is dead.

My answer as an investor is no. But the version of SaaS that minted Salesforce, Workday, ServiceNow, Atlassian, and dozens of other category-defining companies is being rewritten in real time. Capital is reallocating. Pricing models are changing. Distribution is shifting. Buyers are rethinking what they are willing to pay for. And a new generation of AI-native companies is scaling faster than anything the software category has produced before.

Investors who understand what is actually changing and what is not will be positioned for the most interesting decade in enterprise software since the original cloud transition.

The headline is simple: SaaS is not dying. The middle is getting squeezed.

What the data is telling us

The numbers from the past 18 months read less like a normal cycle and more like a regime change.

On the funding side, AI has become the center of gravity for venture capital. AI captured roughly half of all global venture funding in 2025 and around 80% of it in Q1 2026, driven by mega-financings for OpenAI, Anthropic, and xAI (Crunchbase News, 2026). Agentic AI, the category most directly competitive with traditional seat-based SaaS, raised $6.42 billion in 2025, the largest year ever for autonomous software (AgentMarketCap, 2026). Gartner now projects worldwide AI spending will reach $2.5 trillion in 2026 (Gartner, 2026), and IDC expects agentic AI to capture more than a quarter of global IT spend, roughly $1.3 trillion, by 2029 (IDC, 2025).

Those are not normal adoption curves. They are reallocation curves. The public markets are sending the same message from the other direction. The median enterprise-value-to-next-twelve-months-revenue multiple for cloud software fell to 3.6x in early 2026, the lowest level in a decade and down from a 2021 peak above 18x. For the first time in history, software’s forward P/E dropped below the S&P 500, falling from 84x at the 2020–2022 high to roughly 23x by March 2026 (Jamin Ball, Clouded Judgement, 2026). The early-2026 software selloff, what Marc Benioff dryly called “not my first SaaSpocalypse,” wiped out roughly $285 billion of software-stock value in a matter of weeks (Salesforce Ben, 2026).

That is not just a valuation reset. It is the market asking a more fundamental question: if AI can perform work that software previously only helped coordinate, what should software companies be worth?

Then there are the AI-native growth curves. They are almost absurd by historical SaaS standards. Cursor went from $100M ARR in January 2025 to $2B in February 2026 (TheNextWeb, 2026). Anthropic grew enterprise revenue 80x in 15 months to a $30B run-rate by April 2026 (VentureBeat, 2026). Sierra reached $100M ARR in under two years from founding (TechCrunch, 2025). Glean doubled from $100M to $200M ARR in nine months (Fortune, 2025). Harvey reached $190M ARR by January 2026 and raised at an $11B valuation in March (Harvey, 2026). ElevenLabs crossed $500M ARR in early 2026 (CNBC, 2026).

In the prior SaaS era, getting to $100 million ARR in five to seven years was elite. Now we are seeing AI-native companies hit that milestone in two years, sometimes less, and continue compounding at a pace that breaks most historical venture benchmarks.

Some of this is hype. Some of it is pull-forward. Some of it will disappoint. But dismissing the entire pattern as a bubble is lazy. The more useful interpretation is that enterprise buyers are not merely buying new software. They are buying a new labor architecture.

That is a much larger market.

Why the question is being asked now

The reason the “Is SaaS dead?” question has become unavoidable is that some of the smartest operators in the industry have started saying the quiet part out loud.

Satya Nadella said in late 2024 that “the notion that business applications exist” may collapse in the agent era (Windows Central, 2024). His point was not that databases disappear. His point was that many business applications are essentially CRUD (create, read, update, delete) databases wrapped in workflow logic. If the logic moves to agents, the application layer changes. The agent becomes the interface. The system of record becomes infrastructure. The old app becomes less central.

Bret Taylor, who built Sierra after running Salesforce, has made a similar argument from a different angle: the atomic unit of AI is the agent, and the vast majority of digital interactions will eventually happen through agents (Stratechery, 2025).

Martin Casado at a16z has said that venture capital itself is being legitimately disrupted as a discipline. Benedict Evans has gone even further in his read on the Series A market, arguing that it has become virtually impossible to raise a Series A for a traditional SaaS company without an AI-native thesis (Business Insider, 2025).

When the CEO of Microsoft, the founder of Sierra, a top-tier venture investor, and one of the sharpest technology analysts in the world are all describing the same shift, the right question is not whether change is coming.

The right question is what survives it.

A framework: what gets eaten, what survives, what gets bigger

Strip away the noise and three patterns explain most of what is happening in enterprise software right now. Some categories get eaten. Some survive. Some get bigger.

The mistake is treating all SaaS as one thing. It never was. “B2B SaaS” includes lightweight horizontal productivity tools, regulated systems of record, vertical operating systems, workflow automation, data infrastructure, developer tools, security platforms, finance systems, and industry-specific applications. AI will not affect all of those categories the same way.

The right analysis is category by category, workflow by workflow, and pricing model by pricing model.

What gets eaten

The most vulnerable software is horizontal, undifferentiated, seat-based tooling whose value was always something like: we put a better UI on a database and made a human workflow easier to manage.

That was enough in the cloud era. It is not enough in the agent era.

The classic example is customer support. For years, support software sold seats to agents and workflows to managers. The more humans in the loop, the more software you could sell. AI flips that logic. Intercom now sells Fin at $0.99 per resolved outcome, with average resolution rates above 67%. Sierra prices around $1.50 per resolution and only charges when its agent solves the issue end-to-end.

That is a different economic proposition. The buyer is not paying for access. The buyer is paying for work completed.

Once that happens, every horizontal SaaS company priced like a labor tax has a problem. If I can pay per resolution, why should I pay per support seat? If I can pay per qualified lead, why should I pay per sales-development seat? If I can pay per document reviewed, why should I pay for a research seat? If I can pay per workflow completed, why should I pay for a human-facing dashboard that merely coordinates the workflow?

This does not mean all seats disappear. But it does mean the seat is no longer the default unit of value.

The pricing data already shows the shift. Seat-based pricing dropped from 21% to 15% of B2B software companies in just twelve months, while hybrid models surged from 27% to 41% (Bain, 2025). Gartner expects more than 40% of enterprise SaaS spend to move off pure seat-based pricing by 2030.

That is the leading indicator. Pricing changes before company categories change. When buyers stop wanting to pay for seats, the market is telling us what it values instead.

It values outcomes.

This is why the undifferentiated middle of SaaS is so exposed. If a product is horizontal, lightly integrated, weakly differentiated, and primarily sold on seat count, AI compresses it from both sides. Foundation models commoditize the intelligence layer. Agents absorb the workflow layer. Incumbents bundle similar functionality into broader platforms. And buyers start asking why they are paying for another login.

That is a bad place to be.

What survives

The second category is software that survives and in many cases becomes more valuable.

Workflow-deep, vertical, regulated, system-of-record software still has real moats. In some categories, those moats are strengthening.

There are a few reasons.

First, compliance matters. HIPAA, Basel III, FedRAMP, FINRA, SOC 2, state-level privacy regimes, procurement rules, auditability, legal accountability — these are not small obstacles. The closer software sits to regulated decisions, financial workflows, legal liability, or operational risk, the harder it is to replace with a probabilistic agent.

Second, systems of record are sticky for a reason. They hold canonical data. They connect to other systems. They encode permissions. They create audit trails. They become part of how an organization operates. An AI agent may become the interface, but the underlying system of record still matters. In fact, it may matter more, because agents are only as useful as the data, permissions, and workflow context they can access.

Third, proprietary data becomes more valuable when models commoditize. If everyone has access to similar foundation models, differentiation moves to data, workflow context, integrations, and trust. A vertical software company with years of proprietary operational data in construction, healthcare, logistics, insurance, payments, or legal workflows has an asset that a generic horizontal AI wrapper does not.

This is why the “AI replaces SaaS” narrative is too crude. In many enterprise contexts, AI does not replace the system of record. It layers on top of it. The agent becomes the interaction layer. The workflow may become more automated. The human interface may change dramatically. But the data model, permission structure, compliance layer, and audit trail remain essential.

That is the durable middle of the software stack.

Not all vertical software wins, of course. Bad vertical software will still get punished. Thin vertical SaaS with weak data, shallow workflows, and limited customer love is vulnerable. But deeply embedded vertical operating systems are in a much better position than generic horizontal tools.

What gets bigger

The third category is the one many people are underestimating: incumbents with distribution and data can get bigger.

The lazy version of the AI disruption story says incumbents lose and startups win. Sometimes that happens. But in enterprise software, distribution matters enormously. Existing customer relationships matter. Installed bases matter. Data gravity matters. Procurement trust matters. Security approvals matter. Integration surfaces matter.

Salesforce’s Agentforce hit $800M ARR, up 169% YoY, with 29,000 deals closed in a single quarter and 60%+ of bookings coming from existing customers (Salesforce IR, 2026). ServiceNow’s Now Assist crossed $600M ACV and is on a $750M run-rate entering 2026, with management raising the full-year AI projection to ~$1.5B (ServiceNow IR, 2026). Microsoft Copilot is now a $14B+ annualized business with M365 Copilot at 15M paid seats, up 160% YoY (Microsoft IR, 2026). Adobe’s AI-influenced ARR exceeds $5B and Firefly is used by 75% of the Fortune 500 (Futurum, 2025).

These are not defensive numbers. They are offensive numbers.

The reason is straightforward. Large software incumbents sit inside existing enterprise workflows. They have distribution. They have procurement access. They have trust. They have data. They can bundle AI into existing contracts, upsell existing customers, and convert distribution into agentic revenue.

That does not mean every incumbent wins. Many will ship mediocre copilots, overcharge for them, and eventually face churn. But the best incumbents are not standing still. They are using AI to deepen their relevance, expand ACV, and defend the system-of-record layer.

The result is not a clean startup-versus-incumbent story. It is a barbell.

On one end, AI-native companies attack specific workflows with dramatically better products and outcome-based economics. On the other end, scaled incumbents use distribution and data to absorb AI demand across massive installed bases. The compressed zone is the undifferentiated middle: generic software without startup speed or incumbent distribution.

That is where capital is leaving fastest.

What we are actually investing in

As an investor with the Alumni Ventures Seed Fund, we are building our AI portfolio around this exact thesis.

The new winners in enterprise software look less like traditional horizontal seat-based SaaS and more like agentic platforms, vertical operating systems, and infrastructure companies powering both.

A few examples from our Alumni Ventures portfolio illustrate the pattern.

Agentic platforms replacing seats

Tabs is automating contract-to-cash for B2B revenue operations — the AR, billing, and collections workflows historically handled by a patchwork of point tools and human finance-ops teams. This is exactly the kind of back-office function where AI can move software from “helps humans manage work” to “performs meaningful portions of the work.”

Wispr AI is rebuilding the input layer of productivity software around voice and intent. That may sound narrow at first, but the input layer is one of the most important interfaces in computing. If humans interact with software less through clicking and typing and more through speech, intent, and context, then the old UI model becomes less central.

These are not AI features bolted onto SaaS. They are products designed under the assumption that agents, not seats, become the unit of value.

That matters. In the last era, founders often started with a workflow and asked, “How do we sell this as software?” In this era, the best founders start with a job to be done and ask, “How much of this work can the system complete?”

That is a different company-building motion.

Vertical AI in regulated and legacy industries

Patlytics is applying AI to patent and IP intelligence, a market historically dominated by clunky, expensive legal-research software. This is a strong example of where vertical context matters. Legal workflows are not just generic document workflows. They require domain knowledge, source reliability, auditability, and trust.

Trunk Tools is bringing intelligent document and execution workflows to construction, a $13 trillion industry where much of the operational layer still runs through spreadsheets, PDFs, email, and tribal knowledge. Construction is not an easy market, which is exactly why the right vertical AI company can build a durable position. The workflows are messy. The data is fragmented. The stakes are high. Generic tools rarely go deep enough.

KarmaCheck is reshaping background checks and credentialing. Hayden AI is replacing legacy municipal enforcement software with autonomous vision. These are not generic AI wrappers. They are vertical systems built around data, workflow, compliance, and real-world operational constraints.

That is the key. Vertical context plus AI is harder to compete with than horizontal AI alone. The data, integrations, customer trust, regulatory posture, and workflow depth are co-located. That creates defensibility.

AI infrastructure: the picks and shovels

The application layer gets the headlines, but infrastructure is where some of the most durable value may accrue.

Cohere builds enterprise LLMs with private, secure deployment — exactly the configuration regulated buyers need. Not every enterprise wants to send sensitive data to a general-purpose consumer AI model. Many need private deployment, security controls, and enterprise-grade reliability.

Groq’s LPU architecture delivers AI inference at a different cost curve than incumbent GPU clouds and now serves more than 650,000 API users. Inference cost is one of the central bottlenecks in AI adoption. If agents are going to run continuously across enterprise workflows, cost and latency matter enormously.

Lambda’s GPU cloud has become a multibillion-dollar partner to Microsoft and is widely expected to IPO. Together AI is building the open-source AI cloud — an AWS-like layer for models that enterprises increasingly want to run on their own terms.

These companies matter because the AI application boom requires a new infrastructure stack. Compute, inference, model hosting, data preparation, orchestration, observability, security, and deployment are all being rebuilt. The companies that power that layer can capture value regardless of which specific applications win.

In other words, when the software stack shifts, the picks and shovels matter.

The data and knowledge layer

AI is only as good as the context it can access.

That makes the data and knowledge layer one of the most important parts of the enterprise AI stack.

Unstructured is becoming a default data-prep and ETL layer for enterprise RAG pipelines. This is not glamorous work, but it is essential. Enterprises have mountains of unstructured data sitting in PDFs, emails, documents, tickets, transcripts, contracts, manuals, and internal knowledge bases. Turning that into usable AI context is a massive problem.

Mercor went from roughly $1 million to $500 million of annualized run-rate in 17 months by supplying expert human data to frontier AI labs. That growth says something important: even in a world of increasingly powerful models, high-quality human expertise remains scarce and valuable.

You.com is building enterprise AI search and reasoning agents at a moment when internal search is being reimagined wholesale. Traditional enterprise search was about finding documents. AI-native search is about synthesizing answers, reasoning across sources, and taking action.

This layer will be critical because enterprises do not merely need models. They need models connected to their own knowledge, permissions, data, and workflows.

AI-native creative and content tooling

Opus Clip is another useful example. Its generative-video editing tools are used to produce hundreds of millions of clips a year, eating directly into traditional creator SaaS workflows.

This is a pattern we should expect to see across creative software. The old product helped a human edit. The new product performs a meaningful part of the editing. That changes who can create, how fast they can create, and what they are willing to pay for.

Again, the question is not whether there is still software. Of course there is. The question is whether the software is selling access to tools or selling creative output.

The latter is a bigger market.

B2B software retooled, not replaced

Not every strong company needs to be “AI-native” from day one. Some of the most interesting opportunities are companies with strong existing positions that can use AI to deepen their value.

Enable’s rebate-management platform is launching an AI-native layer on top of category-leading distribution. Tilled is enabling vertical SaaS companies to embed payments — increasingly the economic moat that lets vertical software survive an AI margin squeeze. Cents is a vertical operating system for laundromats — effectively a Toast for laundry — that turned profitable in 2025 by being indispensable to operators rather than competing on per-seat economics.

These companies show why the “SaaS is dead” narrative misses the point. The durable companies are not necessarily the ones with the loudest AI branding. They are the ones that become indispensable to the workflow, own economic leverage points, and can use AI to increase value per customer.

The best B2B software companies will not be replaced by AI. They will be retooled around it.

Reasons to be cautious

A balanced view requires sitting with the parts of this story that are not yet settled.

The first caution is ROI. McKinsey’s 2025 State of AI survey found that 88% of organizations now use AI in at least one function, but only about 6% are seeing meaningful financial returns. Adoption is broad (McKinsey, 2025). Realized ROI is narrow.

That gap matters.

It tells us that many enterprises are experimenting, piloting, and deploying AI before they have fully redesigned workflows around it. That is normal in a platform shift. But it also means not every AI product with early revenue has durable value. Some tools will be tried and abandoned. Some copilots will not justify their price. Some agentic workflows will break in production. Some customers will discover that automation without process redesign does not deliver the promised economics.

The second caution is quality. Klarna’s high-profile experiment — replacing 700 customer service agents with AI and ending its Salesforce and Workday relationships — partially reversed in 2025 after quality issues. The company rehired human agents to staff a tiered support model.

The lesson is not that AI failed. The lesson is that “rip and replace” is the wrong mental model.

The better model is composition: agents on top of systems of record, humans at the edges, escalation paths where judgment matters, and continuous feedback loops that improve the system over time.

Enterprises do not just need automation. They need reliable automation. That is harder.

The third caution is valuation. Parts of this market are showing real bubble dynamics. Forward-revenue multiples of 50x to 100x for the fastest-growing AI-native companies assume execution paths that not every company will achieve. Some will. Many will not.

Diligence on durability matters more now than it has in any prior software cycle. Retention matters. Gross margin trajectory matters. Defensibility against foundation model improvements matters. Distribution matters. Data access matters. Workflow depth matters. The ability to move from pilot to production matters. The ability to price on outcomes without destroying margins matters.

In a market this hot, capital will fund many companies that should not exist. That is not a reason to avoid the category. It is a reason to underwrite carefully.

From a venture standpoint, this is exactly the environment where active selection matters. When a category is repricing, dispersion widens. The difference between the winners and the median company becomes enormous. That is when manager skill, access, and stage-appropriate underwriting matter most.

What this means for investors

As an investor with the Alumni Ventures Seed Fund, I’d reduce this transition to three takeaways. First, B2B SaaS is not dying. It is bifurcating.

The horizontal, seat-priced, undifferentiated middle is being compressed. Verticalized, workflow-deep, system-of-record software remains valuable. And the agent-and-infrastructure layer is producing a generation of companies that scale faster than anything the category has historically produced.

The right question is not “Do we still invest in SaaS?” The right question is “Which kind of software company is this?”

Is it a thin workflow tool? Is it a system of record? Is it a vertical operating system? Is it an agentic labor replacement? Is it infrastructure? Does it own unique data? Does it have distribution? Does it produce an outcome buyers can measure? Does AI increase its value or commoditize it?

Those questions matter more than the label.

Second, pricing is the leading indicator.

Watch how a software company sells before you obsess over what it sells. The shift from seat-based pricing to usage, hybrid, agent, and outcome-based models tells you whether a company is positioned for the next decade or fighting the last one.

Seats are not going away entirely. But pure seat-based pricing is becoming harder to defend in categories where AI can complete work directly. The companies that make the transition well will align price with customer value. The ones that do not will face margin pressure, churn, and valuation compression.

By 2030, Gartner expects at least 40% of enterprise SaaS spend to be priced on usage, agent, or outcome models. I would not be surprised if the best AI-native companies get there faster.

Third, distribution and data still matter, sometimes more than ever.

GitHub Copilot’s share of AI coding assistants is not just about model quality. It is also about distribution through GitHub and VS Code. Salesforce’s Agentforce growth is overwhelmingly inside its existing base. Microsoft Copilot benefits from Microsoft’s position inside the enterprise. Adobe Firefly benefits from Adobe’s creative installed base.

The companies most likely to win the long arc of this transition are either AI-native builders with sharp vertical or workflow focus, or incumbents that successfully convert distribution into agentic revenue.

The middle - generic horizontal SaaS without either advantage - is where capital is leaving fastest.

The bottom line

The headlines will keep oscillating between “SaaS is dead” and “SaaS just had its best quarter.” Both can be true at the same time, depending on which version of SaaS we are talking about.

Traditional horizontal seat-based SaaS is under real pressure. Workflow-deep vertical software is still durable. Incumbents with distribution are not dead; the best of them are monetizing AI aggressively. AI-native companies are scaling at unprecedented rates. Infrastructure is being rebuilt. Pricing is moving toward usage and outcomes. Buyers are increasingly asking whether software can do the work, not just help humans manage it.

That is the shift.

The old SaaS playbook was about selling access.

The new enterprise software playbook is about delivering work.

For investors, that means the opportunity is not gone. It is moving. The next decade of value will accrue to companies that rebuild around AI from the ground up, own deep workflow context, capture proprietary data, align pricing with outcomes, and use distribution intelligently.

SaaS is not dead.

But the era of selling another seat to another dashboard and calling it a category may be ending.

The arsenal of enterprise software is being rebuilt. The companies that get rebuilt around AI — not patched with AI — are where the next decade of value is most likely to live.

Glenn and I recently hosted a virtual panel discussion on this topic with several leading VC investors, including:

John Harthorne of Two Lanters Venture Capital

Catherine Ouellet-Dupuis of White Star Capital

Greg Raiz of FoundersEdge

To watch/listen, please check out this link.

I was first introduced to Allison Byers in the fall of 2024 when we came together to host a joint fundraiser between Founders for Kamala and VCs for Kamala in Boston. Since then, I have had the chance to interview Allison about her firm Scroobious and its mission of helping diverse founders raise capital. We have also more recently served together on the Board of the GK Fund, a nonprofit that provides grants to impactful entrepreneurs in underserved Massachusetts communities.

As I have gotten to know Allison, I have marveled at her intellect and clarity of thought around the vexing problem of how to help entrepreneurs raise capital in spite of myriad inherent disadvantages. However, more than identifying and calling out the challenges that founders face, I have been impressed with Allison’s practical guidance and strategies to help founders overcome the odds and succeed in raising capital to start and grow their businesses. With her recently published book, Fundraising for the Rest of Us, Allison has penned the definitive guide for entrepreneurs across the spectrum who seek to raise outside capital for the first time. Delivered with the passion and urgency that can come only from one’s own lived experiences, Allison’s book helps founders navigate that murky, and often biased, minefield that is startup fundraising.

In particular, Allison calls out the pitfalls of “pattern recognition” as a defining characteristic of why many founders simply don’t reach the capital allocators. This should not only come as a wakeup call to investors, but should be a reality check for founders to know what they’re up against. With this knowledge in hand, founders can then take the proactive steps to get in front of the right investors and make their case for funding as effectively as possible.

It is an honor to have Allison share her perspectives and advice in this guest column:

The Pattern Recognition Problem

Venture capital, in its modern form, is a relatively young industry. American Research and Development Corporation (ARDC), founded in 1946, is widely regarded as the first modern VC firm. It invested in companies commercializing technologies developed during and after World War II. The industry’s Silicon Valley-centered norms and fund structures matured later, especially in the 1970s and ‘80s. That’s less than 50 years of institutionalized practice, built almost entirely around a specific type of founder, in a specific geography, building a specific kind of company.

The thesis at the center of it is pattern recognition. Investors look for signals that a founder and a business resemble the ones that worked before. The problem is that “what worked before” is a narrow slice of who actually builds companies. In Q1 2026, all-female founding teams got 0.6% of VC deal value while 78% of first-time financings went to all-male teams. Black founders got just 0.48% of VC funding. The numbers for many other population segments are similarly stark. When you fund people who look like previous successes, you replicate the previous distribution of success, and you miss most of the opportunity.

Women-founded companies deliver 2x revenue per dollar invested (BCG). VC firms with a female partner have 10% more profitable exits (Morgan Stanley). An industry that defines itself by finding undervalued assets is completely missing where the opportunity is most statistically abundant.

I know this not just as a researcher or an observer, but as a founder who lived it. I spent over five years building a medical device company, raising close to $10 million, earning FDA registration, generating paying customers, and publishing peer-reviewed research. By any reasonable measure, we were doing the work. In our final years, I was traveling constantly, pitching investors, and trying to close our round or find a strategic buyer. I developed shingles in my 30s from the sustained stress of it.

We couldn’t close the round. Our board and majority shareholders ultimately authorized an asset sale, meaning the technology survived, but the company itself did not. The all-male team that acquired our assets went on to raise $55 million. That was a gut punch.

I don’t tell this story to generate sympathy. I tell it because it sent me down a path of research that changed how I understood what had happened, and why.

Venture capital isn’t broken, it’s doing what it was built to do: reproduce the outcomes it was trained on. The criteria developed to evaluate founders weren’t designed to be exclusionary, they were designed to reduce risk. But the dataset those criteria are built on is almost entirely homogeneous demographically, so the tools for finding “safe” bets wind up filtering out most of the market. The liberating part is that once you understand this, you start asking a different question: where is the capital that was built with me in mind? That question leads you somewhere much more useful.

The Full Capital Menu

When I started writing Fundraising for the Rest of Us, one of the first things I wanted to do was help founders see that venture capital is a single item on a much longer menu. Here are some other offerings:

Your personal network. You’ll often hear this called the “friends and family round,” but what that really means is angel investors you already know. If you have people in your life with the means and belief to back you early, that capital can be the most aligned you’ll ever raise, because they’re investing in you before there’s much evidence to believe in. The honest caveat, however, is that wealth isn’t distributed evenly across racial, gender, or socioeconomic lines, and startup culture often assumes access to this capital that many founders simply don’t have. If you have it, use it thoughtfully. If you don’t, it’s not a personal failure; it’s a system design flaw.

Angel investors. There are over 24 million accredited investor households in the US alone, and more than 4 million are already writing checks into private companies. Angels are more diverse than the venture world, they move faster, and they often invest based on personal connection to the problem rather than portfolio math. You’re looking for the person whose eyes light up when they hear what you’re building. The one who says, “Oh my goodness, this has to be a thing.” Those are your people.

Grants. Non-dilutive capital is real money that you don’t have to repay and don’t have to trade equity for. Government programs like SBIR and STTR, state-level innovation funds, and mission-aligned foundations are all legitimate capital sources, and founders in life sciences, climate, defense tech, and ag tech often have more grant opportunities than they realize. One filter I still use is to only pursue grant funding for something you’d do anyway, even without the grant. That keeps you focused and prevents you from chasing dollars that pull you off mission.

Revenue-based financing (RBF). RBF allows you to raise capital without giving up equity by agreeing to repay investors through a percentage of future revenue. Unlike a traditional loan, there’s no fixed repayment schedule. Payments adjust based on your actual earnings. For companies with predictable revenue streams, like SaaS or e-commerce, it’s a way to access growth capital while preserving both ownership and control.

Equity crowdfunding. What makes crowdfunding different from traditional fundraising is that anyone can participate, including non-accredited investors. That means your customers, your community, and your supporters can all become owners in your company, not just cheerleaders. Think of it less like pitching and more like launching a marketing campaign. You need to attract a broad audience and build excitement at scale. When it works, the alignment it creates between your investors and your customers is powerful.

Revenue-funded growth. I prefer this term over “bootstrapping” because it reflects what it actually is: a strategic, intentional choice to build by reinvesting what your business earns. You retain full ownership, you’re not beholden to investor timelines, and in today’s market, where investors are paying closer attention to burn rates and paths to profitability, a track record of sustainable, customer-funded growth can actually make you more attractive to the right capital when you’re ready for it.

Strategic partners and corporate investors. Companies with aligned interests like a distribution partner, a supplier, or an enterprise customer often have corporate venture arms or partnership budgets that function like growth capital. These relationships take longer to build, but they can open doors and create ecosystem access that traditional VCs can’t offer.

The Common Thread

None of these paths bypass the work of building relationships, they just redirect where that work happens.

The founder who pursues venture capital for three years without success and then pivots to angel investors and closes a round in six months didn’t suddenly get lucky; they shifted their energy toward people who were already looking to invest in someone like them.

The practical implication is to start before you need money. Give before you ask. Build the relationship with genuine curiosity about what the other person cares about — their goals, their thesis, the problems they’re trying to solve — and let the ask come later, when trust has had time to form. The pitch meeting doesn’t create that trust. It just makes official what the relationship already established.

Capital follows trust. Not the other way around.

Choosing Your Path

The decision about where to raise capital is one of the most consequential strategic decisions a founder makes, and it’s made, far too often, by default.

Founders default to chasing VC because it’s what gets coverage, what accelerators celebrate, and what signals legitimacy in startup culture. But venture capital is a specific financial instrument designed for a specific type of company that can plausibly grow to return 10x or more in a relatively short window, where the business model benefits from aggressive scale. That describes a small fraction of companies, and it may not describe yours.

If you are building a company that can be profitable with lower revenue, that serves a market VC finds “too small,” that requires patient capital, or that is led by a founder who doesn’t fit the historical pattern, the VC path may be a detour. Not a failure. A detour.

There are more capital sources than you’ve probably explored, more investors who want to fund you than have had a chance to meet you, and more paths to building something sustainable and impactful than the dominant narrative allows.

That’s why I wrote the book and that’s the work we’re doing every day at Scroobious: a place where founders and investors can find each other before there’s an urgent need for money so that when the moment comes, the relationship is already there.

The Rest of Us are the market majority. Go raise. Go build. Go take up space.

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Allison Byers is a founder, investor, and capital access advocate working to build a funding system that includes The Rest of Us. She’s the founder of Scroobious, a relationship-first capital access platform, author of the book Fundraising for The Rest of Us, and co-authored California’s landmark Fair Investment Practices by Venture Capital Companies Law. She serves on multiple boards. Previously, she co-founded a medtech company spun out of MIT, raised nearly $10 million, and brought an FDA-registered product to market only to watch the all-male team that acquired it raise $55 million. That experience led her to uncover the systemic barriers facing underestimated founders and dedicate her career to dismantling them.

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More resources and how to buy the book at www.allisonbyers.com.

I have been observing with keen interest the vast appeal and rapid growth of prediction market trading platforms such as Kalshi and Polymarket. These companies offer individuals the opportunity to bet on the outcomes of everything from sports events to political races to when wars will end or what the price of gas will be a week from now. Because of the “wisdom of crowds,” these platforms have done a better job of predicting outcomes of elections, for example, than many professional pollsters with decades of experience. It is worth taking notice of what they are getting right, but also the pitfalls they present for those who use these platforms in the hopes of striking gambling gold.

Betting on sports or trading based on speculation in financial markets is nothing new. What is different here are a) the breadth of what people can actually bet on (e.g. what color dress a certain celebrity might wear to the “Met Gala”), and b) the vast number of people from around the world using these platforms, which help determine the odds by which people place their bets. The betting odds even change in real time during the course of live sporting events, for example, as the game’s score changes and momentum shifts.

I personally make a living investing professionally and I think often about both public markets and “alternative assets” like venture capital. I would say that my investment risk tolerance is considerably higher than the average person and that my portfolio is more highly diversified into “non-standard” assets than most people’s. I have made many “high risk, high reward” angel and VC investments over the years. However, I do not consider myself to be a “gambler.” I can spend a week in Vegas walking through casinos and never have the temptation to place even a single bet.

So why this dichotomy between “high risk investing” and “gambling” when one could argue that the former is essentially a form of the latter?

Here is the difference in my mind: I like to invest in assets where my gain does not necessarily imply that someone else loses. In other words, I do not like to bet when the outcome is “zero sum.” When one person’s gain automatically implies an equal loss to another party, that is when I walk away. A friendly “zero sum” game of poker among friends is one thing, but “zero sum” investing or gambling at a commercial level is another. In these situations, the house always wins. When the “middleman” (whether it’s a casino or a brokerage firm) is the intermediary on such bets, the net return to the gamblers actually becomes less than zero sum. Consider the roulette wheel. Almost all of the potential outcomes are either black or red. However, there are also a couple of potential outcomes that are neither black nor red. In the long run, that is how “the house” always wins.

So why do people bet or “invest” based on “less than zero sum” trading outcomes? I would offer three common reasons:

1. The purpose of the “bet” is to hedge against an opposing outcome. Some airlines, for instance, hedge by buying oil futures contracts that will “gain” when the price of jet fuel goes up. Although airlines don’t want the price of jet fuel to go up, they do this to protect themselves against sudden oil price shocks that could have a detrimental impact on their bottomline. Another very different scenario could be that I make a personal bet as a Boston Red Sox fan that the team will lose the World Series. The thinking is that a financial gain could help soften the psychological blow that I would incur if they do not come away victorious. Just spitballing scenarios (baseball pun intended), but you get the idea…

2. Someone might love the “thrill” of a bet. Contrary to the prior example, they may want to bet on their favorite team winning (or “beating the spread”) or they might bet on the outcome of an election because they have an intuition about the likely result. Or they may simply have fun and get an adrenaline rush from knowing an outcome very quickly (instant gratification). Essentially, it is more of an emotional decision to bet than a logical one.

3. Perhaps the biggest pool of bettors on the prediction market platforms are people who place bets because they genuinely believe that they are “smarter” than more than half of the population who are betting on the same thing. For some select savvy individuals, this may be true. However, this can also be a trap and where things get dangerous for the majority of people who genuinely seek to profit from such bets. With zero sum betting, one is effectively assuming that they know better what the outcome will be than the “wisdom of the crowd.” By definition, on average, “most” people cannot be smarter than “the crowd.”

I would bet dollars to donuts that most Polymarket and Kalshi traders genuinely believe that they are placing smart bets. This is similar to the logic that has sustained much of the mutual fund and asset management industry for decades. The data on stock trading performance tells us that if one wants to be a long-term investor in the public equities market, the best thing to do is invest in ultra low fee (or even “no fee”) stock index mutual funds or similar exchange-traded funds (ETFs) that mimic the performance of broad indices. Nevertheless, to this day, most (though a declining percentage) of global investors still pour their capital into actively managed funds, which not only charge higher fees, but over long periods, invariably underperform their benchmark indices. Contrary to their hopes and feelings, these investors do not actually beat the market.

Not only are the majority of active fund managers not adding value, they actually generate negative value. Yet capital continues to be directed into actively managed funds either because either: a) the investors believe they (or the specific fund managers) are “smarter” than “the crowd,” b) they delegate the management of their funds to a professional money manager who is incentivized to direct that savings into such funds, or c) these investors simply do not have the financial literacy to understand that they are underperforming while having a small percentage of their investment skimmed off the top for purposes that serve no economic value.

There is an even more disturbing possibility for why people trade in zero/negative sum situations. That is information asymmetry. In other words, someone has insider information. Of course, in societies where there is democracy and rule of law, trading based on insider information is generally considered illegal (not to mention immoral) and those found guilty can be subject to severe penalties, including incarceration.

Let’s take the recent case from the news of a US soldier who allegedly placed a substantial bet on the date when the US military would enter Venezuela in order to capture their former president/dictator, Nicolas Maduro. This soldier, who was privy to such plans, is accused of using classified information to knowingly profit from this, which of course came at the expense of the “common” person on the other side of the “zero sum” bet. Trades such as these are evidently becoming increasingly prevalent as it pertains to outcomes from public policy decision marking. Know something from “the inside” about the war in Iran ending soon? Why not bet on the price of oil going down? Your company about to share an upbeat earnings report? Why not bet on stock futures contracts immediately prior to such an announcement? Life would be so sweet if we could all just take advantage of our “soothsaying” abilities!

So insider trading is basically one way to have an upper hand in zero sum markets. If one does not have insider information, then why would one assume that they are any smarter than the next guy or gal? Again, the answer appears to be based on emotion rather than logic. In any given one-off situation, close to 50% of bettors will come out ahead. But for the average person to do this over and over again, unless they truly are “smarter than the average bear,” there is simply no way to consistently repeat this outcome aside from sheer luck (or insider information).

If people want to make emotional rather than logical bets just for fun and kicks, I have no issues with that. If they are hedging and making these decisions for strategic reasons, more power to them. However, if they are trading based on information asymmetry derived from insider information, this is a real problem and if compounded, could lead to the downfall and trustability of the likes of Polymarket and Kalshi. Anything other than that is pure gambling that is guaranteed to result in net losses across the average. Once again, the house “always” wins.

For my money, I will stick to true investing. In venture capital and angel investing, an investment can be risky for sure. However, this type of investing is not zero sum. Gains can and do outweigh losses, thanks to the Power Law effect. Meanwhile, there is societal value from creating companies, building products, driving innovation, employing people, etc. While less risky from an investment standpoint, the same holds true for investing in public stocks, bonds, real estate, small businesses, and all sorts of other assets. True investing, by and large, does good for society while also providing net financial upside for the investor. One company’s success may have little to no negative impact on anybody else. Sure, there is such a thing as “creative destruction,” but this is arguably a net positive at the end of the day.

Folks, it’s a free country. Gamble on Kalshi or Polymarket if you like (and if it’s not based on illegal insider information). However, please do so with the knowledge and humility that you are probably not any smarter than “the crowd” and that there are other ways to earn yield and returns that are both better for you from an ROI perspective and better for the world in the impact that your investment is having.

On March 26th, I had the privilege of interviewing notable journalist Rebecca Fannin (whose reporting has been featured by CNBC, Newsweek, Forbes, and Harvard Business Review, among others) about her new book, The New Tech Titans of China. In front of roughly 100 guests over dumplings at the office of SVB in downtown Boston, I asked Rebecca to unpack for us what we need to know about the state of tech in China and what impact that will have on innovation, geopolitics, and market competition with the US and the West.

Here are some key takeaways from Rebecca’s book and our discussion:

1. As stated at the outset of the book’s introduction: “Once copiers and followers, Chinese tech entrepreneurs are charting their own future today and becoming less dependent on Western technologies.” The major shift in why China is becoming a competitive threat to the West is just this. They have transitioned to a nation that is demonstrating leadership in technology and have come to a position of setting the pace of innovation. Global government and private sector leaders who have not yet woken up to this fact are destined for a rude awakening.

2. A deepening global shift toward autonomy and robotics is being driven by advancements that are originating in China. Everything from robotaxis to cashless payments, renewable energy, and other futuristic forms of transportation and infrastructure have become omnipresent. All of this is happening while much of the advanced world dithers and leaves their populations behind. Case in point: BYD, which is not even available in the US market, has become by far the world leader in electric vehicle deliveries.

3. The Chinese government has become instrumental in promoting technology R&D as well as consumer adoption. As a strategic national priority, government funding of tech enterprises has become so great that venture capital investment has actually diminished and become less significant of a factor in recent years.

4. To that end, with a few exceptions, US VC has all but stopped flowing into China. The confluence of greater restrictions on capital outflows alongside robust protection of Chinese IP has made the environment for foreign direct investment into tech-heavy enterprises a far more daunting proposition.

5. The globally burgeoning reliance on natural resources means that other countries will become increasingly dependent on China and will no longer have the privilege of treating China as an adversary or merely as a supplier of low cost production. Roughly 60-70% of the world’s supply of rare earth minerals are mined and 80-90% are processed in China. This puts the country at a huge advantage when it comes to electronics, defense technology, energy production, medical devices, and many other critical sectors.

6. Biotech is flourishing under the promise of reduced regulatory burden, turning China into an R&D leader for the first time in areas such as medical diagnostics and therapeutic drug development. AI-driven pharmaceutical discovery is a formal priority in China’s Five-Year Plan, and Chinese drug companies have increased their share of global biotech licensing deals from 21% in 2023–2024 to 32% in Q1 2025. In December 2025, the NMPA (China’s equivalent of the US Food & Drug Administration) introduced a new policy to significantly reduce the time between drug approval and market supply, allowing commercial-scale batches of overseas-marketed drugs to be imported and supplied earlier in China. Meanwhile, the rest of the world is struggling to keep pace with the rapid scientific advancements that are being driven by AI.

7. As the US erects more protective barriers on trade and immigration, highly educated scientific and engineering talent from China are staying home or returning home after collecting their Western degrees, allowing China to retain advanced skills and brainpower that otherwise would have been put to use elsewhere.

8. Chinese companies like Tencent, Alibaba, ByteDance (TikTok), BYD, and Huawei will continue to assert their muscle in unprecedented ways and across global markets, in spite of occasional pushback. Other countries will have a choice to either accept their products, isolate themselves, or attempt to fight back through market forces, which will naturally be challenging for nations that are not used to competing through such massive scale industrial policy.

We have entered an era where AI will dictate how we live and work, for better or worse. The impact will be felt in ways that are both promising and concerning. However, it’s a force that cannot be stopped, particularly as each country operates within its own regulatory and R&D silos. Chinese innovation is outpacing competing nations across the innovation economy and as a result, now finds itself in a remarkably advantageous position. Whether other innovation economies of the world are prepared to compete within this reality is a serious open question that global leaders need to be asking themselves.

I am a capitalist and have been ever since I knew what the word meant. I strongly believe that the profit motive creates innovation and leads to the development of products and services that humans need and desire. Chasing wealth may not seem egalitarian on the surface, but it has and will continue to be the impetus for risk taking that solves some of the world’s biggest problems (insert plug for my book Higher Purpose Venture Capital).

Since I was old enough to contemplate the idea of “making lots of money,” my thinking has been: a) Wouldn’t it be great if I could have enough money to have a nice house, take fun vacations, and provide a comfortable life for my family and the highest quality education possible for my kids; and b) For any money I made beyond what is needed to take care of those aspirations, I could give most of it away to the many causes and organizations that I believe in. In other words, become a philanthropist.

It has often been asked at what point does money no longer serve a utilitarian purpose of one individual or family? This is a hard question to answer and one that can be very personal to the individual and circumstances. However, let’s say you desire all of the finest earthly possessions, e.g., a private jet, a yacht, three homes, the most exclusive schools for your kids, luxury cars, elite vacations, luxury furnishings, top restaurants, maids, butlers, tutors, and perhaps a collection or two of fancy antiques, collectibles, or whatever. It can vary widely of course, but it’s hard for me personally to see how anyone could realistically need more than $100 million to have just about everything they could ever conceivably want in life. Or if you really wish to take it to extremes with the collecting of say, museum worthy art or a professional sports team, call it $1 billion.

Forbes estimates that there are 3,428 billionaires in the world and they hold an average net worth of around $5.9 billion. Far be it from me to judge how these billionaires spend their money. Actually, screw that. Let’s judge…

All of the basic niceties of life wrapped up in platinum and diamonds sounds great. You earned it, inherited it, or perhaps even plundered it, so you may as well spend it on what you want. My question is: once you have “everything,” why hoard the billions that remain? To pass it all on to your children… and to what end does that serve, exactly?

Many billionaires (and equivalent in historical dollar terms) have very generously given away much of their wealth to serve social purposes. Consider Jamsetji Tata, founder of India’s Tata Group, widely viewed as the greatest philanthropist in history, who more than a century ago gave the equivalent of over $100 billion away to education, healthcare, and other causes. In the United States, industrialist Andrew Carnegie funded the construction of thousands of public libraries and famously remarked, “The man who dies thus rich dies disgraced.” Perhaps the most awe-inspiring example of Carnegie’s admonition against greed is Chuck Feeney. The godfather of airport duty free shops and founder of The Atlantic Philanthropies, Mr. Feeney, who passed away in 2023, quietly gave away nearly every last penny of his $8 billion fortune while he was still alive. How Mr. Feeney never received a Presidential Medal of Freedom is beyond me. I even wrote a letter to the White House during the Biden administration proposing such a prize, but unsurprisingly, my outreach went unanswered.

Among contemporary billionaire philanthropists, Bill and Melinda Gates stand out for their generosity in working to end disease, malnutrition, and contribute to other areas such as education through an estimated $75 billion that they have committed to the Gates Foundation. Investor extraordinaire Warren Buffett has taken a less active role in directly overseeing personal philanthropic endeavors, but has nevertheless pledged 99% of his wealth to charity.

Most major givers have set up their foundations to survive in perpetuity and generally contribute only a small fraction of their total assets each year (only 5% of foundation assets must be distributed each year, per US tax law). Mackenzie Scott, on the other hand, is taking a different approach. The ex-wife of Amazon founder Jeff Bezos, Ms. Scott, is actively giving away funds through her Yield Giving foundation at a staggering and unprecedented pace that is intended to have an immediate impact. Since 2019, her contributions have already exceeded $26 billion. Without great fanfare, Ms. Scott has spread her giving across more than 2,300 different organizations that serve a vast array of social causes.

While Mackenzie Scott has taken philanthropy to heroic levels, the same unfortunately cannot be said of most of today’s tech oligarchs who built their wealth with great fastidiousness and determination, but seem content on the notion that wealth is intended for accumulation and not for distribution in a way that can meaningfully benefit others who are not so fortunate. It is almost as if they believe that they are in a race to see who can take the biggest sack of cash into the afterlife. Take a few prominent examples:

• Elon Musk - The serial tech showman and disgraced government budget interloper, (see: The Devastating Legacy of DOGE) has given away less than 0.1% of his fortune, which is currently estimated at more than $800 billion, and could very well top $1 trillion after SpaceX goes public later this year. For the record, $1 trillion is more than four times the cumulative salaries of all 3.24 million public school teachers in the United States.

• Peter Thiel - The Paypal Mafia don and J.D. Vance’s puppet master, Thiel is as parsimonious philanthropically as one can get, having given away less than 1% of his estimated $30 billion worth. He has even gone so far as to talk his fellow billionaires out of agreeing to Bill Gates’ Giving Pledge, a non-binding vow to donate half of one’s wealth in their lifetime, because he argued it would be given to “left wing causes.” I suppose helping to prevent poor children in Africa from dying of the measles or malaria is Thiel’s idea of a “left wing cause.”

• Jeff Bezos - While the Amazon founder has given away a few billion to important causes such as education and climate change, as a percentage of his estimated $220 billion-plus wealth, the total is simply miserly compared to his ex-wife Mackenzie Scott’s considerable largesse.

• Mark Zuckerberg - The Facebook/Meta founder and his wife Dr. Priscilla Chan have no doubt done good with giving in education, healthcare, and scientific research through their Chan/Zuckerberg Initiative. Yet, they have contributed only about 3% of their more than $220 billion in wealth thus far, begging the question of what is holding them back from doing even more when the needs are so acute?

• Larry Ellison - Oracle’s co-founder and CEO has given to conservation and medical research, but alas a paltry sum relative to his $190 billion of net worth that has been surging in recent years.

• Sergey Brin and Larry Page - Google/Alphabet’s co-founders have both done some charitable giving in areas like public health and clean energy, but once again, the totals are meager and minimalist (low single digit percentages of their net worth that are each in the hundreds of billions).

So what are we to make of the personal values and philosophy of the tech oligarchs who have over the past couple of decades generated personal wealth that would be enough to feed and clothe the populations of some small countries? I don’t begrudge anyone who has earned great wealth through their ingenuity, if it’s been done legally and ethically. What I simply don’t comprehend is the lack of calling to leave a legacy that transcends the mere accumulation of fortune. At some point, there truly is nothing more that one centi-millionaire, let alone multi-billionaire, can possibly buy that would make their lives any better. Yet, billions of people around the world struggle to keep up. A lack of food, housing, health services, education, training, and other basic necessities of life, impede billions of fellow humans from achieving their potential. Where is the empathy and desire to help fellow members of the human race?

The lessons of Tata, Carnegie, Feeney, Scott, and others, show that generosity can have impact, and the true rewards of accreting incomprehensible fortune ought to come from the satisfaction of helping others and advancing humanity’s promise.

While I am sadly nowhere close to being in the league of the “mega donors,” I try to live my values and support a variety of causes at least in a modest way. Most recently, my wife and I have focused much of our giving on a variety of charities (such as Sunflower of Peace and Children of Heroes) that are supporting the people of her native Ukraine in their existential fight for survival against a barbaric, genocidal invader. Over the years, we have also supported social causes ranging from education and youth services to hospitals, medical research, conservation, and more. I also serve on the Board of the Boston-based nonprofit The GK Fund, which provides grants to entrepreneurs in underserved areas of Massachusetts who seek to have an impact on their communities.

I believe most good hearted humans can find some purpose or organization that’s worth contributing to. Even for those who may have limited means to donate directly can still have an impact. For example, anyone who makes online purchases of goods and services can direct a small portion of these e-commerce transactions to a charity of choice through platforms such as the web browser plug-in Give Freely (see my podcast with founder Stephen Kaufer here). Other notable platforms like Cauze and Givz, both of which are profiled in my book, offer solutions that help to democratize personal and business donations.

Earning immeasurable financial fortune is difficult and unlikely for most people. So for those who have been able to achieve this, I often wonder what exactly they do with such vast wealth. To me, “giving” is the most rewarding part…. My wish is that those who have such means will understand that there are many great challenges in the world that they have a unique ability to help solve, if they can only start to see beyond their own lavishly superfluous material cravings.

Of all of my teachers over the years (at least “teacher” in a formal academic sense), I have stayed closest with Daniel Isenberg. As my professor of international entrepreneurship in business school, a former VC in Israel, an active angel investor, and as a thoughtfully contrarian author and lecturer, we have long had many overlapping personal and professional interests that have kept us tight.

Despite coming from different generations, we have bonded as friends and I consider Dan one of my most trusted mentors and thought partners. On the surface, one might say that I know Dan very well. In reality, I didn’t really get to know what’s deep inside of him until I read his most recent book, rather provocatively titled “This Book is Not for You: My Loss, My Grief, My Healing.”

Dan tragically lost his beloved wife Carla to a rare and aggressive form of cancer back in late 2023. This kind of trauma in one’s life is never welcome, but especially so when a life partner is as young and vibrant as Carla had been. Moreover, in a sad twist of irony, Carla was a brilliant Alzheimer’s and ALS researcher who had dedicated her life’s work to the mission of saving lives.

Dan’s path to coping with Carla’s serious illness and the aftermath of her eventual death was obviously very personal. However, that did not stop him from documenting his experience and internal emotions for all to absorb and contemplate. His book not only serves as a chronicle of a painfully difficult time, but it opened a window into Dan that I had not seen before. This, in turn, opened a path that I could explore within myself.

Adding to Dan’s story was his own recent health incident that could have ended much worse than it did. Allow me this platform to present Dan in his own voice sharing his story. While the video quality linked below is not perfect as this speech was not staged for mass distribution, I encourage you, my dear followers, to listen in. It is hard for me to imagine not finding something in this talk to reflect upon and find some meaning and inspiration.

Dan, my friend, for your “last lecture” (though I certainly hope not)… over to you!

The assassination of President John F. Kennedy on November 22, 1963, represents perhaps the most enduring conspiracy theory in American history, with polls consistently showing that a majority of Americans believe there was a broader conspiracy beyond Lee Harvey Oswald acting alone. The reasons for persistent doubt are multifaceted. The event was traumatic, circumstances contained puzzling elements like Oswald’s own murder two days later, and government agencies were not always forthcoming with information.

It is crucial to acknowledge that questioning authority serves vital democratic functions. History provides numerous examples of actual conspiracies, such as Watergate, the Tuskegee syphilis experiments, tobacco companies hiding health dangers, and even government surveillance programs by both authoritarian and democratic nations worldwide. Healthy skepticism encourages transparency and accountability, creating pressure for institutions to operate more ethically and openly.

There are conspiracy theories that remain in the public discourse today that hold merit and where reasonable alternate theories can be debated and not flat out disproven. Take the 1996 case of the downing of TWA Flight 800, a Boeing 747 bound for Paris that exploded mid-air shortly after takeoff from New York’s JFK killing all 230 individuals onboard. Without going into all of the facts and evidence both for and against the government’s explanation that this was caused by an explosion in the aircraft’s center fuel tank, one shouldn’t dismiss the fact that numerous senior investigators who were directly involved in looking into this tragedy have stated that they believe the more likely cause was a ground-launched missile, a theory that is corroborated by dozens of eyewitnesses who shared similar accounts of seeing a streak of light approach the plane shortly before impact. I do not have a pony in this debate, other than seeking the truth, but I defy anyone to watch the 2013 Lionsgate documentary film about the crash investigation (available for free on YouTube here) and come away secure in the knowledge that the government explanation is incontrovertible.

Now, let’s shift to the darker and uglier side of conspiracy thinking as we are entering an era where this is already having deadly consequences that are rapidly accelerating. Without a doubt, the current anti-vaccination movement represents the most dangerous conspiracy theory of our lifetime. “Anti-vax” conspiracy theories aren’t just “bad information” floating around the internet. They have real world public health consequences. When enough people are persuaded that vaccines are dangerous, unnecessary, or part of a hidden plot, the result is predictable: fewer vaccinations and the return of outbreaks that modern medicine has pushed to the margins. The danger isn’t abstract. It is measurable in hospitalizations and preventable deaths.

Polio is a stark example of what vaccines can accomplish and what we risk forgetting. In the United States, polio infections peaked in the early 1950s, with 21,000 paralytic cases in 1952 alone. After the introduction of effective polio vaccines in 1955, incidence plummeted, and the last U.S. case of wild poliovirus acquired domestically was in 1979. If you have never had to worry about spending your life inside an iron lung, you have Dr. Jonas Salk and his polio vaccine to thank. Sustained high vaccination coverage lasted long enough to stop transmission.

Measles shows the same dynamic. The disease is so contagious that public health authorities commonly cite the need for very high immunity levels to prevent spread. When coverage dips, outbreaks ignite quickly. Globally, the impact of measles vaccination is enormous. A Centers for Disease Control (CDC) analysis estimates measles vaccination prevented around 57 million deaths worldwide from 2000 to 2022. The World Health Organization’s count is similar, while still estimating about 95,000 measles deaths in 2024, mostly among unvaccinated or under-vaccinated young children. Conspiracy theories thrive on anecdotes and insinuations, such as “someone I know got sick after a shot” or “they’re hiding the truth,” but measles punishes lapses at scale. When misinformation lowers uptake even a few percentage points, it can move a community from protected to outbreak-prone. Case in point was the 2019 measles outbreak in American Samoa, which resulted in 5,700 cases and 83 deaths.

When it came to COVID-19, vaccines did not end the pandemic overnight. However, the data show that vaccination dramatically reduced severe disease and death, especially among older adults and other high-risk groups. A study summarized by the Center for Infectious Disease Research and Policy (CIDRAP) estimated that through November 2022, vaccines prevented 18.5 million U.S. hospitalizations and 3.2 million U.S. deaths.

Anti-vaccine conspiracies were dangerous during COVID-19 for two reasons. They reduced uptake, leaving more people exposed to the virus’s worst outcomes. They also turned vaccination into an identity badge. When a decision becomes a marker of belonging to a tribe (“people like us don’t trust vaccines”), evidence tends to bounce off. That social shift matters because infectious disease doesn’t negotiate with beliefs. As the popular astrophysicist Neil deGrasse Tyson once remarked, “The good thing about science is that it’s true whether or not you believe in it.”

The deepest harm of anti-vaccine conspiracy theories may be what they steal from the future. Vaccination is one of the few interventions that can permanently shrink a disease’s footprint, sometimes to the point of elimination (such as smallpox, which was eradicated globally in 1980). Polio’s disappearance from the U.S. after 1979 is a triumph of sustained trust and shared responsibility.

The modern anti-vax movement gained momentum following Andrew Wakefield‘s fraudulent 1998 study linking the Measles/Mumps/Rubella (MMR) vaccine to autism, and though thoroughly debunked, the conspiracy theory proved remarkably resilient, evolving into broader narratives about pharmaceutical companies and medical establishments suppressing “truth” about vaccine dangers. Measles, declared eliminated from the United States in 2000, is seeing a resurgence in communities with low vaccination rates. The skyrocketing numbers are particularly jarring just in recent months, which correlates noticeably with the misinformation being spewed by the leading public health officials of the current administration, notably Health and Human Services (HHS) Secretary Robert F. Kennedy, Jr. See chart below illustrating cumulative measles cases over 2025 vs. previous years.

This tragedy demonstrates the transition from healthy skepticism to dangerous conspiracy belief. While it’s reasonable to want to understand vaccine risks and benefits, the anti-vaccine conspiracy requires believing that hundreds of thousands of medical professionals across the world are complicit in harming children, and it demands accepting that diseases which killed millions throughout history are preferable to prevention.

It is particularly galling that individuals, who are not trained in science or medicine, will entrust their doctors and nurses to fix a broken arm or treat their cancer, but they will disregard their professional expertise when it comes to one of the most well documented preventative measures the world has ever created (a miracle of science, if there ever was one). How easily we forget that before vaccines, nearly one in five children did not make it to their fifth birthday. It seems that conspiratorial social media influencers such as Joe Rogan who are persuasive communicators hold more sway with some people than those who actually did the hard work of graduating from medical school and other highly rigorous healthcare provider training programs.

What makes all of this especially infuriating is that vaccine-preventable diseases don’t only harm the children of conspiracy believers, but also those babies too young to be vaccinated as well as immunocompromised individuals who are legitimately unable to take a vaccine and rely on herd immunity. When vaccination rates drop, the most vulnerable suffer. In today’s climate, with a non-medically trained Secretary of HHS at the helm, we are seeing funding for mRNA vaccine research slashed, even while new studies are showing mRNA’s potential for drastically reducing occurrences of cancer and other fatal diseases.

The challenge facing modern society is nurturing critical thinking and healthy skepticism while building resilience against unfounded conspiracy theories. This requires teaching media literacy, ensuring institutions operate with genuine transparency, and addressing underlying conditions that make conspiracy theories appealing. When conspiracy thinking leads parents to leave children vulnerable to preventable diseases, the abstract question of belief becomes a matter of life and death. As a thinking, intelligent race, humans are obliged to recognize that truth matters, that reality exists independent of our “beliefs” about it, and that our choices have consequences that extend far beyond ourselves.

This creates a fundamental divergence between venture capital and almost every other asset class. Public stocks, real estate, and bonds generally follow a Normal Distribution, or a “Bell Curve.” In those worlds, most assets perform near the average, and the primary goal is often to minimize risk and avoid losing capital.

Venture capital, by contrast, follows a Pareto distribution. In our ecosystem, the “average” outcome is actually a loss, as most startups fail, but the right-tail outlier is theoretically uncapped. While a public equity manager might focus on hedging against volatility to avoid a bad year, we must actively hunt for volatility. Missing the single best-performing company in a vintage, like an early Google or Facebook, is not just a missed opportunity; it is a catastrophic failure of strategy that renders the rest of the portfolio irrelevant.

Despite the high failure rate, the returns in venture capital are compelling because of the mechanics of asymmetric risk. When we invest in a startup, our downside is strictly capped: we can only lose 1x our invested capital. However, our upside is uncapped. We can make 10x, 100x, or even 1,000x our money. This asymmetry is the engine that powers the industry. It allows us to be wrong the majority of the time and still generate superior aggregate returns. We accept that a significant portion of our portfolio may go to zero because the math of a single “home run” is powerful enough to pay for every strikeout and still deliver substantial profit to our Limited Partners.

Historically, venture capital has functioned as a high-beta, cyclical asset class that delivers exceptional returns during technological booms. For instance, the asset class famously outperformed public markets during the “dot com” era, with the Cambridge Associates US Venture Capital Index generating a staggering 32.4% average annual return from 1995 to 2020. While this can be offset by lagging performance during market downturns, it is important to consider the long-term nature of such investments. Liquidity in venture investing can take 5, 10, or even 15 years to manifest. The upside for such patience and willingness to accept reduced liquidity should ultimately come through superior returns. In more recent times, the VC index returned roughly 17.2% annually from 2010 to 2020 compared to the S&P 500’s 13.9% (source here). It should also be noted, however, that these aggregate figures mask a steep power law where the top quartile of funds drives nearly all industry profits, while the median fund frequently fails to justify the illiquidity risk relative to public benchmarks.

At Alumni Ventures (AV), we have crafted a strategy around co-investing alongside the leading VC firms in our industry. Our performance has been benchmarked against nearly all major North American VC firms. In the past two years, both CB Insights and TIME Magazine have independently determined that AV ranks among the “Top 20” firms in VC, among some illustrious company that includes the likes of Kleiner Perkins, Andreessen Horowitz, General Catalyst, and NEA. At the AV Seed Fund, we lean into the Power Law by making a high volume bets (50+ companies per vintage) on “moonshot” style opportunities, where valuations are low and the risk is understood, but knowing that if things turn out well, the possibility of achieving outsized returns is limitless. Among our highest returning seed investments have been Sondermind, which has resulted in a greater than 90x MOIC (multiple on invested capital) while other portfolio companies like TRM Labs and Sleeper have seen a rise of more than 30x.

For an individual investor, venture capital offers a critical role in a well-diversified portfolio by providing a high-beta source of “alpha” that is structurally distinct from public markets. Public companies are generally “efficiently priced,” making it difficult to gain an information advantage. Venture capital captures value during the private, inefficient, and steep-growth phase of a company’s lifecycle, meaning value creation that occurs long before a ticker symbol exists. While illiquid and risky, this asset class provides exposure to innovation and disruption with low correlation to daily stock market fluctuations, offering the only reliable way to capture the exponential growth of the next generation of giants before they become household names.

Alumni Ventures Seed Fund 9 is open to new commitments until December 31st. If you are an accredited investor, you may join our community and gain access to a highly diversified seed-stage venture portfolio, with a minimum investment of $10,000. If you are the type of investor who prefers to pick your deals selectively on an individual basis, you may also join the AV Seed Fund syndicate. Under NDA, investors have the opportunity to review deals where our fund is investing and members may choose to direct capital into only those startups that they find most compelling.

Outperforming stock market indexes is the holy grail for investors, but I have seen first hand how the Power Law works in practice. For my own startup that I co-founded, TravelPerk (now known as Perk), we originally raised our seed round in 2015 on a $2.5 million cap SAFE while the latest round of funding valued the company at $2.7 billion!

While nothing is ever guaranteed and VC implies risk and illiquidity for a period of time, thousands of savvy investors with Alumni Ventures have already helped to secure their long-term financial futures by putting money to work in the most cutting edge, innovative startup teams in the world by taking advantage of The Power Law that fuels the venture capital asset class.

Open AI / ChatGPT 5.1

Yes — we’re absolutely in a speculative phase of the AI cycle, but it’s not a uniform “bubble” so much as a bifurcated market: inflated on the surface, disciplined underneath. Capital is chasing anything with “AI” in the name, valuations are stretched, and many startups are building thin wrappers with no real moat — classic signs of froth. Yet beneath that noise, a quieter layer of enduring value is forming around companies with proprietary data, deep workflow integration, and real distribution advantages. Like every technological inflection, the hype will deflate, but the foundational winners — those compounding genuine intelligence and defensibility — will endure long after the bubble pops.

Anthropic / Claude Sonnet 4.5

The debate over whether we’re in an AI bubble is intensely contested, with compelling evidence on both sides. Major figures like OpenAI CEO Sam Altman and investor Ray Dalio have stated they believe an AI bubble is underway, with comparisons to the dot-com era, and the share of the economy devoted to AI investment is nearly a third greater than internet-related investments during the dot-com bubble, while companies like OpenAI are making trillion-dollar deals despite generating only $13 billion in expected 2025 revenue. However, defenders argue the fundamentals are stronger: today’s largest AI companies trade at about 26 times two-year forward earnings compared to 70 times during the dot-com peak, and unlike the 1990s speculation, today’s AI investments are primarily funded through retained earnings rather than debt, while equity funds show measured inflows rather than speculative frenzy. The reality appears nuanced—while certain segments like quantum computing stocks show extreme valuations that likely constitute individual bubbles, the broader AI sector shows a mix of reasonable and stretched valuations, with the ultimate verdict depending on whether the technology delivers the productivity gains needed to justify current trillion-dollar spending levels.

Google / Gemini 3.0

Whether investors are in the midst of an AI bubble is a subject of intense debate among economists and financial experts, with many believing there is significant “froth” or over-exuberance in the market, though not necessarily a classic bubble poised for an immediate, catastrophic burst like the dot-com era. Proponents of the bubble thesis point to the sky-high valuations of companies, particularly those central to AI infrastructure like chipmakers, where stock prices have often surged ahead of near-term, proven profitability, and they note the concentration of market gains in a small group of “Magnificent Seven” tech giants. However, the counter-argument suggests the situation is different from past bubbles because the underlying AI technology is genuinely transformative with massive, long-term economic potential, and many of the highly valued companies actually possess substantial earnings and cash flows, which was not true of many companies during the 1990s tech bubble. Ultimately, while speculation is rife and some valuations may be unsustainable for smaller or less profitable players, the sheer scale of investment and the revolutionary nature of the technology make it difficult to definitively declare a traditional bubble.

xAI / Grok

As of November 2025, investors appear to be navigating the early stages of an AI bubble, characterized by unprecedented capital inflows—exceeding $1 trillion annually into AI infrastructure, data centers, and startups—driving valuations like Nvidia’s $4.4 trillion market cap and a $19 trillion surge in AI-related stocks since ChatGPT’s launch, far outpacing tangible returns where 95% of enterprises report zero ROI from generative AI despite billions in spending. This frenzy, echoing the dot-com era with circular deals like Nvidia’s $100 billion stake in OpenAI, has fueled extreme multiples (e.g., Palantir at 700x forward earnings) and market concentration, with AI stocks comprising 80% of U.S. equity gains and 30% of the S&P 500, prompting warnings from figures like OpenAI’s Sam Altman, Alphabet’s Sundar Pichai, and Bridgewater’s Ray Dalio about irrational exuberance amid energy constraints, chip shortages, and lagging adoption. Recent volatility, including Nvidia’s post-earnings dip and a 3.6% MSCI AC World sell-off, signals emerging cracks, with 45% of global fund managers fearing economic fallout, though optimists like BlackRock’s Larry Fink argue it’s a justified supercycle for transformative tech, not mania—yet the disconnect between hype-driven prices and fundamentals suggests a correction looms, potentially reshaping portfolios if expectations falter.

Mistral

As of November 2025, many analysts and market observers are debating whether the current surge in AI-related investments constitutes a bubble. While AI technologies continue to advance rapidly—driving significant interest in startups, public companies, and infrastructure—some warn that valuations for AI-focused firms have become disconnected from fundamentals, with high cash burn rates and uncertain paths to profitability. The influx of capital, especially in generative AI, has led to comparisons with the dot-com era, though proponents argue that AI’s transformative potential across industries justifies the investment. Regulatory scrutiny, geopolitical tensions, and the pace of actual AI adoption remain key factors that could either sustain the boom or trigger a correction. The consensus is mixed, with some seeing a bubble in specific sectors, while others believe the long-term value creation will validate current spending.

Conclusion:

I can say from an investor lens with reasonable confidence that some kind of AI bubble is here. It is not that AI doesn’t have the vast potential that is in focus at the moment. However, is there room to create enough value over the next 5-10 years to justify the level of funding and value that is being assessed for AI companies across the board from early startups to Nvidia? I believe that virtually all sector categories will all have key winners that become the platforms and standards. It’s likely that there will not be a need for as many startup ventures to solve each market need as are currently emerging, which will lead to a shakeout and a fair amount of M&A and acqui-hire activity. I will be taking a balanced and diversified approach as I look to which companies are solving challenges with AI with the most advanced products and speed to market. If the bubble does deflate at some point in the next few months, we will begin to see who the real survivors and market leaders will be.