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In An Agentic Era, VC Is Buying A-Player C-Suite Execs At Any Cost — Not ‘Staffing Up’
By Pukar C. Hamal Venture capital has become a mechanism for extracting executives from trillion-dollar companies and paying them whatever it takes to build in an AI-native world. We’re not funding companies anymore — we’re buying access to the few hundred people who’ve built AI systems inside Google, OpenAI and Meta. Safe Superintelligence was founded by Ilya Sutskever (ex-OpenAI chief scientist), Daniel Gross (ex-Apple AI lead), and Daniel Levy (former researcher at OpenAI). The company operates with roughly 20 employees. So far, it’s raised $3 billion at a $32 billion valuation, without a product or any revenue. What they do have is three executives from trillion-dollar companies who understand how to build superintelligence. That alone commands $1 billion in capital per team member. This has become the playbook. Pukar C. Hamal Microsoft agreed to pay Inflection AI $650 million to use its models and hire DeepMind co-founder Mustafa Suleyman as CEO of Microsoft AI, along with most of Inflection’s 70-person team. Meta CEO Mark Zuckerberg reportedly offered Andrew Tulloch up to $1.5 billion over six years. Google struck a $2.4 billion nonexclusive licensing deal with Windsurf and hired its CEO, co-founder and select R&D staff. Meanwhile, OpenAI CEO Sam Altman has publicly stated that Meta offered top OpenAI talent $100 million signing bonuses. The traditional venture formula is inverting. It used to be simple: raise $20 million, spend 95% on growth and headcount, allocate 5% to executive comp. Now the majority of capital flows toward recruiting a handful of executives who understand how to operate in an AI-native environment. But most founders can’t compete in $20 million bidding wars. And so there’s an asymmetric play, and it’s 10x cheaper. Why executive judgment is the new scarce resource In an agentic era, AI systems write code, process data, handle customer service and automate operations. The scarcest resource has become the judgment of executives who know how to orchestrate these systems effectively. Think about what this means in practice. A decade ago, $100 million might have hired 200 engineers. Today, that same capital might fund five FAANG executives at $10 million each, with the remaining $50 million allocated to compute, AI tooling and a skeleton crew of 20 to 30 people overseeing autonomous agents. Executives from frontier AI companies command massive premiums because they possess knowledge that doesn’t exist elsewhere. They navigate what’s possible with current AI capabilities, understand the economics of model training and inference costs, and can anticipate regulatory frameworks before they’re codified. What this means for capital formation This shift creates a new power dynamic. Founders who can attract marquee executives unlock fundraising rounds that would be impossible based on traction or revenue alone. VCs evaluate deals increasingly on “who’s building this” rather than traditional metrics like customer acquisition cost or gross margins. The clearest signal: Voyage AI, with 19 employees, was acquired by MongoDB for $220 million — $11.6 million per employee. In an agentic world, team size has become irrelevant. How to compete with the asymmetric playbook Most founders reading this can’t offer $10 million to $20 million equity packages to marquee executives. But there’s a counterintuitive strategy emerging: Instead of competing directly for executives who’ve built AI systems at frontier labs, target the operators who’ve integrated them at scale inside Fortune 500s. A chief technology officer who deployed LLMs across 50,000 employees at JPMorganChase or Walmart understands enterprise AI adoption patterns that most OpenAI researchers don’t. Here’s the asymmetric approach we’re seeing work: 1. Hire the “translator” executives, not the “builder” executives. A former VP of engineering from Databricks who integrated AI into enterprise workflows is more valuable for a B2B AI startup than a research scientist from DeepMind. They’re 10x cheaper and often more relevant to your actual go-to-market challenges. 2. Offer board seats, not just equity. The most compelling pitch to executives earning $800,000 at FAANG companies isn’t just equity — it’s offering: (a) a board seat they’d never get at a big company; (b) meaningful ownership in a high-growth company; and (c) the chance to compress 10 years of career advancement into two to three years. The value proposition isn’t “get rich” — it’s autonomy, impact and an accelerated path to becoming a recognized operator in AI. 3. Build technical credibility through advisory networks, not executive hires. Instead of hiring one $5 million executive, allocate $500,000 across 10 advisers from Google, Meta and Microsoft who can provide technical validation during enterprise sales cycles. 4. Target executives in “golden handcuff” situations. The best candidates aren’t those getting $100 million offers — they’re the overlooked VPs at trillion-dollar companies who’ve built AI systems but are stuck behind org politics. They have the expertise, they’re ready to leave, and they’ll join for $2 million or $3 million equity packages if you can articulate a clear path to relevance. The companies winning without massive war chests aren’t trying to out-recruit Anthropic for research talent. They’re targeting enterprise operators who understand how AI systems actually get deployed at scale — and building credibility networks instead of expensive org charts. The real tradeoff We’re witnessing the formation of a technical aristocracy. A few thousand individuals now command compensation packages previously reserved for successful founders, as wealth transfers from broad-based tech employment to an elite operator class. Venture capital has fundamentally transformed from a growth capital fund into a talent acquisition fund. The AI gold rush will eventually end, but the economic structure it’s creating is permanent. In the agentic era, you don’t raise capital to hire engineers — you raise it to hire executives who know how to orchestrate AI agents that do the actual work. The question isn’t whether the rules have changed. They have. The question is which version of the new game you’re playing: competing for $20 million executives from frontier AI labs, or building asymmetrically with $2 million enterprise operators and credibility networks. Both paths work. Only one is accessible to most founders. Pukar C. Hamal is founder and CEO of SecurityPal, which eliminates the security review bottleneck that stalls enterprise deals for companies such as OpenAI, Figma and MongoDB. Born in rural Nepal, he built a profitable company with a 24/7 security operations command center in Kathmandu, proving that world-class execution doesn’t require Silicon Valley overhead. He writes about capital formation and the economics of AI-era operations. Illustration: Dom Guzman
Why This OpenAI And CoreWeave Investor Thinks The AI Market Is ‘Dangerously Overheated’
Mark Klein, president and CEO of SuRo Capital, believes that the AI startup market is not just frothy, but “dangerously overheated.” Founded in 2011, San Francisco-based SuRo Capital Corp. is a publicly traded investment fund that invests in “high-growth” venture-backed private companies. Naturally, Klein is bullish on OpenAI, considering that SuRo Capital owns a position in the buzzy startup, now the most highly valued private company in the world. But in his view, much of the rest of the AI ecosystem — including the capital that is chasing it — is inflating market caps. Mark Klein, president and CEO of SuRo Capital Klein believes that the fact some second-tier AI and adjacent startup valuations are tripling in months, not years, “with little change in fundamentals,” will not bode well in the long term. It’s a velocity he’s never seen in his 30 years as a VC investor. Besides OpenAI, SuRo was an early investor in CoreWeave and owns positions in unicorns including Vast Data, Canva, Plaid and other companies. The firm has seen exits in the likes of Dropbox, Facebook (now Meta), Lyft, ServiceTitan, Spotify and X. But for now, when it comes to AI investing, Klein is playing it safe. He’s holding on to cash, waiting for prices to correct. Crunchbase News interviewed Klein via email to get his thoughts on the AI space and why he believes OpenAI “copycats and the capital chasing them” could be creating more problems than solving them. Would you say that we’re in an AI bubble? The current AI market is meaningfully different from a bubble. There is genuine progress and value being created in model capability and in the buildout of AI infrastructure. At the same time, it is possible that some companies, particularly in the application layer or adjacent software categories, are a bit ahead of current fundamentals, given the strong interest in the space. There seems to be some concern that some of these companies don’t have the revenue or product to back-up such high valuations. Do you believe that’s true? AI is not a monolith. Valuation dynamics differ depending on where a company sits in the stack. There are three categories: infrastructure, LLM/models and applications. It is important to differentiate between these areas. Infrastructure and certain vertical applications with clearer unit economics may appear more grounded. Some of the early application tools may appear more extended, with the potential to face consolidation or pricing pressure as the market develops. What do you mean by holding on to cash and waiting for prices to correct? Our strategy has been to stay disciplined. We are seeing tremendous deal flow, which gives us the ability to be selective and focus on the opportunities that best fit our investment framework. We look for market-leading companies that are building transformational products, but we balance that with long-term value creation for shareholders. That means being mindful of valuations and deploying capital when expected returns justify the risk. Which specific AI subsectors do you see as the most overhyped? When looking at the frontier model leaders, and specifically OpenAI, we see a company driving a very meaningful step change in one of the most transformative technology shifts. Their progress is influencing investment activity at a scale larger than historical national efforts such as the Apollo Space Program or the Interstate Highway buildout. Some of the companies with the most aggressive valuation moves, especially relative to underlying performance, appear in the layers built on top of these foundational models. Many companies are attracting investment at this layer, though it is reasonable to expect that not all will ultimately win or become category leaders. As with any technological cycle, we should expect real value creation alongside some companies that fall behind or are consolidated as the market matures. Related Crunchbase query: See also: Illustration: Dom Guzman
Fintech Ramp Now Valued At $32B After $300M Raise Led By Lightspeed
Fintech startup Ramp is on a tear. The expense management company has raised yet another round of capital — $300 million at a $32 billion valuation, the company announced on Monday. The financing marks the fourth raise for New York-based Ramp in 2025 alone, and brings its total equity raised since its 2019 inception to $2.3 billion, per the company. It was valued at $13 billion after a secondary share sale in March, and announced a $500 million Series E-2 at a $22.5 billion valuation in late July. Roughly half of the $300 million in equity just raised will be used toward covering employee liquidity, according to the company. Any other employee liquidity needs will be covered by the secondary/tender portion, but that amount isn’t final. Lightspeed Venture Partners led the latest equity round, which included participation from existing backers such as Iconiq Capital, Founders Fund, Khosla Ventures, General Catalyst and Lux Capital, among others. New investors Alpha Wave Global, Bessemer Venture Partners, Robinhood Ventures, 1789 Capital, Epicenter Capital and Coral Capital wrote checks into the round as well. Ramp says it is now generating more than $1 billion in annualized revenue and producing free cash flow. It also reports that it has over 50,000 customers, double the amount it had last year, including CBRE, Shopify, Anduril Industries, Figma, Notion and Cursor. In particular, Ramp says it grew its enterprise customer base by 133% year over year, with more than 2,200 customers. Overall, it claims to power over $100 billion in purchases annually. Global venture funding to financial technology startups in 2025 has, as of Nov. 17, reached $45.8 billion across 3,291 deals, per Crunchbase data. That’s a 27.6% increase in dollars raised compared to the $35.9 billion raised across 4,348 deals during the same time period in 2024. Related Crunchbase query: Related reading: Illustration: Dom Guzman Clarification: This story has changed since its original publication to correct the amount of the new valuation.
Bezos Launches AI Startup With $6.2B In Reported Funding
Jeff Bezos will reportedly serve as co-CEO of a new artificial intelligence startup, Project Prometheus, focused on applying the technology to physical tasks, according to an article in The New York Times citing anonymous sources. Project Prometheus is reportedly launching with $6.2 billion in funding, partly from Bezos. The startup’s other co-CEO is Vik Bajaj, a physicist and chemist who most recently served as CEO and co-founder of biotech startup Foresite Labs. Bajaj is also known for his work at Google’s X, the company’s lab dedicated to pursuing moonshot projects. Additionally, he served as co-founder of Alphabet precision health tech startup Verily. Bezos, who stepped down from his longtime role as Amazon CEO in 2021, has long been active in funding and scaling startups. His best-known venture investment vehicle, Bezos Expeditions, has participated in at least 115 known funding rounds since the mid-2000s, per Crunchbase data. The Amazon founder is also famously associated with spacetech ambitions, most prominently through spaceflight startup Blue Origin. To date, the company says it has flown 80 individuals into space. Project Prometheus, meanwhile, will reportedly be focusing on AI that will help in engineering and manufacturing in multiple fields, including computers, aerospace and automobiles, per the article. Its work could potentially provide technology that Blue Origin could use to further its goals for expanding spaceflight. The company has already hired a team of close to 100 employees, according to the article, including researchers affiliated with OpenAI, Meta’s AI efforts, and other prominent AI labs. Illustration: Dom Guzman
Beyond The Pitch: How Emerging VCs Can Still Raise
By Alex Menn Over the past few years, we’ve been witnessing a paradox in venture capital. Carta’s data shows that smaller VC firms have higher TVPI than larger funds of the same vintage. Yet, less money has gone to emerging funds, even as they continue to outperform established players. Endowments, pensions and family offices claim they want exposure to innovation and risk, but in reality, their capital increasingly flows into the safest, largest franchises. A tougher market for first-time fundsAlex Menn Bloomberg reports that first-time fund managers have raised only $1.1 billion in the current fundraising cycle, a fraction of what they raised just a few years ago. Carta’s 2024 Fund Performance report states that for funds in the $100 million to $250 million range, the median number of LPs fell to 47 in 2024, nearly half the level of two years earlier. Even with a stellar team and returns surpassing Sequoia Capital’s, for most small funds, fundraising is no longer about projected IRR. It is about credibility and connection. The first fund is about people, not performance At an early stage, investors back the person, not the model. Sure, some may genuinely believe in you as a manager. But most will back you because they like being around you. Some like to talk about deep tech or discuss how you win deals. But many will just want to have a drink, play sports or be part of your circle. I call it long-term entertainment, because investors stay close due to the environment you create. The question is how to deepen that connection and make it real. Capital follows trust. Build trust, and you’ll have higher chances that the money shows up. Familiarity still decides who gets funded People still divide the world into “ours” and “theirs.” A Harvard–Stanford–Yale graduate who spent years at Goldman Sachs or Meta will hesitate to back someone from a completely different background, even if that person is successful. The solution to this barrier is to either stop fishing in ponds where the fish fear you, or learn to present yourself in a way they see you as an insider and belong to the same tribe. The goal is to be visible in the same spaces and speak the same cultural language, in order to build enough familiarity that the initial bias fades. Look beyond traditional LPs Most managers chase the same predictable investors. But while they are already flooded with decks, there’s more capital sitting where no one bothers to look. Owners of sports teams are a good example. They’re used to losing millions each season chasing Champions League victories; the risk in a venture fund feels tame by comparison. Developers who’ve stopped building in Europe because the economy has stalled are also searching for new ways to deploy money. And side note — don’t bother writing to the person who was the U.K.’s top taxpayer last year. By the time they make that list, you’re already too late. It can be valuable to have an anchor, but choose wisely Many first funds will end up with one dominant investor. This gives you stability and legitimacy. The key is why that investor comes in. The good ones invest because they want proximity to the team and trust your judgment. The bad ones invest because they want to influence where the money goes. You’ll never make real returns under someone else’s steering. A strong anchor believes in your process and stays close for perspective, not control. Otherwise, you don’t have an ally. You have a boss. Alex Menn is a partner at Begin Capital, a $120 million London-based venture capital fund backing tech founders in Europe and the U.S. Prior to moving into VC, he was a founder (exit in 2018) and spent more than 12 years in European private equity, where he was involved as an investor in over 50 deals worth $3.5 billion. Illustration: Dom Guzman
Longevity Startup Funding Sees Fewer Moonshots, But Plenty Of Buzzy Investments
Virtually everyone would like to live a longer, healthier life. Given the ubiquity of this aspiration, it’s not surprising that longevity has a lengthy history as a popular startup investment theme. However, the space is also not immune to market dynamics. In recent quarters, investors appear to have pulled back on large financings for startups innovating around extending lifespans. This comes in the wake of underwhelming performance of many of their biggest prior bets. As we’ve seen in prior analyses around longevity startup funding, deals continue to get done, even during off cycles. To illustrate what’s attracting interest this time around, we used Crunchbase data to assemble a list of 14 longevity-focused startups that secured funding in 2025. Few moonshots, more measured dealmaking The largest longevity-related funding round we could find this year totaled $130 million — which is sizable but not crazy moonshot-level dealmaking. It went to NewLimit, a startup co-founded by Coinbase CEO Brian Armstrong that touts its mission as “epigenetically reprogramming cells to younger states.” The next-largest rounds went to AI drug discovery companies, coinciding with a very buzzy year for the space. This includes Insilico Medicine, an AI drug developer that cites aging-related diseases as one of its core focus areas, which raised $110 million. Nine-year-old Juvenescence also picked up a $76 million Series B-1 tranche this spring to develop a pipeline of AI-enabled therapeutics to extend healthy lifespans. It’s focused on medicines that target core aging mechanisms to treat and prevent age-related diseases. And on the prevention side, Fountain Life, a startup that counts Peter Diamandis and Tony Robbins among its co-founders, secured an $18 million Series B. Fountain sells memberships that it says offer access to AI-guided insights, personalized restorative therapeutics and “proactive biologic optimization” for every stage of life. Seed-stage action Seed-stage companies, meanwhile, secured smaller rounds but also demonstrated ambitious visions. Toronto-based Grey Matter Neurosciences, for example, is looking to use focused ultrasound to treat age-related diseases of the brain. Launched last year, it secured $14 million in an initial funding round in January. Another intriguing newcomer is Seattle’s Circulate Health, which offers therapeutic plasma exchange to patients seeking to extend their healthy lifespan. The startup emerged from stealth and announced in July that it raised $12 million in a seed funding led by Khosla Ventures. And while it’s not precisely a longevity startup, Tomorrow Bio certainly has an intriguing business model. The Berlin-based startup provides cryopreservation for humans and pets. Longevity startups don’t always age well Since the desire to live a longer, healthier life is so universal, it’s common for longevity startups to generate early enthusiasm. Ironically, they don’t always age well. Performance of several longevity-focused IPOs demonstrates this propensity. Probably the most recent was BioAge Labs, a startup focused on “harnessing the biology of human aging” to develop new therapies for obesity and metabolic diseases. It went public on Nasdaq just over a year ago, and shares are now trading at less than half the initial IPO price. One of the biggest disappointments was Unity Biotechnology, a longevity-focused biotech that went public in 2018 after raising nearly $300 million in venture funding. Its shares are now worthless, and the company is no longer operating. Among early private unicorns, Human Longevity, a provider of diagnostics and longevity also co-founded by Diamandis, also underperformed expectations. The San Diego-based company reportedly saw its valuation fall to $310 million from $1.6 billion in 2018. It’s unclear where the valuation stands now. Not just about returns For longevity founders, however, ROI is obviously not the only metric that matters. The big success stories will be those that advance our understanding of the aging process and contribute to dialing back the ravages of age-related disease. Hopefully, they’ll continue to forge ahead on these fronts regardless of how the IPO market is faring. Related Crunchbase query: Related reading: Illustration: Dom Guzman
The Week’s 10 Biggest Funding Rounds: AI And Defense Tech Take The Lead
Want to keep track of the largest startup funding deals in 2025 with our curated list of $100 million-plus venture deals to U.S.-based companies? Check out The Crunchbase Megadeals Board. This is a weekly feature that runs down the week’s top 10 announced funding rounds in the U.S. Check out last week’s biggest funding rounds here. The largest rounds this week went to AI and defense tech companies, amid a generally busy period for big financings. Coding automation platform Cursor and parent company Anysphere led by a long shot, closing on a $2.3 billion Series D. The next-largest round was a $510 million financing for defense tech company Chaos Industries, followed by financings in sectors including AI inference, e-commerce and electric vehicles. 1. Anysphere, $2.3B, AI coding: Coding automation platform Cursor and parent company Anysphere raised $2.3 billion in a Series D financing backed by Accel, Thrive Capital, Andreessen Horowitz, DST Global, Coatue, Nvidia and Google. The round set a $29.3 billion post-money valuation for the San Francisco-headquartered company, which is more than 3x higher than what it secured just six months ago. 2. Chaos Industries, $510M, defense tech: Chaos Industries, a defense tech startup focused on counter-drone radar and communication systems, announced that it secured $510 million in new funding led by Valor Equity Partners. The round sets a $4.5 billion valuation for the 3-year-old, Los Angeles-based company. 3. D-Matrix, $275M, AI infrastructure: Santa Clara, California-based D-Matrix, a developer of generative AI inference compute for data centers, closed on $275 million in Series C funding. Bullhound Capital, Triatomic Capital and Temasek led the round, which sets a $2 billion valuation for the 6-year-old company. 4. Gopuff, $250M, fast delivery: Philadelphia-based Gopuff, which offers fast delivery of groceries and other products, picked up $250 million in new funding led by Eldridge Industries and Valor Equity Partners. Founded in 2013, Gopuff has raised $3.7 billion in known funding to date, per Crunchbase data. 5. Forterra, $238M, defense tech: Clarksburg, Maryland-based Forterra, a developer of autonomous systems for the defense sector, closed on $238 million in Series C equity and debt funding. Moore Strategic Ventures led the financing. 6. Skims, $225M, apparel: Skims, the Kim Kardashian-founded shapewear and clothing brand, landed $225 million in new financing led by Goldman Sachs. The round sets a $5 billion valuation for the 6-year-old, Los Angeles-based company. 7. Genspark, $200M, AI tools: AI agent builder Genspark raised $200 million in a financing led by SBI Investment and LG Technology Ventures. Per Crunchbase data, the round brings total funding to date to $360 million for the Palo Alto, California-based company, which was founded in 2023. 8. Harbinger, $160M, electric vehicles: Garden Grove, California-based Harbinger, a maker of medium-duty electric and hybrid vehicles, secured $160 million in a Series C round led by FedEx, Capricorn Investment Group, and recreational vehicle manufacturer Thor Industries. Along with its investment, FedEx placed an initial order for 53 Harbinger EVs, the company says. 9. TeraDAR, $150M, sensors: TeraDAR, a developer of terahertz technology to be used in sensors for automotive, defense and other industries, closed on $150 million in a Series B round. VXI Capital led the financing for the Boston-based company. 10. Alembic, $145M, AI marketing tools: Alembic, a startup that provides AI-enabled data analytics for marketing, picked up $145 million in a fundraising round led by Prysm Capital and Accenture. The round values the San Francisco-based company at $645 million. Methodology We tracked the largest announced rounds in the Crunchbase database that were raised by U.S.-based companies for the period of Nov. 8-14. Although most announced rounds are represented in the database, there could be a small time lag as some rounds are reported late in the week. Illustration: Dom Guzman
The Patience Gap In Healthcare AI, And What To Do About It
By Jonathan Kron Healthcare funding is surging again. Crunchbase data shows investors put an estimated $10.7 billion globally into startups in AI-powered health tech categories so far this year — already 24% higher than 2024’s full-year total. But what funders are failing to understand is that in this sector, adoption happens in regulatory cycles instead of viral ones. Their impatient push for hockey-stick growth is quietly suffocating the kind of systemic change that healthcare actually needs. Bessemer Venture Partners’ 2025 Healthcare AI Adoption Index found that while most health systems are running pilots, only 3 in 10 projects reach production. This shows that venture speed keeps outpacing the system’s ability to absorb it. Jonathan Kron When investors push for short-term traction, founders are forced to chase momentum instead of integration. They pivot to whatever metric looks good on a dashboard, even if it drags them further from clinical adoption. Some health tech startups start building out infrastructure that could reshape the system, but end up building features that fit pitch decks. The result is predictable: high burn, high noise and very little real change. This is not a problem of bad intentions. It is a problem of mismatched time horizons. In consumer tech, speed is a moat. In healthcare, it’s often a mirage. Trust, validation and interoperability are what compound value here, and those take years. The biggest returns in healthcare don’t come from the first wave of hype. They come from the infrastructure that everyone else eventually depends on. But that kind of staying power requires patient capital, not tourist capital. Why healthcare resists ‘move fast’ culture Healthcare AI is entering a defining moment. The same ingredients that fueled the crypto boom are all here. Rapid innovation, speculative funding and a flood of new entrants. If the sector keeps overpromising and underdelivering, a correction is inevitable. The antidote is integration. The companies that will last are the ones building with clinicians and health systems, not around them. They are teams that understand data standards, compliance and workflow realities. If AI companies in healthcare focus on solving grounded, verifiable problems rather than chasing headlines, they can avoid the crash cycle and deliver real transformation. The bubble no one wants to name There is also a valuation gap worth watching. The “AI wellness” segment has exploded because it is fast to market, light on regulation and easy to pitch. Engagement metrics are plentiful, while validation is optional. Meanwhile, the “AI clinical” space, focused on diagnostics, decision support and infrastructure, is slower and harder. Yet, it is where the defensible IP, regulatory moats and long-term value live. Five years from now, the speculative wellness valuations will likely correct downward while clinically grounded AI platforms quietly underpin global health systems. Founders who win play the long game For founders, the path forward begins with alignment. Not every investor understands healthcare, and that is fine. The goal is to find those who do. It is a waste of energy to educate fast-turnover capital. In this regard, it is wise to design for adoption, not hype. A technology that fits neatly into an existing workflow will outlast dozens of flashier competitors. Founders who anchor their story in outcomes and compliance, not features, will earn the trust that drives longevity. Patient investors will own the future Investors have a role to play, too. If they want meaningful change, they need to fund patient trust, not just fast algorithms. A model can be brilliant and still fail if it never earns clinical confidence. They should back integration-first models and think in decades, not quarters. Healthcare transformation doesn’t follow startup speed, and it never will. The investors who accept that and stay committed through early friction will own the platforms everyone else eventually builds on. At its best, the real compounding advantage of investing in healthcare AI is about underwriting the next operating system for global health. Those who understand that difference will not only create impact but will also capture the kind of returns that only compound when you have the patience to wait. Jonathan Kron is the CEO of BloodGPT, an AI-powered platform for diagnostic laboratories and clinics that interprets blood test results in seconds. He is a healthcare strategist and entrepreneur with more than 20 years of experience building and scaling healthcare ventures. Before joining BloodGPT he founded and exited Med24, a London-based clinic (raised £5 million, exited 2022), co-founded PCG, a Monaco-based healthcare-at-home startup that secured $1 million-plus in contracts on a $500,000 seed budget, and has advised digital health ventures including Klarity and LIPS Healthcare on major fundraising and growth. Illustration: Dom Guzman