That’s the headline that should make you stop scrolling. Stark Defence, founded in 2024, just closed a €500 million round (about $570 million) led by Sequoia Capital and Peter Thiel’s Founders Fund, with the NATO Innovation Fund, Project A, Air Street Capital, 201 Ventures and Döpfner Capital joining. Reported valuations differ by outlet, but every source puts it north of €3 billion, roughly triple where the company sat back in February. Total raised now runs around €640 million, up from roughly €140 million before this round.

Here’s the part the headlines skip. According to Financial Times reporting, Stark’s Virtus drones failed to hit a single target across four attempts in trials with British and German forces last November. Germany approved a €269 million Bundeswehr contract anyway, with options stretching toward €2.86 billion. More than 80% of the new money is earmarked for manufacturing and R&D, not go-to-market. And Stark is now on the clock to equip a full German brigade in Lithuania by the end of 2026.

So why would two of the sharpest funds on earth write that check?

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This is where one of the models from my book earns its keep: Second-Order Thinking.

First-order thinking reads the trial result and stops. The drone missed, so it’s a bad product, so it’s a bad bet. Clean, fast, wrong.

Second-order thinking asks what happens next, and then what happens after that. The thing being priced here isn’t this quarter’s hit rate. It’s European strike-drone manufacturing capacity during a rearmament cycle, sitting on top of a procurement position inside contracts that are already signed. In a war of attrition, a good-enough system you can build by the thousand beats a perfect system you can’t ship. Capacity is the scarce asset. Stark is being financed like a factory, because a factory is what the buyers actually need.

I’ve spent enough time around regulated, infrastructure-heavy markets to recognize the shape of this. At /mkt, we build inside systems where the demo is the easy part and compliant execution at scale is the hard part. Defense procurement rhymes with that: signed contracts, certifications, and hitting a delivery deadline carry more weight than a single flashy test.

Now the contrarian flag, and I’ll keep it conservative, because I’m not here to tell anyone what to buy. When capital races to “be in the room,” price can run out ahead of proof. A signed contract isn’t a battlefield result, and €3 billion-plus is a lot of expectation to load onto a two-year-old company that hasn’t yet shown it can manufacture at the volumes it’s promising. The second-order logic is sound. The valuation is where the risk actually lives.

Watch the factories, not the press releases. The next eighteen months are a single question: can Stark build what it already sold?

If this was useful, share it with someone who builds things. And if you want the full toolkit of 50 mental models, you can grab my book, Mental Models: How to Think, Act, and Win, right now.

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Startup Spotlight is for informational and educational purposes only. It is not investment advice, an offer, or a solicitation to buy or sell any security. Company metrics are self-reported, and funding details are drawn from public reporting and company statements. Figures may change.

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That single decision is why this company is worth your attention this week.

Company Overview

In plain English: Adaptive Innovations is a home health care provider that runs on its own AI operating system. When a hospital discharges an elderly patient who needs care at home, a traditional agency handles the intake, scheduling, clinical documentation, and compliance billing through a tangle of legacy software and human coordinators. Adaptive automates that back office with AI and sends its own clinicians into the home. It isn’t selling the tooling to someone else. It’s the licensed provider getting paid to deliver the care.

The company is at the Series A stage. It came out of stealth in early June with $60 million raised to date: a $50 million Series A led by Felicis, plus a previously undisclosed $10 million seed round that Bain Capital Ventures led. The Series A drew in Bain Capital Ventures, Optum Ventures, Sunflower Capital, Conviction, BoxGroup, SV Angel, Dorm Room Fund, and Constellation, along with angels from healthcare services and frontier AI labs.

The founding team runs deep on both sides of the problem. Co-CEOs Alex Wendland and Logan Stinson lead alongside CTO Ryan Tolsma and COO Hunter Stinson, working out of New York City and Dallas. The company says its bench includes engineers from Palantir and Jane Street and operators from McKinsey, Harvard, Stanford, and the U.S. Army Rangers. That’s an unusual mix: people who can ship hard software sitting next to people who’ve actually run operations under pressure.

What have they built so far? According to the company, 200 clinicians have completed more than 100,000 home visits in 18 months. Adaptive reports a rehospitalization rate below 5% against an industry average around 11%, and says its AI workflows have cut clinician documentation time by roughly 80%. Treat those as company-reported figures, because they are. They’re still the kind of early numbers that make sharp investors lean in.

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On June 23, Cadence, the clinical AI company managing chronic care for older adults, announced a $100 million Series C led by Spark Capital. The syndicate is worth reading closely. Thrive Capital, General Catalyst, Coatue, and B Capital came in alongside three health-system investors: Corewell Health Ventures, Memorial Hermann, and Duke Health. Cadence also announced a new affiliation with Duke Health the same day.

The product fits the moment. Cadence supports more than 90,000 patients across 20-plus health systems, using AI to handle the high-volume routine work of chronic care, monitoring vitals and surfacing risk, so clinicians spend their time on the decisions that need a human.

Here’s the part the headline skips. Medicare’s innovation center rolled out an experimental program called ACCESS that pays providers a set amount per patient, roughly $180 to $420 in year one depending on the condition, and pays the full amount only if patients hit outcome targets. Compare that to a standard remote-monitoring setup, where a provider can bill around $100 per patient per month for doing the work regardless of results. Cadence said it would be among the first to sign up.

This is where I’d reach for Skin in the Game, one of the models in my book. The idea is simple: you carry real downside, not just upside, and your incentives are wired to the result instead of the activity. ACCESS flips healthcare’s default. The old model pays for motion. ACCESS pays for outcomes. Cadence is volunteering for a structure where it eats the risk if patients don’t get better.

That also explains the cap table. When three health systems write checks into the company they’re buying from, they’ve got skin in the game in its success too. That’s not a logo grab. That’s alignment.

The contrarian read: the $100 million is the least interesting number in this story. The interesting numbers are $180 to $420 per patient paid on results, against $100 a month paid no matter what. Cadence is betting it can use AI to make the outcomes math work where labor-heavy competitors can’t. If patients don’t improve, the model doesn’t pay. Most companies run from a constraint like that. The good ones build toward it.

I think about this at /mkt, where we operate inside a Reg A+ structure with tZERO as our trading infrastructure. In regulated markets you don’t write the rules, you build to fit them. The structures that force you to win only when your users win can look like constraints. They usually turn into moats.

If this was useful, share it with someone who builds things. And if you want the full toolkit of 50 mental models, my book is coming soon.

This newsletter is for informational and educational purposes only. It is not investment, legal, tax, or financial advice, and it is not an offer or solicitation to buy or sell any security. Figures are drawn from publicly available reports as of June 23, 2026, and are subject to change. Do your own research and consult a licensed professional before making any decision.

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What Corgi Actually Does

Corgi is an AI-native, full-stack commercial insurance carrier built for startups and high-growth companies. It was founded in 2024 by Nico Laqua (CEO) and Emily Yuan (COO), came out of Y Combinator’s Spring 2024 batch, and has spent less than two years going from zero to a $2.6 billion valuation.

On May 28, 2026, …

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What Contraline Actually Does

Contraline, Inc. is a clinical-stage biopharmaceutical company headquartered in Charlottesville, Virginia. It’s building what could become the first approved pharmacological contraceptive for men. The company has two investigational products in active clinical development: NES/T Gel and ADAM.

On June 2, 2026, Contraline closed a $92.5 million Series B, co-led by BVF Partners and RA Capital Management, with participation from GV (Google Ventures), Lumira Ventures, Invus, and other investors. The round funds Phase 3 readiness for NES/T and continued advancement of ADAM.

The company was co-founded by Kevin Eisenfrats, who serves as CEO. Eisenfrats has been building in men’s reproductive health since his undergraduate days at the University of Virginia, where the core concept behind ADAM was first developed. He’s not a career biotech executive who wandered into a hot category — he identified the unmet need, raised early capital from GV, ran first-in-human trials in Australia, and is now steering a late-stage clinical program backed by some of the sharpest life sciences investors in the business. Iris van Alderwerelt van Rosenburgh from BVF Partners joins the board alongside the Series B close.

The two investigational male contraceptive products:

• NES/T Gel — a daily hormonal topical gel combining Nestorone (a progestin) with testosterone. Suppresses sperm production while maintaining physiological testosterone levels, avoiding the side effects that tanked prior hormonal male contraceptive programs. Licensed from the Population Council and the NIH’s NICHD. Phase 2b completed, enrolling 462 couples globally. Phase 3 start projected for 2027.

• ADAM — a non-hormonal injectable hydrogel implanted into the vas deferens via a minimally invasive procedure. Physically blocks sperm transport and is designed to eventually biodegrade, making it reversible. First-in-human trial completed across three Australian sites. 25 participants enrolled, 100% successful implantation rate. 24-month efficacy data shows azoospermia in participants who’ve reached that milestone. Phase 2 now in planning.

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Every generative AI product you’ve used so far works the same way. You give it instructions. It runs computations. Eventually, it hands you a result. That lag — even if it’s milliseconds — is a ceiling. It means AI can’t react. It can only respond.

A San Francisco startup called Reactor just raised $59 million to blow past that ceiling entirely.

Reactor emerged from stealth on May 28th with a Series A led by Lightspeed Venture Partners. WndrCo, Amplify Partners, Sky9 Capital, and FPV Ventures also participated. The company was co-founded by Alberto Taiuti and Bryce Schmidtchen, both former technical leads on the Apple Vision Pro. Taiuti previously co-founded Luma AI, where he built the infrastructure behind one of the most widely used 3D and video generation platforms in the market. They know what it takes to ship this stuff at scale.

The product: a unified SDK and API that lets developers build real-time interactive AI applications in just a few lines of code. No batch processing. No prompt-and-wait. The video generates as you interact with it — dynamically shaped by user input, in the moment it’s happening. Reactor calls this the shift from AI as a tool you prompt to AI as an experience you step inside.

Jeffrey Katzenberg, the Hollywood mogul turned investor, joined through his WndrCo holding company as a board observer. His read on it: “Literally every facet of the production pipeline can be enhanced using these tools. Live action, TV, film, commercial work, animation — any visual medium.” That’s not a media pitch. That’s an infrastructure pitch wearing a Hollywood jacket.

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Most fintechs spend a decade trying to capture banking-like economics without becoming a bank. Mercury just did the opposite.

The headline last Wednesday was the money. Mercury closed a $200M Series D at a $5.2 billion valuation, led by TCV, with Andreessen Horowitz, Coatue, Sequoia, Sapphire, Spark, and CRV all participating. That’s up 49% from a $3.5B valuation just 14 months ago. CEO Immad Akhund told CNBC the company is at $650M annualized revenue with four years of profitability. Total funding to date sits at roughly $700M across primary and secondary.

The number that actually matters is buried lower in the announcement. Mercury submitted an application to the Office of the Comptroller of the Currency for a national bank charter, and applied for federal deposit insurance with the FDIC. The company has stated plans to file with the Federal Reserve to restructure as a bank holding company.

For context, this is the hardest path in fintech. Estimated timeline is 12 to 24 months. Capital requirements are steep. Operating constraints are real. Very few fintechs in the modern era have made it through.

So why do it?

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Vapi is a San Francisco-based voice AI platform that enables enterprises to build, deploy, and manage configurable voice agents at scale. The company raised a $50 million Series B on May 12, 2026, led by Peak XV, with participation from M12 (Microsoft’s Venture Fund), Kleiner Perkins, and Bessemer Venture Partners, bringing total funding to $72 million. The round valued the company at approximately $500 million.

Co-founders Jordan Dearsley and Nikhil Gupta met at the University of Waterloo and previously built a Y Combinator-backed calendar app that reached profitability. Dearsley started Vapi almost by accident. In mid-2023, he built a voice-based AI therapist for his daily walks, chaining models together and optimizing for latency until he had a working phone-based system. The therapy product didn’t take off, but the infrastructure did. Vapi launched publicly on Product Hunt in March 2024.

The team is small but battle-tested. The startup currently has around 100 employees. But here’s what matters: the company reports more than 1 million developers, over 2.7 million unique agents created, and over 1 billion calls made. That’s not hype. That’s proof of product-market fit.

The Market: Why Voice AI Is Becoming Non-Negotiable

The enterprise voice AI market is moving from “nice to have” to “competitive necessity” in real time.

The global enterprise voice AI agents market was valued at $6.8 billion in 2025 and is projected to grow at a compound annual growth rate of 29.5% from 2026 to 2034, reaching an estimated $62.4 billion by 2034. That’s a 9x market expansion over eight years. But there’s a more immediate signal: the market crossed $22 billion in 2026, enterprise adoption tripled, and Gartner says contact centers will save $80 billion this year from conversational AI alone.

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SECTION 1: Company Overview

Adfin is a London-based fintech built to solve a deceptively simple problem: getting small businesses paid on time. But the approach is anything but simple.

The company pairs proprietary payment infrastructure with what it calls “agentic AI workflows”—autonomous agents that decide the best course of action to recover, reconcile, and accelerate invoice payments. Translation: an AI system that acts on behalf of your finance team, deciding which payment method to present, when to retry failed payments, how to sequence reminders, and when to escalate without human judgment bottlenecks.

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Company Overview

Standard Intelligence is a six-person AI research company headquartered in San Francisco. It closed a $75 million Series A on April 30, 2026, led by Sequoia Capital and Spark Capital, at a pre-money valuation of approximately $425 million. The post-money figure lands near $500 million. That math gives you a company worth half a billion dollars before it has publicly shipped a product, staffed a sales team, or hired its tenth employee.

The investors behind the round are not tourists. Sonya Huang and Mikowai Ashwill represented Sequoia. Yasmin Razavi led for Spark Capital. Angel investors include Andrej Karpathy, the AI researcher who co-founded OpenAI and ran Tesla’s Autopilot program; Stanley Druckenmiller, one of the most respected macro investors alive; and Milan Kovac, former head of Autopilot software at Tesla.

The founding team is Galen Mead (21) and Devansh Pandey (20). They met as teenagers through the Atlas Fellowship, a selective program for high-school students focused on AI alignment. Both concluded, independently and then together, that AGI was arriving faster than institutions understood. Both left their undergraduate programs to act on that conclusion. Mead had been enrolled at the University of Toronto. Sequoia’s written description of them is unusually pointed: “taste, scrappiness, technical courage, and ambition” in a combination the firm found rare enough to write a very large check.

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