By the time a frontier AI researcher’s departure reaches TechCrunch, the best-connected investors may already be months into the relationship. That is the problem with treating talent movement as news. News tells you what happened. Sourcing infrastructure should tell you what is beginning to happen. Frontier AI labs have become some of the most productive founder factories in venture history.…
It's 1 AM. You're still awake. Not because of a deadline. The Slack stopped hours ago. You're awake because this is the only hour of the day that belongs to you. That's not a sleep problem. That's a resource allocation problem. THE PERFORMANCE OF THE DAY From the moment you wake up, you are someone's version of you. You're an answer to an email. A face on a call. A founder projecting confidence. A…
The standard pitch for ML-driven VC sourcing is correct in the aggregate and wrong at the margin where it matters. Hiring velocity, web traffic, GitHub commits, app store ratings, these signals outperform gut intuition across the full universe of startups. The problem is that the full universe is not your portfolio. Stage-agnostic scoring models are systematically miscalibrated because the signals…
The distress signal arrives in the board update before it arrives in the financials. You are reading the financials. Every month, founders send you a structured window into their psychological state: the board update. Revenue numbers, burn rate, headcount. You scan them. You check the metrics against the previous quarter. You note whether the company is on plan. What you are not doing, what almost…
The AI Engineer World’s Fair opens in San Francisco on June 28. It has more than 6,000 attendees, 300 speakers and 29 tracks. That scale matters because this is not a conference about what AI might become. It is a conference about what AI has already become, and what now breaks when companies try to run it at scale. The people attending are not tourists. They are engineers, founders, product…
The multi-agent investment committee is becoming the new toy in venture. Five AI agents read the same memo. One is the market-sizing agent. One is the technical diligence agent. One is the financial model agent. One is the founder-pattern agent. One is the skeptic. They debate, vote, and produce a dashboard with confidence scores. It looks rigorous. It may also be fake rigor. The problem is not…
The most dangerous slide in a Southeast Asian startup deck is not the TAM slide. It is the U.S. pilot slide. Every founder expanding into America wants that one recognizable logo. A U.S. enterprise agrees to test the product. Someone senior sounds excited. The company runs a proof of concept. The logo goes into the fundraising deck. Suddenly everyone starts calling it “U.S. traction.” I would be…
For twenty years, software investors underwrote a simple assumption: software scales better than labor. SaaS sold access to reusable code. Add another customer, seat, or department, and the marginal cost was close to zero. That was the economic magic behind 80–90% gross margins, high net retention, and the valuation framework that built modern enterprise software. AI agents complicate that…
The headlines all said the same thing in Q1 2026: venture capital is back. Global VC hit $330.9 billion — a record. Founders read those numbers and walked into fundraising meetings expecting a warm market. Most of them got a cold one. Here's what the headline didn't say: five companies captured 63% of it. OpenAI ($122B), Anthropic ($30.6B), xAI ($20B), Waymo ($16B), Databricks ($7B). Strip those…
Samir Kaji recently reignited an important conversation about venture capital. A follow-up piece in Venture Notes , titled “The VC Playbook Has Changed… But Not Equally for Everyone,” argues that while AI has expanded the ceiling of outcomes, the structural advantages remain concentrated among Tier 1 funds with privileged access. The logic is compelling. Venture capital is still governed by power…
Venture capital runs on a simple lie we all tell ourselves: if revenue is going up and the product feels inevitable, the unit economics will sort themselves out later. That lie worked in SaaS because “later” mostly meant: keep shipping, keep selling, and your marginal cost asymptotically goes to zero. Serving the 10,000th user was basically free. So you could fund growth first, then let operating…
Generate:Biomedicines just announced Phase 3 trials for GB-0895, an antibody entirely designed by AI, recruiting patients from 45 countries as of late 2025. Isomorphic Labs has human trials "very close." That's not hype. That's proof that AI-designed drugs work in humans. And the market hasn't priced this in yet. Generative biology, applying the same transformer architectures behind ChatGPT to…
Naval called Moltbook the “new reverse Turing test,” and everyone immediately treated it like a profound milestone. I think it’s something else: a live-fire test of whether we can contain agentic systems once they’re networked together. Let’s be precise. Moltbook is an AI-only social platform, roughly “Reddit, but for agents,” where humans can watch but not participate. The pitch is simple:…
Oxford’s The Impact of Artificial Intelligence on Venture Capital argues AI accelerates sourcing and diligence, but investment decisions stay human because durable moats are socially grounded conviction, gut feeling, and networks. I agree with the workflow diagnosis. I disagree with the implied endgame. Not because “gut” is fake—but because “gut” is often a label we apply when we haven’t defined…
I called neuro-symbolic AI a 600% growth area back when I analyzed 20,000+ NEURIPS papers. I wrote that world models would unlock the $100T bet because spatial intelligence beats text prediction. I predicted AGI would expose average VCs because LLMs struggle with complex planning and causal reasoning. Now Ilya Sutskever—co-founder of OpenAI, the guy who built the thing everyone thought would lead…
The performance gap between tier-1 human VCs and current AI on startup selection isn't what you think. VCBench: a new standardized benchmark where both humans and LLMs evaluate 9,000 anonymized founder profiles, shows top VCs achieving 5.6% precision. GPT-4o hit 29.1%. DeepSeek-V3 reached 59.1% (though with brutal 3% recall, meaning it almost never said "yes").[1] That's not a rounding error.…
Yann LeCun, the Turing Award winner who helped build the GPU-fueled LLM machine, just walked away from it. He didn't retire. He didn't fade. He started a new company and said out loud: we've been optimizing the wrong problem. That's not ego protection. That's credibility. What changed For three years, while Meta poured hundreds of billions into scaling language models, LeCun watched the returns…
The climate tech sector is correcting. After the hype peak of 2021—$51 billion in funding—reality hit hard. Funding dropped 75% by 2024. AI vacuumed up the oxygen. Generalist VCs fled. What's left is brutal clarity: only capital-efficient, economically-defensible businesses survive. This is actually good news for the right founders. The pattern is familiar. In Cleantech 1.0, founders built for…
Founders often ask: “Will more US tech giants buy Asian startups?” The sharper question is: if only a small fraction of companies generate most of the returns, can you afford to build anything that isn’t capable of becoming a global outlier? Meta’s US$2+ billion acquisition of Manus—a company founded in Beijing, redomiciled in Singapore, and integrated into Meta’s AI stack in under a year—is not…
Everyone keeps asking: "Can AI do X yet?" That's the wrong question, in the same way "How many alumni does this university have?" is the wrong question. The question is always: out of what total ? In 2024–2025, AI was graded on the easiest denominator available: best-case prompts, controlled conditions, with a human babysitter . In 2026, the denominator changes to: all the messy, real tasks done…
Most unicorn-founder university rankings are really school-size rankings. A more useful view is “conversion efficiency”: unicorn founders per plausible founder cohort, not per total living alumni. The denominator problem Ilya Strebulaev’s published unicorn-founder-by-university counts are a strong numerator, but most people may implicitly pair them with the wrong denominator (“living alumni”).…
The most successful field in computer science right now is also the most anxious. You can feel it in Reddit threads, conference hallways, and DMs: something about how we do ML research is off. The pace is intoxicating, the progress is real—and yet the people building it are quietly asking, “Is this sustainable? Is this still science?” That tension is the story: a field that went from scrappy…
World models are quietly transforming AI from text predictors into systems that understand and simulate the real world. Unlike large language models (LLMs) that predict the next word, world models build internal representations of how environments evolve over time and how actions change states. This leap from language to spatial intelligence promises to unlock AI capable of perceiving, reasoning,…
Build global, or get boxed in. Singapore is an exceptional launchpad for deep tech—world-class research, predictable regulation, dense talent, and brand equity that travels—but the world won’t bend to our advantages unless the execution is ruthless, market-led, and globally capitalized. The playbook is simple to say, hard to do: prove your science is best-in-class, lock real customer pain with a…
Expanding a foreign AI startup into the United States isn’t a simple market entry—it’s a strategic reset across technology, capital, talent, and culture. America remains the highest-leverage arena for AI due to capital concentration, enterprise buyer expectations, and dense technical ecosystems. Winning requires timing the move, structuring the team for speed, adapting GTM and messaging to…
Copying isn’t laziness; it’s leverage in a region where timing, localization, and distribution matter more than novelty—and in 2026 the bar rises because bigger VC funds with thicker dry powder need bigger outcomes to matter. If you want their capital, your market must credibly support 20x fund-level math, which points founders toward fintech rails, enterprise automation layers, and…
Smart people aren’t the ones who never miss. They’re the ones who course-correct quickly and publicly—without ego, without shame. In startups, that’s not a personality quirk; it’s a survival trait. The founders who win treat beliefs like code: ship, test, refactor. They trade pride for progress. Why changing your mind signals intelligence Intellectual humility is recognizing the limits of your…
If you’re raising kids in Asia, the default operating system is discipline, duty, and deference to authority. It produces astonishing focus, world-class test scores, and an instinct for precision. If you’re raising kids in America, the OS is independence, speaking up, and pushing back. It produces boldness, restless energy, and a bias for action even before all the facts are in. Both systems…
I've spent years pattern-matching across startups, digging through founder trajectories, and watching ecosystems evolve. But nothing crystallizes the proximity advantage quite like watching the current AI wave unfold in San Francisco. If you're an AI founder operating outside the Bay Area right now, I'll cut to the chase: you're likely working with information that's 6 to 12 months behind what the…
The AI sector in 2025 exhibits classic bubble characteristics, but unlike previous tech manias, this one sits atop genuine technological transformation. Here's what the latest data reveals about timing, risks, and strategic positioning. The Bubble Evidence Is Overwhelming Multiple indicators confirm we're in speculative territory. AI startups now trade at 50-70x revenue multiples, while the sector…