Sequoia Capital

NBC News · 2026-05-14 2026-05-15-w2

OpenEvidence: Most physicians quietly use this medical AI tool

OpenAI launched ChatGPT for Clinicians in April without licensing NEJM or JAMA. OpenEvidence has both, and the market repriced it from $1B to $12B in 15 months on the back of 65% US physician reach and 27 million April clinical encounters. The binding constraint for entering credentialed verticals was never model quality; it was licensed-data governance and the operational-regime approval that comes with it. The Deployment Company and the LF Networking pattern this week are structurally identical: the moat that holds isn't capability, it's the layer of credential, distribution, or implementation sitting above it. For frontier labs, that means the verticals with the clearest content-licensing moats (clinical, legal, financial) will reprice fastest against whoever shows up without the corpus.

NBC News 2026-05-14-2

OpenEvidence: Most physicians quietly use this medical AI tool

OpenAI launched ChatGPT for Clinicians in April without licensing NEJM or JAMA. OpenEvidence has both, hit 65% of US physicians across 27 million April clinical encounters, and got repriced from $1B to $12B in 15 months. The binding constraint for frontier labs entering credentialed verticals is content licensing, not model capability, and OpenAI just supplied the revealed-preference proof.

WIRED · 2026-04-28 2026-05-01-w2

The Man Behind AlphaGo Thinks AI Is Taking the Wrong Path

David Silver raised $1.1B at a $5.1B valuation on the argument that LLMs are bounded by the human-data manifold, and that the only way out is RL-trained agents operating in simulation. The architectural evidence is real: AlphaGo's Move 37 came from outside the space of human play, and Sutton's Turing Award validates the theoretical foundation Silver is building on. What this week's picks clarify is that the capability argument is almost beside the point: the OpenAI goblin postmortem shows that even current systems can't reliably control what they're optimizing for, and Karpathy's MenuGen demo shows that the harness around the model is already more consequential than the model itself. Silver's unpriced bottleneck, reliable verifiers for unbounded domains, is also the missing piece in both of those stories. The next value pool isn't in bigger models or better prompts; it's in the infrastructure that tells you whether the output was actually right.

Sequoia Capital · 2026-04-30 2026-05-01-w3

Andrej Karpathy: From Vibe Coding to Agentic Engineering

Karpathy's trust threshold is the most telling data point in the piece: senior practitioners stopped correcting agent outputs in December 2025, not because agents became perfect, but because the correction cost exceeded the perceived value of intervening. The MenuGen demo makes the structural consequence concrete: one Gemini Nano Banana call replaced an entire Vercel app stack, which reframes the build decision from 'how should we architect this' to 'should this app exist at all.' That reframing connects to both other picks this week. Silver is betting that the next capability jump requires simulation environments and reliable scoring; the goblin postmortem confirms that without those, systems optimize for the wrong thing silently and at scale. The durable position in agentic AI isn't the model or the prompt or even the agent: it's the verification environment, the infrastructure that makes iteration trustworthy enough to trust.

Sequoia Capital 2026-04-30-3

Andrej Karpathy: From Vibe Coding to Agentic Engineering

Karpathy's December 2025 trust threshold is a behavioral signal more telling than any benchmark: senior practitioners stopped correcting agent outputs. The sharper insight sits in the MenuGen demo, where one Gemini Nano Banana call replaced an entire Vercel app stack; that collapse turns 'should this app exist at all' into the new build-evaluation primitive for 2026. Verifiability is where iteration compounds, which makes the verification environment, not the model or the prompt, the durable position in agentic AI.

WIRED 2026-04-28-1

The Man Behind AlphaGo Thinks AI Is Taking the Wrong Path

David Silver left DeepMind to raise $1.1B at $5.1B for Ineffable Intelligence on a thesis that says LLMs hit a ceiling defined by the human-data manifold and only RL-trained agents in simulations can break through. The architectural argument has teeth: AlphaGo's Move 37 came from outside human play, and Sutton just won the Turing Award for the foundational work. The unspoken bottleneck if Silver is right isn't compute or data, it's verifiers — reliable scoring functions for unbounded domains like science, governance, novel discovery — and that is the quiet investable category nobody's pricing yet.

Financial Times 2026-04-12-3

How will AI change the org chart?

Dorsey's hierarchy-to-intelligence thesis lands differently when you notice the article's own evidence: Handelsbanken, Disco Corp, and Bayer all flattened management without AI. The technology isn't the cause; it's the accelerant for an organizational redesign that was already overdue. The $2.6T in US manager payroll won't vanish through layoffs; companies will simply stop hiring the next generation of coordinators, routing the savings into decision-speed infrastructure instead.

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