Belated post: excited to share I joined @ScribbleVC last year. Since 2015, I’ve tried to be like the best VCs I worked with as an operator/founder — show up when needed and stay out of the way when not. That’s also the Scribble way. Proud to be on board!

The Artificial Intelligence Underwriting Company has raised $55M to audit and insure frontier AI models. Insurance produces audits the public can trust and understand. The mechanism is simple: insurers need audits to price the risk. They pick auditors they believe will help them price the risk most accurately. Insurers then turn the audits into a price signal that cuts through political debates. Insurers are aligned with the public: if they get the audits wrong, they go out of business. That’s different from today, where labs pick their own auditors, creating public distrust. Insurance only works if we scale up auditing, and we are building the infrastructure to do that. Millions of agents are being deployed; they leave terabytes of traces and will create thousands of incidents across dozens of risk categories. To scale auditing, we need reliable agents to surface evidence traces for human review. History guides us. Take cars: auto insurers funded crash tests to price risks; crash tests led us to airbags, lowering the risk. Take electricity: home insurers funded lightbulb tests to price fire risks; today, every lightbulb carries a safety mark. Nuclear safety works similarly. We’ve been learning by doing.. In the last 6 months, we’ve audited and insured frontier agent builders like Cursor, ElevenLabs, Lovable and Harvey. For ElevenLabs to get the world’s first agent insurance coverage, a Lloyd’s of London insurer required quarterly technical audits by an auditor of the insurer’s choice. We’ve built infrastructure for quarterly technical audits of any agent, working alongside firms like Gray Swan (technical evaluations) and Schellman (audit). In the coming weeks, we’ll share our vision for how an insurance ecosystem can work for the frontier, and open source the world’s first actuarial model for frontier AI catastrophic risk. We’re hiring across all roles in San Francisco. Come do your life’s work with us. Rune & Rajiv

I’m psyched to announce that Smack has raised a $61M Series B. This funding accelerates our ability to ship domain-specific AI models that are actually relevant across the Joint Force in 2026, and to build the hardware to deploy it to the tactical edge. I’m truly grateful for the investors, technologists, and warriors who have become Team Smack. To @costanoavc and First In, thanks for doubling down on our merry band of psychopaths. Your support, along with @p72vc, @GeodesicCap, @NomiCapital, @felicis, @ScribbleVC, @fortitude_vc, @BloombergBeta, @PalumniVc, and Fulcrum VG supercharges our ability to deliver Decision Dominance to the DoW. To our researchers and engineers, thanks for choosing to build here. Without you, Smack’s story would be Marines doing AI good. No one wants to hear that story. The late night breakthroughs amidst piles of Celsii are testaments to the fact that you are leading the charge on mission-driven AI. What you’ve built will save lives in combat. To our warriors, thanks for continuing to serve. I’ve deployed to combat with many of you. It’s an honor to ride with you again. For those I haven’t, it’s an honor to serve with you now. Together, we will become a new category of defense prime: built by warriors, for warriors.

From "eating glass" to building a $5.3B healthcare AI leader… This is the incredible story of how @scribblevc founder @ShivdevRao built @AbridgeHQ, now undergirding 300+ health systems. We recorded our recent catch-up + Shiv shared: —> The most underrated moat in AI right now —> How to unlock exponential growth —> Critical skills founders need in 2026 —> Why one unchanging thesis is paramount Watch/listen: piped.video/9izBbAMaYok?si=107s…

Human biology matters. Scientists and AI need human data to understand health and disease. Crownlands is open sourcing Gateway 4M, the largest single-cell tissue dataset ever released from living humans, to advance research on brain aging and neurodegeneration.

Announcing @xdofai: We’ve raised $70 million to build the core robotic infrastructure ecosystem for robot foundation models. My cofounders Fred (@YideShentu), Nemo (@itsnemojin) and I have been pursuing the dream of general purpose robots for our entire lives. After work at Covariant, Meta and Tesla, it became clear to us that general purpose robots are coming, and we are building XDOF to help make them a reality. For the last two years, we’ve been working behind the scenes to support major labs and companies deploying robots. In us, they have a partner with full-stack expertise, from hardware to operations to policy training. As our first public contribution to the space, we are open-sourcing ABC-130K, the largest open source teleoperation dataset, in collaboration with our partners from UC Berkeley, Carnegie Mellon, MIT and Amazon FAR. Thank you to our customers, partners, collaborators and investors for your trust and conviction in us. Together, we can accelerate the future of robotics!

New AI x Science research: Frontier models have gaps in their scientific knowledge. Our new eval tests how models recall significant published findings without tools, in Alzheimer’s disease. GPT-5.5 performed best among released models, but the benchmark remains far from saturated. Questions are based on prominent findings, often the central claims from highly cited papers, that were published before the models’ cutoff dates. Does it impact AI x Science discovery agents? In the topics that the LLMs have gaps in “parametric” knowledge, agents using the model overlook potential discoveries -- even with tools and internet search. The conclusion: training models more intensively on the latest scientific findings is a promising way to make scientific agents more useful! “More information can be pulled into context. More information should be pulled into context. But there will always be a marginal query that the agent does not run, and the shape of this frontier is determined by internal knowledge.” Link to research blog below:

Today is my last day at OpenAI, as OpenAI for Science is being decentralized into other research teams. It’s been a mind-expanding two years, from Chief Product Officer to joining the research team and starting OpenAI for Science. Accelerating science will be one of the most stunningly positive outcomes of our push to AGI, and I’m rooting for @sama @markchen90 @fidjissimo @gdb @merettm and the whole team!

Introducing FrontierSWE, an ultra-long horizon coding benchmark. We test agents on some of the hardest technical tasks like optimizing a video rendering library or training a model to predict the quantum properties of molecules. Despite having 20 hours, they rarely succeed

you can now control things with your brain. literally. we're building the most wearable BCI on the planet, with @sabi, backed by @khoslaventures @accel @initialized & @kevinweil. we collected the world’s largest neural dataset and trained the most capable Brain Foundation Model. then we invented a new class of biosensors powered by custom ASICs. type without typing. click without clicking. a cap that lets your brain do the work. we’re sabi.

Filmed at a real Primer school. Starring real Primer students. A 200 year vision for American Education:

Little textbooks called ‘primers’ shaped the first 200 years of American Education. Primer will shape the next 200. This is our labor of love for the kids of America. A vision for the future of Education, featuring MarQuis – a real Primer student:

We raised $165M at a $1.15B valuation to stop doing demos. 2026 is about 1) deployment and 2) research. We will start shipping Memo with our new frontier models in a few months. Our series-B is led by Coatue, with Thomas Laffont joining the board. ->🧵

Sunday's dishwasher-loading, laundry-folding robot starts beta testing this year. CEO Tony Zhao explains how the robot learns — and why it wears a hat bloom.bg/3NAxIxQ

Excited to release PostTrainBench v1.0! This benchmark evaluates the ability of frontier AI agents to post-train language models in a simplified setting. We believe this is a first step toward tracking progress in recursive self-improvement 🧵:

SO excited to welcome @stuartdsmith to @ScribbleVC! He's a triple threat (founder + operator + investor) with a stellar track record. But what makes him even more rare is that he's kind, humble, & a joy to talk to every single day. Big win for our team & our founders!

We are pumped to welcome @stuartdsmith to @ScribbleVC! This is great news for both our team & our founders. Stu is kind and humble, yet has backed some of the best founding teams on the planet. He's a triple-threat - a founder + operator + investor, and he brings that to bear for our founders as they build their companies and their networks. Finally, he's a wonderful person and teammate, and we look forward to every conversation, every meeting, every decision, and every team offsite with him. We are thrilled you joined us, @stuartdsmith!

"Have you really thought through your moat?" "Is speed really your only lead right now?" @elizabeth joins @glennsolomon @notablecap on hypergrowth lessons from the early days of Twitter & her early investments in Whatnot, Slack, Figma, + more.

today, we're introducing self diagnostics: the first ever way for agents to proactively self-report issues they encounter. welcome to the future of agent observability.