"There is no Apple of healthcare. There is no Airbnb of healthcare." We believe every major consumer market has been rebuilt around the individual except healthcare. Congratulations to @thatch_ai on their $108M Series C to create a healthcare system people love. Thatch gives employees a health budget from their employer to buy whatever plan fits their life. We’re proud to triple down on our partnership with @chrisellisdc, Adam Stevenson, and the team. Watch Alex Tran in conversation with Chris and Adam. Chapters 00:00 — How a WWII Wage Freeze Built America's Healthcare System 05:35 — Losing Parents to Cancer and Starting Thatch 09:07 — Inside the Thatch Product 14:38 — Why the Hardest Healthcare Problems Are Fintech Problems 20:49 — AI That Calls Your Doctor to Confirm It's In Network 25:55 — Unbundling Healthcare From Employment 31:32 — Lessons From Switzerland and Singapore

UK finance teams have waited long enough. Ramp is now live in the UK. Sorry we’re late. ramp.com/uk

@generalcatalyst is tripling down on @cognition and thrilled to continue to back @ScottWu46, @russelljkaplan, @walden_yan, @stevenkplus1 and the team in the important pursuit of enterprise sovereignty. Devin is a critical piece of the AI stack with real commitment to help enterprises adopt AI with real ROI

Congratulations to @forus on its $150M Series C to build an AI network for medicine. Over a third of patients prescribed specialty treatments never get their first dose. Forus moves new drugs from development to the patients who need them, faster. We’re proud to triple down on our partnership with @sahirjaggi and the entire team. Revisit @chriswbischoff's full conversation with Sahir: piped.video/Vdi0fUekm_g

.@MistralAI is building open-weight frontier AI in Europe, for the world. We've backed @arthurmensch, Timothée Lacroix, and @GuillaumeLample since seed and are investing in their €3B Series D. With Mistral’s full stack, industries tackling the hardest problems of our time gain agency over their AI. Congratulations to the entire team.

Our short film started with one line: "I want to ride my bike on the moon." When it comes to the creative case for investing in space, imagination precedes ambition. What looks naive in scientific progress is remembered as inevitable, but only if someone funds the gap in between.

When @brycestrauss was in fourth grade, NASA made most of the technical decisions for the Juno mission. By 22, Strauss was on the team flying Juno to Jupiter. Now he's the cofounder of @Nominal_io, building the software toolkit for hardware problems. “The operation is just a really high-stakes test,” he says. In the latest installment of our Space series, Bryce shares why the physical world always gets the final word: generalcatalyst.com/stories/…

"If you're not tackling hard problems, why are you creating a startup?" @bernhardsson was told to use Kubernetes. Instead he built @modal's file system and container runtime from the ground up, tuned for the speed AI workloads demand. With Modal, containers boot in under a second, and workloads burst from zero to thousands of CPUs or GPUs in a few lines of code. Watch @max_rimpel in conversation with Erik. Chapters 00:00 — Learning to Code on a Mac Plus 04:38 — Building the Engine Behind Spotify’s Discover Weekly 09:17 — The Pandemic Project That Became Modal 10:14 — The 1 to 2 Year Rule for Picking Startup Problems 12:36 — Broke Until Stable Diffusion Hit 15:42 — Architecting a New Cloud for AI 17:41 — Agents Want the Same Things Developers Do

meet @mostik_ai! what happens when you put 12 PhDs in one room for four months? first place on the ARC-AGI leaderboard, which I can't say much about while the competition is still running. and this, which I can. everyone's arguing about whether open models will catch up to frontier models. we think it's the wrong question. here's the one we pose: why does a frontier model have to generate your answer at all, when the only thing you need from it is the reasoning? we do this by enabling models to communicate in latent space. through our protocol, hidden states pass straight from a frontier model into a small one running on your infrastructure -- no text between them, and neither model is fine-tuned. two models from different families, sharing reasoning, both left untouched. how do we know it works? we tested it on a setup where a 753B model reads the problem, and a 4B edge-class model writes the answer. with this approach, we get results 80% as accurate as the frontier model, but at 20x faster performance. we're committed to preventing frontier model lock-in and are already partnering with inference providers to accelerate open-weight adoption. we've done this between 15 of us, in four months, 12 PhDs and a Fields medalist, backed by @generalcatalyst WIRED has the first external account of the company and the work: wired.com/story/russian-star… full writeup, the setup, and all the numbers: mostik.ai/read-more

I didn’t think autonomy would get nationwide-scale this fast... but here we are 📷! Our work with @HUMAIN and @TareqAmin_ will bring thousands of trucks to KSA. But this is just the start – followed by robotaxis, ports, mining, construction, and more. The size, scale and scope is unprecedented! Letssss go! 🚀🚀🚀

It's been over 20 years since a human last beat a machine at chess. In cloud security, we're still putting humans against machines. Amit Megiddo co-founded Native to build security into the cloud since you can't fight AI without AI. Watch @CraneMcrane in conversation with Amit. Chapters 00:00 — Why Cloud Security Got Stuck 02:15 — Leaving AWS to Start Native 06:22 — Building the Founding Team 08:35 — Winning the First Customers 12:04 — AI Changes the Threat Landscape 15:14 — Deploying AI to Fight AI 19:32 — Earning Trust to Automate Security 24:13 — Securing Multi-Cloud Environments 35:09 — The Long-Term Vision for Native 47:58 — The Customer Explains the Problem Back

We're leading @transfyrai’s $25M seed as they come out of stealth to build the observability layer for science. Much of scientific knowledge lives in the hands and instincts of the person at the bench, and it's lost when they move on. @AnnaMarieWagner and @rwegrzyn saw this firsthand at Ginkgo Bioworks and the Advanced Research Projects Agency for Health (ARPA-H). Transfyr's physical AI captures that knowledge as it's made so scientists, models, and robots can build on it, accelerating scientific progress. Congratulations to Anna Marie, Renee, and the entire team.

Adoption of AI agents can only move at the speed of trust. We led @ArgaLabs' $10M seed as they enable teams to build that trust in testing. @PhillipLii and @akkkkiira created high-fidelity twins of the software that agents run on, so teams can watch their agent work before it is deployed to a customer.

In 2024, we made the unprecedented decision to acquire a hospital system. It was an opportunity to create a blueprint for healthcare transformation to make American healthcare proactive, accessible, and affordable. @SummaHealth and our Health Assurance Transformation Company (HATCo) revealed their technology transformation stack, partnering with some of our portfolio companies @aidocmed, Clarium, @CommureOs, @poweredbyfabric, @hippocraticai, @judihealth, @transcarent, and @versemedical. @percepta is serving as a transformation partner, unifying the tech stack into a seamless Al-native operating system. We believe the future of healthcare is health assurance with tech founders and health system leaders working together to reimagine healthcare in the US and beyond.

"When will agents surpass humans on the internet?" @haakamaujla co-founded @agentmail to give AI agents their own email inboxes. An email address is the first thing the internet asks anyone for, and its next billion users will need one. Watch @yuris in conversation with Haakam. Chapters 00:00 — Why AI Agents Need Their Own Email 02:38 — The Drop Shipping Dream That Became AgentMail 08:27 — A Reddit Post and the First Customer 16:53 — The OpenClaw Explosion 22:31 — Email Is the Paper Trail of the Internet 29:11 — Sign In With AgentMail 32:50 — Billions of Agents in 18 Months 40:56 — Where Trust on the Internet Begins

.@river_ai_inc has a new vision for personal AI. We co-led River’s $1.1B funding round because we believe in @ibab's ambition to build open-weight models that individuals can train and improve continuously. Watch @htaneja in conversation with Igor. Chapters 02:22 — Co-Founding xAI 04:36 — An AI Experience You Own 05:59 — Betting Early on Open Weights 07:47 — How Do You Make Money on Free Models? 09:25 — Why the US Needs Its Own Open Models 11:27 — Enterprises Want to Control Their AI 13:36 — What Is Continual Learning? 16:56 — An API That Updates the Weights 19:17 — A Personal AI for Everyone 20:46 — The 20-Minute Training Run