Has a developer you know lost their peace? Is that developer you?

Sail Research (@sailresearchco) is building an inference platform for long-running agents. We're excited to share our $20M investment in Sail, as part of their $80M Seed & Series A round, alongside our friends at Kleiner, Sequoia, Theory, and several other fabulous co-investors. @neilmovva and @blintzbase are generational founders – highly technical, customer obsessed, and shipping fast. Agents will consume far more tokens than humans, and an inference engine for agents requires different design decisions at every layer of the stack – running across heterogeneous hardware, writing custom kernels, and pausing, resuming, and forking entire VMs, including open network connections. The result is better primitives for developers building long-running agents, higher throughout, and lower costs. I’ve gotten to know much of the founding team at Sail, and every member of the team could be a founder on their own. To capture the vibe of the team, we at @Redpoint spent a day at Sail’s offices filming a short documentary on the company’s mission. Neil and Samir are wildly articulate, so hear them in their own words, and reach out if you’d like to work at Sail!

Congratulations to @neilmovva, Samir Menon, and the @sailresearchco team on their $80M Seed & Series A round. We're excited to have invested in both the Seed and Series A alongside many fantastic co-investors. Today, agents run autonomously for hours, making thousands of decisions with no one in the loop. The industry needs an order-of-magnitude drop in cost per token, and Sail is rebuilding the inference stack from the silicon up to deliver it. Neil has spent his career at the hardware-software interface, from Tensor Cores at NVIDIA to the Neural Engine at Apple to leading GPU kernels at Together.ai. Samir's background spans applied cryptography and security, from cofounding Blyss to platform security work at Apple. Together, they've built a culture obsessed with efficiency, where every engineer owns their piece of the stack outright. In this video, they discuss why Sail bet on an order-of-magnitude drop in cost per token, why ownership is the trait they hire for, and why Renee Shah and Satish Dharmaraj backed them on day one. Congratulations again, we are honored to partner with this team! Watch below👇

It is not too late to _actually_ own your inference. Introducing: Modal Auto Endpoints.

Congratulations to Yotam Segev, Tamar Bar-Ilan, Yonatan Itai, and the entire @cyera_io team on raising a $600M Series G at a $12B valuation! Since 2024, they have quadrupled their valuation. When we first met Yotam, Tamar, and Yonatan in 2023, their conviction that trust would become the foundation of enterprise AI stood out to us. That conviction has only proven more prescient since over 68% of organizations cannot tell the difference between human activity and AI agent activity inside their own systems. Cyera's AI-native platform discovers and classifies data with high precision, which gives teams clear visibility into how their data is used, stored, and secured. This visibility provides the crucial trust layer enterprises need to accelerate AI adoption while knowing and controlling what AI can see and do. 🎉We're honored to partner with this team.

Introducing Athena: the industry coalition to protect open source software from AI attacks. Athena is operational today. More than two dozen members. It's processed 20,000 findings and generated 2,000 patches across 500 open source projects. Join us: chainguard.dev/athena

I sat down with @arimorcos and @_RobToews for our recurring AI vibe check. We got into the tenuous future of open source models, the latest in the lab wars and some really interesting future implications of the compute crunch. It's been far too long since we did one of these and I always have fun jamming with these two. This time we hit on: ▪️ Why near-frontier open weight AI may be disappearing ▪️ Will compute constraints push labs to suspend their own APIs ▪️ Frustrations around Fable ▪️ OpenAI’s future ▪️ Where we are with Recursive Self Improvement and its implications We also hit on Cursor/xAI, ASML competitors and a ton more. 0:00 Intro 1:40 Coding Agents Cross a Threshold 3:29 Is Open-Weight AI in Retreat? 7:37 Cost Crunch & Scaffolding 12:13 The "Apps Are Cooked" Debate 16:37 Sam Altman Under Scrutiny 19:44 Anthropic's Fable Backlash 23:24 How Big a Step Change Is Fable? 26:50 What's Going On at Google? 33:20 Could the APIs Go Away? 34:11 Breaking the Semiconductor Bottleneck 35:42 Beyond EUV: Atom & X-Ray Lithography 37:23 Implications of a Compute Shortage 40:20 Do Alt Chips Actually Help? 43:43 SpaceX, xAI & the Cursor Acquisition 48:50 How Close Are We to RSI? 52:21 Quickfire YouTube: youtu.be/W_iO8XxgD_I Spotify: bit.ly/4envbk8 Apple: bit.ly/4eoD4FT

Congrats to @mo_norouzi and the @ideogram_ai team on their new model: Ideogram 4.0! This is now the best open-weight image generation model.

I sat down with @lukaszkaiser to get into whether the architecture he helped invent is actually enough, and what's next in generalization, coding agents, RL and more. Lukasz co-authored "Attention Is All You Need," the paper that introduced the transformer and worked on reasoning models at OpenAI so he’s been a key part of major shifts in the field. We hit on: ▪️ The case for and against a new architecture coming after the transformer ▪️ What’s required for model generalization in the physical world ▪️ How much coding agents have improved his AI research productivity ▪️ The next domains for RL ▪️ Why Anthropic initially won coding ▪️ Future research directions he’s excited about 0:00 Intro 1:12 Transformers vs. Human Learning 8:37 How Do We Get Physical World Generalization? 10:52 What Comes After Transformers 13:59 How Much Have Agents Improved Lukasz's AI Research Productivity? 17:21 How Close Is an AI Research Intern? 26:06 RL Beyond Verifiable Tasks 35:38 App Companies: Build Models or Lean on Labs? 46:21 Multimodal Is Still Missing Something 49:46 OpenAI's Bet on Reasoning 55:26 The AI Coding Wars 59:26 Focus vs. Keeping Embers Burning 1:02:09 Open Source vs. Closed Source Gap 1:05:15 Quickfire YouTube: youtu.be/N1geOimmdDo Spotify: bit.ly/4foudX0 Apple: bit.ly/4uGUhkO

Welcome @dfkoz to Redpoint as Partner and Head of Founder Experience.  Redpoint has invested in FX for a decade. As a team, we aim to deliver concrete value to our founders that manifests in the two most important things to any growing business: people to power the business, and customers to drive revenue. A great team deserves a great leader. Dan is one of the first Platform leaders in venture, having spent a decade at FirstMark building out the network function and writing the original FX playbook that so many firms (Redpoint included) took inspiration from. He then spent the last couple of years building startup programs at Google. Now, Dan will lead our FX team to keep delivering concrete value to Redpoint founders. Beyond the resume, Dan’s low-ego and founder-first instincts align perfectly with the ethos of our team. With Dan, our ambitions only grow: to identify, back, and accelerate more founders of generational companies. Dan, we're so lucky to have you on our team. Welcome!!

.@scmallaby spent 30 hours with Demis Hassabis in the back of a British pub. I sat down with Sebastian to chat about his recent book, The Infinity Machine, where he provides a fascinating history of DeepMind, Demis and the broader AI landscape. We hit on: ▪️ Whether the race between labs was inevitable ▪️ Project Mario: the secret plan to spin DeepMind out of Google ▪️ Why Google missed scaling the transformer despite inventing it and wasn’t first to ChatGPT and Claude Code ▪️ The personal history between Demis, Elon and Sam ▪️ The quasi-spiritual conviction Sebastian didn't expect to find underneath the science 0:00 Intro 2:04 Was the AI Race Inevitable? 4:03 The 2015 Safety Summit Backfire 11:27 Why Google Doesn't Make As Concentrated Bets 15:51 Project Mario: The Secret Spinout Plan 19:43 What Demis Actually Regrets 23:46 Venture Startups vs. Tech Behemoths 34:08 David Silver and the RL True Believers 38:21 Demis, Elon, and the Evil Genius Feud 42:39 Great Man Theory vs. Inevitability 45:00 What Demis Didn't Want Published YouTube: youtu.be/WC_embCiwgU Spotify: bit.ly/4wRqvLE Apple: bit.ly/4dDnnvq

Garner Health is one of the fastest growing and under-the-radar companies in tech. On the heels of their Series E, @nikillinit and I talked with @nickpreber to dig into how @getgarner reached this scale and what comes next. We’ve had the privilege of working closely with Nick for five years now and I think you’ll see in this conversation what makes him such a special entrepreneur. He’s had a consistently clear vision for improving US healthcare and relentlessly executed to do so. He’s incredibly thoughtful about how AI and data can be effectively used and we got into a lot of details around Garner’s approach to both. Full episode below: YouTube: youtu.be/I92TlMES_TY Spotify: bit.ly/3Ry7EVW

We're honored to continue our partnership with Nick Reber and the @garnerhealth team as they close their $100M Series E. One of the most important decisions in healthcare is which doctor you see, but patients have rarely had reliable information about who actually delivers the best outcomes. Garner is changing that. Having partnered with Nick and the team for years, we've had a front-row seat to how he operates with relentless focus on providing better care for employees, lower costs for employers, and a clear signal for the doctors who deliver the best outcomes. We're thrilled to keep backing the Garner team as they bring better care to millions more 🎉

We're honored to deepen our partnership with @modal and co-lead their $355M Series C! When @bernhardsson and @akshat_b started Modal in 2021, they had conviction that building a truly great cloud for AI meant rebuilding the entire stack from the ground up. Five years later, that bet has paid off. Erik built the recommendation system behind Discover Weekly at Spotify. Akshat was an early engineer at Scale AI before joining Erik as co-founder and CTO. Together, they've assembled what one engineer affectionately calls "a monastery for super nerds" and it shows in the product. Modal has become the high-performance cloud that serious AI teams reach for when they need to ship. We couldn't be more excited to continue backing them. Huge congratulations to Erik, Akshat, and the entire Modal team!

“LLMs are intrinsically unsafe.” @ylecun argues that models that can’t predict the consequences of their actions can’t be made reliable.

Fun interview with Jacob Effron on the Unsupervised Learning podcast.

It’s hard to imagine more of a dream Unsupervised Learning guest than @ylecun. Yann is one of the godfathers of AI, and he has some fascinating contrarian views on the limitations of LLMs. It was incredible to get to have a wide-ranging discussion with Yann about these views, reflections on his time at Meta and departure and what’s next for him. We hit on: ▪️ LLM limitations and a path forward for robotics ▪️ Why he left Meta ▪️ How he came to so dramatically disagree with his Turing co-laureates Geoff Hinton and Yoshua Bengio on LLMs ▪️ His predictions for 2027 ▪️ His new company AMI and the bet on world models ▪️ Why he compares OpenAI and Anthropic to Sun Microsystems ▪️ Why he tells PhD students to stop working on LLMs Plus some sharp views on the current safety discourse, how breakthrough research actually happens and what FAIR got right and wrong. YouTube: youtu.be/ngBraLDqzdI Spotify: bit.ly/4dL8fvT Apple: bit.ly/4wxgpiX