Building the GitHub for RL Environments: Prime Intellect's Will Brown & Johannes Hagemann

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1. 

   24 Mar 2026 · 58 min

   How Autonomous Labs Will Transform Scientific Research: Ginkgo Bioworks’ Jason Kelly

   Jason Kelly founded Ginkgo Bioworks in 2008 with a simple but radical idea: DNA is code, and cells are programmable. Sixteen years later, AI is finally making that vision real in ways that could reshape science itself. Jason describes a landmark collaboration with OpenAI in which a reasoning model with access to a robotic lab beat the state of the art in biochemistry by 40% - not by being smarter than scientists, but by running experiments 24 hours a day and sharing data across a hundred parallel hypotheses simultaneously. He argues that the biggest inefficiency in science isn't…

2. 

   17 Mar 2026 · 44 min

   Greetings, Earthlings: Philip Johnston of Starcloud on Data Centers in Space

   Philip Johnston, founder and CEO of Starcloud, explains why space will become the primary location for AI compute infrastructure within the next decade. After witnessing SpaceX's massive manufacturing scale at Starbase, Philip realized that declining launch costs would make space-based data centers cheaper than terrestrial ones. He breaks down the physics of heat dissipation in vacuum, the economics of solar power without atmosphere, and why the marginal cost of space infrastructure decreases while Earth-based costs increase. Philip previews a future where close to a trillion dollars per…

3. 

   10 Mar 2026 · 41 min

   Physics Gets a Vote: Nominal Cofounders on Hardware Development in an AI World

   Nominal’s cofounders (Cameron McCord, Jason Hoch and Bryce Strauss) realized that the new age of reindustrialization requires a new approach to hardware engineering and testing that’s closer to how software is developed. They founded Nominal with the insight that while SpaceX, Tesla, and Anduril built proprietary internal platforms for hardware testing, the thousands of new hardware entrants can't afford to replicate that work. Nominal serves as the system of record for hardware testing, helping companies move from PDF-based workflows to modern data infrastructure that catalogs telemetry…

4. 

   6 Oct 2026 · 1 hr 4 min

   Google's AI Infrastructure Chief, Amin Vahdat, on the Physics & Economics of Frontier AI

   At 100,000-accelerator scale, something fails multiple times an hour, which is why Google's Chief Technologist for AI Infrastructure Amin Vahdat thinks FLOPS is a vanity metric. The metric that matters is what he calls goodput: the useful work a workload actually delivers through real failures. Amin walks through the calculus that split the TPU line into 8i and 8t for the first time, why the TPU's core primitives haven't changed since v1, and how Google and DeepMind co-design in the same rooms, intercepting chip architectures mid-flight before tape-out. He explains why long-horizon agents…

5. 

   15 Sep 2026 · 1 hr 5 min

   Box's Aaron Levie: On Reinventing Yourself in the AI Age and Enterprise Diffusion

   Starting a company is hard. Reinventing your company for AI as a public company with quarterly earnings results is even harder. Aaron Levie has pulled off the transition with Box and offers hard-won advice for founders. The cofounder and CEO of Box argues the value isn't only in the model; it's in the bridge from a model's raw capability to the actual workflow inside a bank, a law firm, or a pharma company. That's the case for the application layer, and Box is building it: an agent harness tuned so tightly to its own file system, permissions, and search that it beats handing the raw API to…

6. 

   1 Sep 2026 · 52 min

   Making Cities Awesome: Peregrine’s Nick Noone & Ben Rudolph

   Most public safety technology companies grow by collecting more data. Peregrine inverted the model: no sensors, no new data, a business built on connecting the data and information cities already own. Co-founders Nick Noone and Ben Rudolph received more than two dozen no's before San Pablo PD let them in the door in February 2018. Today, Peregrine powers law enforcement, emergency medical services, fire and rescue, and other services in more than 400 cities and communities globally. Nick and Ben explain their north star for data sovereignty, and discuss how Peregrine's philosophy and…

7. 

   25 Aug 2026 · 55 min

   Parallel’s Parag Agrawal: Building a New Web for AI Agents

   Parag Agrawal is making a bet that goes against two decades of web search: agents will query the web a thousand times more than humans ever have, and the infrastructure built around human clicks is wrong for them. The former Twitter CEO, now founder and CEO of Parallel Web Systems, explains why Parallel treats human click data as a bug and trains on agent feedback instead. He unpacks the counterintuitive choice to ship a search agent before a search engine, building an index incrementally, and how the new Turbo product cut agentic search to 200 milliseconds. But the problem Parag keeps…

8. 

   18 Aug 2026 · 54 min

   Rich Sutton and Khurram Javed: Why AI Models Stop Learning, and How to Start It Again

   Rich Sutton, who helped pioneer reinforcement learning and wrote the seminal AI essay The Bitter Lesson, has now cofounded Oak Lab with his former student Khurram Javed. Their goal: to build agents that continuously learn from their own experience rather than from us. Rich doesn't think he holds a radical view: "I'm not weird. The field is weird." He says all learning is continual, and the field is the one that needed a new name for it. Rich and Khurram argue synthetic data is "a big mistake." Their "big world hypothesis" is that the world is massively more complex than any agent or…

9. 

   4 Aug 2026 · 47 min

   Chai Discovery's Bitter Lesson: Drug Design Is Another Scaling Problem

   Most people treat biology as a bespoke, messy science. Josh Meier and Matt McPartlon, co-founders of Chai Discovery, treat it as an engineering problem. They make the case that drug design obeys the bitter lesson: scale data, models, and compute, and the model can learn what a hand-built pipeline simply couldn't capture. The results are concrete: Chai-2 pushed de novo antibody design from a sub 0.1% hit rate to 16%, turning a needle-in-a-haystack search into something more like designing a key to fit a lock. Josh argues, counterintuitively, that biology is more verifiable than code, and…

10. 

    29 Jul 2026 · 49 min

    Building the Automated AGI Lab: Core Automation's Jerry Tworek and Rohan Anil

    Jerry Tworek led reasoning at OpenAI, convinced that scaling reinforcement learning was the path to AGI. Rohan Anil co-led Gemini pre-training and built the Shampoo optimizer. Now they've teamed up at Core Automation on a contrarian premise: the transformer has carried us as far as it can, and the bottleneck to smarter systems is no longer scale — it's the architecture itself. The missing capability is continual learning, models that adapt at test time, which transformers can't do. In-context learning taps out fast (Codex needs compacting after ~20 minutes) and fine-tuning invites…

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