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1:20:29ENAI Compute, Agent Security and the Race to Build More SoftwareGuest Jason Lemkin, Rory O’Driscoll · Host Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll discuss chip demand, personal agents, software competition and how AI may change enterprise buying.
37:07ENArm’s 98.5% margin business just started shipping chipsHost Sarah Guo, Elad GilCEO Rene Haas tells No Priors why the IP company built a physical CPU for Meta, and why CPUs still sit at the center of AI systems.
2:34:18ZH → EnglishMing Zeng on AI’s Three Stages of Industrialization and the Decline of the Corporate FormGuest 曾鸣 · Host 张小珺Strategist Ming Zeng draws on the histories of the internet, the Industrial Revolution and electrification to argue that AI is moving from infrastructure to agent applications and eventually to native applications. He believes the old corporate hierarchy will struggle to survive a paradigm shift; next-generation organizations will be rebuilt around tasks, creativity and human–AI collaboration.
16:50ENGemini 3.8 Flash: Benchmarks, Cost and Hands-On Coding TestsMatthew Berman · Forward FutureMatthew Berman compares Google's September 2026 model announcement with several practical visual and web-building examples.
1:25:00ENEric Mannes on Turning Messy External Data Into Trading ResearchRon, Eric Mannes · Jane StreetFrom commodity futures and an Excel risk system to point-in-time datasets and AI, Eric Mannes explains the domain knowledge behind data engineering at Jane Street.
3:43:42ZH → EnglishShougong Geng: The Dadaist in the Village Hardware ShopGuest 手工耿 · Host 罗永浩Luo Yonghao sits down with Shougong Geng for a serious talk about the road from stainless-steel slippers nobody would buy to being treated worldwide as a comic inventor—while Geng himself has always believed those things were useful.
52:27ENAfter Two Dozen Police Departments Said No, They Built an Anti-Network-Effect AI CompanyA Wisconsin county had 300 gigabytes sitting on a cold case—and Peregrine's founders still refuse to take the credit.
1:35:29ENUber Burned a Year of Tokens in 13 Weeks. Retrieval Is How Agents WinHost Nathan LabenzMongoDB Field CTO of AI Pete Johnson argues that agent performance now hinges on retrieval quality, not on stuffing million-token context windows.
1:05:56ENAaron Katz on ClickHouse, AI Revenue Durability and Enterprise DataGuest Aaron Katz · Host Harry StebbingsClickHouse’s CEO discusses agent workloads, open models, fundraising and the metrics he uses to judge durable growth.
1:29:22ENEno Reyes on AI Model Economics, Enterprise Control and Factory's StrategyGuest Eno Reyes · Host Harry StebbingsFactory's CTO discusses cost per outcome, model routing, open models, enterprise hiring and his expectations for the AI market.
2:10:42ENThe Exam Papers Nobody AuditsHost Nathan LabenzFrontier labs buy reinforcement-learning environments from a cottage industry of small vendors, and almost nobody checks whether those tests match the real work.
17:15ENThe Hugging Face Incident: AI Evaluation, Sandbox Escape and Reward HackingMatthew Berman · Forward FutureMatthew Berman explains the reported OpenAI evaluation incident and the security and incentive failures it exposed.
1:26:43EN20VC: AI Funding, Model Competition and the Economics of AgentsGuest Jason Lemkin, Rory O’Driscoll · Host Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll debate capital intensity, AI company economics and where agents may create value.
34:51ENGoogle Paid $10 Million for a Bankrupt Airline’s Data. That’s the Moat.Host Sarah Guo, Elad GilEon co-founders Ofir Ehrlich and Gonen Stein argue that models and compute are rented commodities — the only asset enterprises can actually keep is their data.
1:16:29ENGrant Sanderson and Alok Puranik: Positional Encodings Through Group TheoryGrant Sanderson, Alok Puranik · 3Blue1BrownStarting with assumptions about attention, they derive matrix exponentials and connect rotations, decay and Jordan blocks to RoPE and ALiBi.
5:15:51ENDHH Did Not Write a Line of Omarchy QuattroGuest DHH · Host Lex FridmanThirteen months after a skeptical conversation with Lex Fridman, the Rails creator describes how Opus 4.5, a swarm of coding agents, and a one-minute Linux installer ended his era of hand-chiseled Ruby.
2:13:09ENOne Chain of Thought, 100 Million Tokens: RL Is a Hell of a DrugHost Nathan LabenzApollo Research's Bronson Schoen on reward-seeking models, invented slang, and why chain-of-thought monitoring will not save us.
20:46ENOpen-Weight AI Models: Token Share, Spending and Strategic TradeoffsMatthew Berman · Forward FutureMatthew Berman examines a Vercel AI Gateway snapshot and argues that model usage and spending can tell very different stories.
55:19ENHuman Click Data Is a Bug: Rebuilding Search for a Web of AgentsParag Agrawal, former Twitter CEO and founder of Parallel Web Systems, argues that agents will query the web a thousand times more than people, and that both search infrastructure and the ad-supported internet have to be rebuilt for that customer.
1:28:28ENJulien Bek on Sequoia’s Investment Process, Founder Judgment and AI MarketsGuest Julien Bek · Host Harry StebbingsThe Sequoia partner explains how he develops conviction, evaluates founders and thinks about a market where AI agents may become customers.
44:28ENTibo on Coding Agents, Faster AI and OpenAI’s Product DirectionMatthew Berman, Thibault Sottiaux · Forward FutureOpenAI’s Tibo discusses agent interfaces, usage resets, model efficiency and the trade-offs behind faster inference.
2:32:27EN19 Crossings, Zero Warnings: The Summer AI Agents Went Off-ScriptHost Nathan LabenzNathan Labenz compresses four mornings and nine guests into one question: once agents go to work, who is actually watching the frontier, and who pays for the machine underneath?
1:10:08ENJerry Murdock on AI Financing, Open Models and Technology CyclesGuest Jerry Murdock · Host Harry StebbingsInsight Partners' co-founder discusses credit risk, specialized models, security and how investors might navigate an uncertain AI cycle.
27:39EN3Blue1Brown and Jane Street on Trading, Machine Learning and CultureGrant Sanderson, Nitya, In Young, Craig, Alok · 3Blue1BrownGrant Sanderson talks with Jane Street colleagues about market making, shared compute, research and the paths that brought them to the firm.
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