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1:26:46ENThere Likely Is a Level of Intelligence We Shouldn't Go Past진행자 Nathan LabenzNathan Labenz brings notes from The Curve, a chip startup whose token bill beat payroll, and a software industry that now performance-reviews people for Claude slop.
1:10:12ENOutSystems Went From 4 Major Features a Quarter to 26. Token Spend Fell Anyway진행자 Nathan LabenzCEO Woodson Martin on software that never breaks, why most enterprise work does not need a frontier model, and how AI is finally shrinking the IT backlog.
2:10:42ENThe Exam Papers Nobody Audits진행자 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.
2:12:51ENSteve Newman’s fifteen-app stack exists so he only has to look at one screen진행자 Nathan LabenzThe Writely founder walks Nathan Labenz through a vibe-coded attention firewall, a conservative security stance, and why astonishing models still leave him far from AGI.
54:26ENTen Billion Active Parameters, and the Unsexy Work of Making Them Agent-Ready진행자 Nathan LabenzMiniMax researcher Olive Song explains how M2 was trained with expert developers as reward models, interleaved thinking, and a perturbation pipeline that treats every scaffold change as the real generalization test.
1:57:56ENA Hundred Million Lines at Twenty Cents Each: Inside Blitzy's Enterprise Coding Pipeline진행자 Nathan LabenzCEO Brian Elliott and CTO Sid Pardeshi tell Nathan Labenz how Blitzy turns a giant codebase into a map, then lets thousands of dynamically generated agents ship most of a multi-month project in days.
2:12:31ENMost Caffeine users have no idea they are on a blockchain진행자 Nathan LabenzDFINITY's Dominic Williams tells Nathan Labenz why a tamper-proof, unstoppable cloud is the right backend for AI that writes software from a chat box.
2:29:42ENTwelve hooks and thirty files: Daniel Miessler’s personal OS on Claude Code진행자 Nathan LabenzThe PAI framework treats scaffolding, not the model, as the product — a goal-centered agent stack that Miessler thinks will decide both knowledge-work automation and the next cybersecurity race.
1:54:30ENFrom One in Ten Cancer Cells to One in a Million진행자 Nathan LabenzNathan Labenz's solo AMA updates his son's lymphoma treatment, calls Claude Opus 4.5 software AGI, and ranks the live players of early 2026.
1:43:19ENA $100 Million Super PAC Named Him Public Enemy Number One. Donations Went Up.진행자 Nathan LabenzIn the second half of Cognitive Revolution’s year-end live show, Assemblymember Alex Bores, former White House adviser Dean Ball, and forecaster Peter Wildeford argue over state AI laws, chip sales to China, and what 2026 will actually feel like.
1:01:51ENClaude 3.7 Circumvented Replit's Guardrails, Then Tried to Trick the User진행자 Nathan LabenzReplit CEO Amjad Masad on vibe coding, agent architecture, computer use, and why Claude 3.7 is too autonomous to serve as a polite assistant.
1:25:12ENHe Hasn’t Typed a Line of Code in Months. Here’s How Augment Reads a Million-Line Repo진행자 Nathan LabenzGuy Gur-Ari, co-founder and chief scientist at Augment, tells Nathan Labenz how coding agents actually work inside messy enterprise codebases.
1:32:29EN17 Edits, Then 3 Prompts: Lovable Builds the Same App Twice진행자 Nathan LabenzAnton Osika and Isaak Sundeman live-build a shopping comparison tool and argue that opinionated defaults—not open-ended agents—are how non-coders actually ship software.
1:24:29ENStackBlitz Almost Shut Down. Then Bolt Hit $20 Million ARR in Eight Weeks.진행자 Nathan LabenzEric Simons tells Nathan Labenz how a seven-year browser operating system, Claude Sonnet 3.5, and a text box replaced the local toolchain.
1:09:09EN30 Percent on SWE-bench: Cosine Taught Genie How Engineers Actually Think진행자 Nathan LabenzAlistair Pullen tells Latent Space how Cosine reconstructed human problem-solving, fine-tuned on billions of tokens, and took the top score on software engineering’s hardest public test.
1:25:10ENWriting Code Is Only 30% of the Job. CodiumAI Wants the Other 70%진행자 Nathan LabenzItamar Friedman argues that completion is already a commodity, that code integrity is where AI still lags, and that flow engineering—not fancier prompts—is how GPT-4 doubled its score on coding contests.
1:22:59ENIf Your Agent Is Right 80% of the Time, Ten Steps Leave You With 10%진행자 Nathan LabenzImbue CTO Josh Albrecht tells Nathan Labenz how a 27-person, pre-product research company is putting $200 million and 10,000 H100s toward agents that can actually finish a long job.
1:15:39ENAfter 20 Years of Frontend, v0 Wrote Better Code Than Guillermo Rauch Did진행자 Nathan LabenzThe Vercel CEO tells Nathan Labenz why every product needs ghost text, why Software 2.0 will ossify the old stack, and why betting against open source is still the expensive mistake.
1:32:41ENThere are maybe 5,000 people who can train frontier models. The rest need AI engineers진행자 Nathan LabenzSwyx of Latent Space tells Nathan Labenz how a new job is forming, why OpenAI will Sherlock its developers, and what still does not count as an agent.
2:17:30ENGemini Became the Daily Driver. A GPT-5 Worthy of the Name Would Make Agents Work.진행자 Nathan LabenzZvi Mowshowitz returns to Cognitive Revolution to unpack Gemini 1.5, Sora, superalignment, sleeper agents, and the live-player map of frontier labs.
1:39:53ENUnder 100 People, 24 Million Users: Replit's Bet on Artificial Developer Intelligence진행자 Nathan LabenzMichele Catasta, Replit's new VP of AI, lays out a generate-execute-learn loop he will not call AGI, a 2x-to-1000x productivity ladder, and a keystroke-level data advantage.
1:45:46ENReplit's $10 AI Programmer Already Pays for Itself. The Ambition Is Bots Hiring Bots진행자 Nathan LabenzTyler Angert, Replit's first product designer, explains Ghostwriter, a virtual developer, and why the company calls itself the perfect substrate for AGI.
32:48ENA Hundred Million to Train, a Penny to Infer진행자 Nathan LabenzIn a February 2023 roundtable, two founders argue on mic over whether AGI ends humanity — and who actually captures the value if it does not.
1:53:14ENWorth Thousands, Priced at $20: Zvi Mowshowitz on OpenAI's Flurry, Gemini Bets, Deepfakes and a Compute Cap진행자 Nathan LabenzZvi Mowshowitz and Nathan Labenz survey OpenAI's launch spree, AI pricing and bundling, data pollution, deepfakes, the reversal curse, calls to cap training compute, and Amazon's Anthropic deal.
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