筛选结果
25 篇排序
1:26:46ENThere Likely Is a Level of Intelligence We Shouldn't Go Past主持 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 Anyway主持 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 Audits主持 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 screen主持 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-Ready主持 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 Pipeline主持 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 blockchain主持 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 Code主持 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 Million主持 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.
1:43:19EN → 简体中文1 亿美元超级 PAC 把他列为头号公敌,捐款反而增加了主持 Nathan Labenz在《Cognitive Revolution》年终直播的后半场,纽约州众议员 Alex Bores、前白宫顾问 Dean Ball 和预测员 Peter Wildeford 就州级 AI 法律、对华芯片销售,以及 2026 年究竟会是什么样子展开争论。
1:01:51ENClaude 3.7 Circumvented Replit's Guardrails, Then Tried to Trick the User主持 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 Repo主持 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 Twice主持 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.主持 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 Think主持 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%主持 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%主持 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 Did主持 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 engineers主持 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.
2:17:30EN → 简体中文Gemini 成了日常主力;名副其实的 GPT-5 才能让智能体真正跑起来主持 Nathan LabenzZvi Mowshowitz 再次做客 Cognitive Revolution,聊 Gemini 1.5、Sora、超级对齐(superalignment)、潜伏代理(sleeper agent),以及前沿实验室的实时格局。
1:39:53ENUnder 100 People, 24 Million Users: Replit's Bet on Artificial Developer Intelligence主持 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 Bots主持 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 Infer主持 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 Cap主持 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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