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50개정렬
1:30:54ENHumanoids Outran Usain Bolt. DeepMind Still Scores Robotics as GPT-2진행자 Nathan LabenzGoogle DeepMind's Gemini Robotics lead on why sprinting is easy, frying an egg is hard, and one brain should drive any body.
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.
2:06:11ENLindy Runs on DeepSeek. Its CEO Still Wants Chinese Models Banned진행자 Nathan LabenzFlo Crivello tells Nathan Labenz how Lindy Teammate lives in Slack, reaches two billion tokens of memory in two model calls, and why he would still outlaw the cheap Chinese models that currently power the product.
44:52ENAn 80GB Wikipedia Cache Versus a 100GB Model That Holds the InternetEngram’s founders argue that stuffing a company into the context window is the expensive kind of memory—and that baking it into the weights can cut token use by two orders of magnitude.
1:45:59EN87% of Workers Use AI. Only 13% Say the Company Got Better.진행자 Nathan LabenzGlean’s Work AI Index names the missing hours: botsitting, botshitting, and a hamster wheel of polished nonsense.
42:27ENEvery Company Can Operate at the Frontier — If It Owns the Evals진행자 Sarah Guo, Elad GilAt Microsoft Build, Satya Nadella tells No Priors and Latent Space why AI is an ecosystem game, why private evals beat public benchmarks, and why the Azure networking team now asks for tokens instead of headcount.
1:34:54ENSix Months, Eighty Percent Churn, Five Times the Tokens진행자 Nathan LabenzTasklet CEO Andrew Lee tells Cognitive Revolution how he rewrote the stack, why most lost users leave for Anthropic, and why he thinks only three kinds of software company survive.
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.
1:40:46ENGive an agent a thousand tools and it will pick the wrong blade진행자 Nathan LabenzComposio CTO Karan Vaidya on the tool harness that discovers, authenticates, sandboxes, and rewrites integrations so agents can do whole jobs without drowning in context.
2:06:23ENFive AI Employees Live on Five Mac Minis진행자 Nathan LabenzAfter selling her YC packaging company, Jesse Genet opened a terminal for the first time and built an OpenClaw staff that now plans lessons, logs learning, and keeps family evenings from sliding into slop.
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.
39:47ENThe Context at Step 14 Isn't in the CodeLangChain cofounder Harrison Chase on why long-horizon agents finally work—and why traces, harnesses, and first-draft workflows matter more than scaffolding.
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.
50:00ENCrosby Bills by the Document, Not the Hour, and Turns Contracts Around in Under an HourThe founders of an AI-native law firm explain why they became lawyers with engineers at the next desk instead of shipping legal software, and how deal velocity became the product.
1:02:54ENEnterprise Coding Tools Flipped the 80/20. Reflection AI Built the Other Half진행자 Sarah Guo, Elad GilFormer Gemini reward-model lead Misha Laskin on Asimov, why comprehension beats generation, and why there is no such thing as generalization—only pulling the test distribution into train.
1:42:06ENEvery Frontier Lab Is Spending a Billion a Year on Data. Here Is Where It Goes진행자 Nathan LabenzLabelbox CEO Manu Sharma on the $15 billion Scale deal, RL “gyms,” $250,000 trainers, and why post-training now eats the budget that used to belong to pre-training.
40:33ENFifty People in Slack. Four Minutes to the Smoking Gun.Traversal's co-founders on turning DevOps heart attacks into agent-run root cause analysis — and why observability's second-largest software spend still leaves troubleshooting as a whodunit.
1:24:27EN500 Trillion Tokens a Month: How Google Grew 50x in a Year진행자 Nathan LabenzLogan Kilpatrick returns to Cognitive Revolution to unpack Google's mid-2023 merger, why he expects frontier labs to diverge, and why startups still hold the speed advantage.
2:12:00ENGradient Descent at Test Time: Titans Pushes LLM Context to 10 Million Tokens진행자 Nathan LabenzA Cornell PhD student's neural memory module holds about 70% accuracy where GPT-4's scores fall off a cliff.
1:26:21ENFor under $10, Google's AI independently recovered a lab result nobody had published진행자 Nathan LabenzVivek Natarajan and Anil Palepu tell Nathan Labenz how AMIE beats primary-care doctors on treatment plans, and how Co-Scientist matched Imperial College's unpublished bacterial-resistance mechanism.
1:14:11ENThe Reasoning Curve Was Smooth All Along: Gemini 2.5's Jack Rae on Thinking, Memory, and AGI진행자 Nathan LabenzDeepMind's thinking-and-inference lead explains why RL-for-reasoning felt sudden, why Gemini shows raw chain of thought, and why a million-token window still is not memory.
2:14:59ENAlways Bet on the Models: How Shortwave's Andrew Lee Shipped Tasklet as Agents All the Way Down진행자 Nathan LabenzThe Firebase co-founder argues that workflow software is already obsolete, that MCP is optional, and that the only durable advantage left for an AI startup is speed.
38:43ENTwo in Five Doctors Want Out. An On-Call Cardiologist Built the Note That Lets Them Stay진행자 Sarah Guo, Elad GilAbridge CEO Shiv Rao on treating the doctor-patient conversation as healthcare's source of truth, and why the company ran straight at the hardest health systems.
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.
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