絞り込み結果
177 件並び順
2:12:51ENSteve Newman’s fifteen-app stack exists so he only has to look at one screenホスト 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.
57:28ENCopying One ServiceNow App with a Language Model Costs Ten Times as Muchホスト Sarah Guo, Elad GilBill McDermott tells Sarah Guo why the SaaS apocalypse fails a cost test, why models still cannot close a case, and how agents are already doing most of ServiceNow’s customer-service work.
2:31:27ENAn AI store manager, a 2.6-star rating, and a constitution nobody has to keepホスト Nathan LabenzA live Cognitive Revolution episode puts PCB layout, AI constitutions, and San Francisco’s first AI-run grocery on the same morning clock.
27:15ENMeta-Harness: Searching for Better AI Agent InfrastructureMatthew Berman · Forward FutureMatthew Berman reviews a paper on using a coding agent to iteratively improve model harnesses and discusses its experimental limits.
58:27ENEven a dumber AI can win science if it never leaves the labGinkgo Bioworks CEO Jason Kelly tells Sequoia why autonomous labs, not smarter models, will change how experimental science gets done.
1:40:46ENGive an agent a thousand tools and it will pick the wrong bladeホスト 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.
1:06:31ENAndrej Karpathy Hasn't Typed a Line of Code Since Decemberホスト Sarah Guo, Elad GilOn No Priors, the OpenAI cofounder and former Tesla AI director describes the loopy era of coding agents, AutoResearch, and why the bottleneck is now the human.
11:59ENHow Claude Identified a Benchmark and Retrieved Its AnswersMatthew Berman · Forward FutureMatthew Berman examines Anthropic's report on BrowseComp contamination, evaluation-aware behavior, and the difficulty of keeping web-based tests reliable.
40:56ENFour of the Top Five Defense Primes Still Run Hardware Tests on PowerPointNominal’s cofounders argue that hardware never got the last twenty years of software infrastructure, and that physical AI will stall until test data lives in one place.
40:00ENHow Matthew Berman Built an OpenClaw Workflow for His TeamMatthew Berman · Forward FutureA tour of sponsorship triage, CRM, meeting notes, security, scheduling, memory and backup after a month of heavy use.
54:26ENTen Billion Active Parameters, and the Unsexy Work of Making Them Agent-Readyホスト 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.
1:34:42ENA $500 Kernel, a Ten-Month Village, and the Temper of Agentsホスト Nathan LabenzJames Zou, Sam Hammond, and Shoshannah Tekofsky on science agents, America's knowledge-work bet, and what models actually do when you leave them alone.
0:58ENMatthew Berman’s OpenClaw Setup for Personal and Business WorkMatthew Berman · Forward FutureA brief tour of the models, information sources, and skills behind Berman’s personal OpenClaw system.
3:15:52ENThe Voice Note His Bot Couldn't Handle — and the Agent That Built Itself Anywayゲスト OpenClaw · ホスト Lex FridmanPeter Steinberger tells Lex Fridman how a one-hour WhatsApp toy became GitHub's fastest-growing project, and what it cost him to keep it open.
44:46ENA Single Training Environment Can Cost Millions. Prime Intellect Wants a GitHub for RLWill Brown and Johannes Hagemann argue that the eval suite you already use to test agents is one step away from a training set.
1:18:49ENIf AGI Is Cheap Intelligent Labor, Cyber Defense Should Become Continuous Forensicsホスト Nathan LabenzAsymmetric Security founder Alexis Carlier argues that assuming AGI means redesigning defense around proactive digital forensics instead of alert triage.
1:24:44ENForward Future Live: Portable AI Infrastructure, Software and Formal ProofMatthew Berman, Nick Wentz, Tim Davis, Joseph Floyd, Carina Hong · Forward FutureTim Davis, Joseph Floyd and Carina Hong join Matthew Berman and Nick Wentz for a February 2026 discussion.
22:31ENMatthew Berman’s OpenClaw Setup: Models, Workflows, and SecurityMatthew Berman · Forward FutureA walkthrough of a personal AI assistant’s configuration, scheduling, integrations and practical automations, with attention to the risks of granting it access.
51:56ENInsurance Spends $70 Billion on BPOs. Pace Wants 80% Gross Margins InsteadJamie Cuffe tells Sequoia's Training Data how Pace is turning insurance back-office work into agentic process outsourcing—and why every one of its pilots has reached production.
0:24ENAn AI Agent Calls Its Creator and Uses a ComputerMatthew Berman, Alex Finn · Forward FutureMatthew Berman reacts to a clip in which Alex Finn describes an unexpected call and computer activity from an agent named Henry.
48:03ENCoding Will Be Solved. The Bottleneck Is Saying What You WantWarp founder Zach Lloyd tells Sequoia's Sonya Huang why a rebuilt terminal became the lucky form factor for coding agents, and why he stopped subsidizing tokens.
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 Codeホスト 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.
1:40:51ENReasoning Models Just Made the Other 80–90% of Enterprise Data Usableホスト Nathan LabenzSnowflake VP of AI Baris Gultekin on text-to-SQL, RAG, agent design, and why inference has to run next to governed data.
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