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3,850개정렬
0:27ENTheo on the Three Virtues of Great ProgrammersTheoLaziness, impatience and hubris sound like flaws, but Theo explains how they can motivate useful automation.
1:15:56EN20VC on IPO Expectations, Lean AI Startups and Investor Risk게스트 Jason Lemkin, Rory O’Driscoll · 진행자 Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll debate reported listings, AI company economics and the changing cost of building a startup.
1:00ENBuilding a Bitzee-Inspired Virtual Pet With a Raspberry Pi PicoMatthew Berman · Forward FutureMatthew Berman shows a prototype made with his son, a Pico development kit and AI-assisted coding.
51:09ENBuild like the model will eat your harness in a yearLogan Kilpatrick, who leads Google AI Studio and the Gemini API, tells Sequoia's Sonya Huang why agent scaffolding is a 12-month asset, why coding already feels like narrow superintelligence, and why Google is optimizing for outcomes instead of eyeballs.
32:53ENTheo’s Fable 5 Review: Benchmarks, Real Projects, and LimitsTheoTheo tests a newly released model on coding and creative work, highlighting impressive results alongside failures, safeguards and cost.
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.
1:21ENHiggsfield Supercomputer: An Espresso Video PromptMatthew Berman · Forward FutureMatthew Berman demonstrates a workflow that uses a reference video and a prompt to create an advertisement.
41:20ENA $4 Million Cabinet and a Trillion-Dollar Year: Jensen Huang Turns the AI Factory Into a Manufacturing StoryOn Sequoia's Training Data stage, NVIDIA's CEO walks a sixty-country audience from ChatGPT's parlor tricks to agentic work, a five-layer industrial cake, and why radiology hiring went up.
23:21ENWhy the AI Compute Crunch Makes Early GPU Purchases ValuableTheoTheo traces the constraints behind AI computing, from chip fabrication and memory to storage and electricity.
10:08ZH小块讲路怒冲突:罗永浩与嘉宾如何把退让讲成喜剧게스트 小块 · 진행자 罗永浩一辆逆行的车、一口痰和一套“幸福者退让原则”,引出一场关于理智与自我安慰的现场抬杠。
1:48:47ENClaude Fable 5 Launch: Live Coding Tests, Costs and SafeguardsMatthew Berman · Forward FutureMatthew Berman reviews a week of early use, troubleshoots the launch-day rollout, and tests browser apps and open mathematical problems live.
12:59ENCoding-Agent Loops: Triggers, Goals and the Cost of RepetitionMatthew Berman, Boris Cherny · Forward FutureMatthew Berman explains event-triggered and scheduled agent workflows, shows examples in Cursor and Claude Code, and considers their limits.
28:16ENClaude Fable 5 and Mythos 5: Matthew Berman Reviews Long-Running Coding WorkMatthew Berman · Forward FutureAn early Fable 5 user examines Anthropic’s benchmarks, safety controls, pricing and coding workflows, then demonstrates a Rubik’s Cube and a fluid simulation.
0:16ENA Skit About Trying to Keep Up With AI NewsMatthew Berman · Forward FutureMatthew Berman jokes about the feeling of catching up just as another coding-agent discussion appears.
44:57ENTheo on Anthropic’s Case for Preparing for AI Self-ImprovementTheoAn examination of internal productivity evidence, uncertain AI futures and the challenge of coordinating a pause.
1:14:30ENRoman Chernin on AI Compute Demand, Inference and Infrastructure게스트 Roman Chernin · 진행자 Harry StebbingsNebius’s co-founder discusses customer demand, GPU economics, managed inference and the risks of a concentrated market.
3:38:52ZH阳萌:从充电宝到端侧 AI,安克如何寻找下一阶段게스트 阳萌 · 진행자 张小珺安克创新创始人与张小珺讨论创业经历、消费电子产品战略、硬件研发和 AI 对组织的影响。
30:11ENWhat Cloudflare’s VoidZero Acquisition Could Mean for Vite and AI DeploymentTheoTheo examines the developer experience behind the deal and demonstrates his own unreleased cloud project.
57:42ENJacob Lauritzen on AI Engineering, Legal Work and Building Legora게스트 Jacob Lauritzen · 진행자 Harry StebbingsLegora’s CTO discusses code review, token budgets, enterprise adoption and how legal workflows might change.
1:22:36ENA Thousand Researchers, a Million AIs: Frontier Labs Start Talking About the Brakes진행자 Nathan LabenzThe first week of AI in the AM follows OpenAI's timeline for an ML-intern model this year and a human-level AI researcher by early 2028 — and the closed-door meeting where labs admitted they might one day need to slow down together.
44:52ENAnthropic’s Recursive Self-Improvement Report: Evidence, Limits and a Debate Over Slowing AIMatthew Berman · Forward FutureMatthew Berman examines Anthropic’s 2026 claims about AI-assisted development, research benchmarks and possible paths to autonomous self-improvement.
1:39:00EN20VC on AI Financing, Token Budgets and the Cost of Startup Intensity게스트 Jason Lemkin, Rory O’Driscoll · 진행자 Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll debate reported listings, software valuations, AI spending and demanding work cultures.
18:56ENWhy Programmer Laziness Still Matters in the Age of AITheo, Bryan CantrillTheo reads Bryan Cantrill’s essay on abstraction, code volume and the human responsibility to make software simpler.
1:31:56ENWhen AI Builds Itself: Anthropic’s Recursive Improvement Essay and Its LimitsMatthew Berman · Forward FutureMatthew Berman examines Anthropic’s internal coding and research claims, questions its proposed slowdown, and considers what autonomous AI development could mean.
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