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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 InfrastructureGast: Roman Chernin · Moderation: 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Gast: 阳萌 · Moderation: 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 LegoraGast: Jacob Lauritzen · Moderation: 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 BrakesModeration: 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 IntensityGast: Jason Lemkin, Rory O’Driscoll · Moderation: 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.
42:27ENEvery Company Can Operate at the Frontier — If It Owns the EvalsModeration: 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.
0:47ENCognition's AI Productivity Guarantee for DevinMatthew Berman · Forward FutureMatthew Berman discusses a 2026 enterprise offer that compares estimated engineering value with the cost of using Devin.
2:59:44ENTwo Endangered Languages Broke Transformers. Nested Learning Gave Models a Sleep Button.Moderation: Nathan LabenzGoogle researcher Ali Behrouz tells Nathan Labenz how stacking update frequencies — not just layers — and an offline sleep phase could give language models genuine continual learning.
20:29ENHow Prompts Become Technical Debt in AI CodingTheoTheo examines outdated agent instructions, model-specific behavior and the value of regularly auditing project guidance.
1:13:33ENA Trillion Tokens Later, the Concept Finally Lands: Łukasz Kaiser on What Transformers Still MissModeration: Jacob EffronThe Attention Is All You Need co-author tells Unsupervised Learning that transformers will probably keep winning — and that they still do not learn the way people do.
20:12ENAI, Jobs and the Gap Between Automation Hype and Business ValueMatthew Berman · Forward FutureMatthew Berman argues that adoption is slower and more complicated than feared, while discussing layoffs, AI costs and the work humans still do.
1:06ENRunning AI Agents in the Cloud Instead of on a LaptopMatthew Berman · Forward FutureMatthew Berman argues that cloud-hosted agents can keep working when a laptop sleeps or loses connectivity. The video is sponsored by DigitalOcean.
40:22ENBuilding Gets Easier Near AGI. Knowing What to Build Does Not.Listen Labs CEO Alfred Wahlforss on AI interview agents, a 30-million-person audience, and why transcripts beat credit-card data when you need to predict customers.
38:50ENCan AI Help Less Experienced Engineers Grow?TheoTheo discusses coding assistants, team coordination and the difference between learning with AI and blindly relaying its output.
0:53ENA Coding Benchmark Comparison Raises Questions About SWE-benchMatthew Berman · Forward FutureMatthew Berman contrasts a SWE-bench Pro chart with DeepSWE results and questions whether the first matches users' experience.
56:10ENReid Hoffman Pledged a Billion to Free DeepMind. Hassabis Never Played the CardModeration: Jacob EffronSebastian Mallaby's biography of Demis Hassabis, discussed with Jacob Effron, is a story of a founder who tried to stop the AI race and then became one of its central players.
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