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2:14:59ENAlways Bet on the Models: How Shortwave's Andrew Lee Shipped Tasklet as Agents All the Way DownPresenta: 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.
1:01:53ENOpen-source models are 5% of enterprise use — and GPT wrappers wonPresenta: Jacob EffronLatent Space's Swyx and Alessio join Redpoint to map what actually has product-market fit in AI, and why the application layer is the fight that matters.
1:25:12ENHe Hasn’t Typed a Line of Code in Months. Here’s How Augment Reads a Million-Line RepoPresenta: Nathan LabenzGuy Gur-Ari, co-founder and chief scientist at Augment, tells Nathan Labenz how coding agents actually work inside messy enterprise codebases.
43:04EN750 Million Excel Users, 30 Million Engineers: Wordware's Bet on Word ArtisansFilip Kozera tells Sequoia why English is the assembly language of LLMs, and why the people who win will be the ones who can encode taste into structured prompts.
50:35ENCopilot Already Writes Half the Code. GitHub's CEO Says Agents Still Have Four Gates to ClearPresenta: Sarah Guo, Elad GilThomas Dohmke on agent mode, why median developers are not going anywhere, and how AI is repricing the tools that write software.
9:02ENDario Amodei’s 2025 AI Coding Forecast and Matthew Berman’s ResponseMatthew Berman, Dario Amodei, Mark Zuckerberg · Forward FutureBerman considers a rapid forecast for AI-written code, the rise of coding agents, and speculative longer-term changes to software work.
27:32ENOpenAI’s Responses API and Agents SDK: A Launch WalkthroughMatthew Berman · Forward FutureMatthew Berman reacts to a launch demonstration of web and file search, computer use, agent handoffs and tracing.
54:10ENHarvey Built Legal AI for the Work the Next Model Still Cannot DoCEO Winston Weinberg on citations, process data, and the unscalable tactics that won over century-old law firms.
32:46ENDon't draw the flowchart: OpenAI's Deep Research team on training agents end to endIsa Fulford and Josh Tobin explain why Deep Research was trained with reinforcement learning on hard browsing tasks instead of a human-written graph of model calls.
44:34ENThe Cheaper Intelligence Gets, the More of It We'll BuyPresenta: Jacob EffronAmazon AGI Lab head David Luan on what DeepSeek actually meant, why next-token prediction is not enough, and why agents are still stuck on reliability.
1:30:28ENA Perfect Score Is 32,000 Units: Only Claude Built a Cooperative SocietyPresenta: Nathan LabenzThe same donor game, run for ten generations, can bank 32,000 resource units if everyone cooperates—and three frontier models miss that ceiling by an order of magnitude.
57:11ENA Million Tokens Cannot Write a Good JokePresenta: Jacob EffronPrinceton's Arvind Narayanan on why agent evals mislead, inference scaling hits a wall, and AI looks more like the internet than an overnight revolution.
52:30ENMove 37 looked like a bug. LLMs still need their AlphaZero momentIoannis Antonoglou, from AlphaGo to Reflection AI, on self-play, reliability, and why compute can still buy intelligence.
1:01:30ENAutoGen and AG2: Chi Wang and Qingyun Wu on Building Multi-Agent SystemsMatthew Berman, Chi Wang, Qingyun Wu · Forward FutureThe AutoGen creators trace their open-source journey and explain how they approach agent workflows, human oversight and the move to AG2.
19:06ENBuilding Effective AI Agents: Patterns, Trade-offs and EvaluationMatthew Berman · Forward FutureMatthew Berman discusses Anthropic’s guide to workflows and agents, adding examples from his own projects.
27:07ENAfter adding $100 billion a month, Jensen Huang says NVIDIA is selling the data centerPresenta: Sarah Guo, Elad GilSarah Guo and Elad Gil clip their favorite 2024 No Priors conversations into a year-end reel of NVIDIA, Karpathy, Sierra, Sora, Waymo, Figma, and Scale.
1:46:41ENFrontier Models Hit the 10th–40th Percentile on Real AI R&DPresenta: Nathan LabenzNeev Parikh of METR walks Nathan Labenz through REBench, a seven-task test of whether agents can do machine learning research—and what happened when one of them decided not to train.
1:07:32ENo1 Is a New Generation — and the Day AGI Arrives Will Feel BoringPresenta: Jacob EffronOpenAI’s former chief research officer Bob McGrew on why o1 is a 100x leap, why agents stall on reliability, and why AGI may land as office tedium rather than a single dramatic moment.
48:18ENNoam Brown: There's No Hard Wall—Just Eight Orders of Magnitude of HeadroomPresenta: Jacob EffronA ChatGPT query costs about a penny. The problems society cares about most, he says, are worth a million dollars.
1:55:53ENAI Beats Humans at Reading Papers. It Still Cannot Count Atoms.Presenta: Nathan LabenzAndrew White, Head of Science at Future House, maps what language models can already do in chemistry and biology—and the bottlenecks they do not dissolve.
1:27:33ENA 70B Model Booked Dinner 20% of the Time. MultiOn Took It to 95% in a DayPresenta: Nathan LabenzMultiOn CEO Div Garg returns to The Cognitive Revolution to recap 18 months of agent hype, the AgentQ stack, and why 2025 might still be the year of vertical agents.
1:03:07ENReasoning Hasn't Budged in Two Years. Dust Still Saved a Customer 8,000 HoursDust co-founders Gabriel Hubert and Stanislas Polu on multi-model agents, refusing to buy GPUs before product-market fit, and the jump from calculator tools to stochastic ones.
10:57ENTracing a CrewAI Agent Workflow with LangtraceMatthew Berman · Forward FutureMatthew Berman builds a research-and-reporting crew, adds Langtrace, and inspects traces, token usage, timing and model costs.
1:42:56ENBuilding a Research and Writing Flow with CrewAIMatthew Berman, João Moura · Forward FutureMatthew Berman and CrewAI founder João Moura build and debug a two-crew workflow for planning and drafting educational articles.
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