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Matthew Berman· 9 jul 2026Two GPT-5.6 Coding Demos: A Block World and a SpreadsheetMatthew Berman · Forward FutureMatthew Berman shows a Minecraft-like game and an Excel-like application built with Codex and GPT-5.6.
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Theo - t3․gg· 8 jul 2026Theo on Guilt-Merging Pull Requests and Questioning CodeTheo Browne · Ping LabsA short reflection on why developers sometimes accept changes they do not think are right.
25:34ENMatthew Berman· 8 jul 2026Anthropic’s J-Space Research: What Its Experiments Reveal and What Remains UnknownMatthew Berman · Forward FutureMatthew Berman examines experiments on internal representations in Claude, from causal interventions to safety auditing and the limits of consciousness claims.
1:53ENMatthew Berman· 8 jul 2026What Anthropic’s J-Space Research Suggests About AI ReasoningMatthew Berman · Forward FutureMatthew Berman discusses internal model representations, interventions and the question of consciousness, while the research itself describes important limits.
28:11ENTheo - t3․gg· 7 jul 2026The Tradeoffs of Running Open-Weight AI Models LocallyTheo Browne · Ping LabsTheo Browne separates the value of open weights from the hardware, concurrency and cost constraints of local inference.
0:22ENTheo - t3․gg· 7 jul 2026Theo Asks Why Teams Need a Separate System for Environment FilesTheo Browne · Ping LabsA brief prompt to reconsider how development teams share environment configuration.
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Sequoia Capital· 7 jul 2026PódcastThe drone is 15% of Zipline: 140 million miles, zero incidentsKeller Rinaudo Cliffton and Eric Watson explain why the aircraft is the small part of an automated logistics system now cheaper than a car.
0:24ENMatthew Berman· 7 jul 2026Claude Fable 5 Access Extended Through July 12, 2026Matthew Berman · Forward FutureMatthew Berman reports a short extension for paid Claude subscribers, without a reset of their existing usage quota.
18:34ENMatthew Berman· 7 jul 2026Model Routing for AI Coding: A Worked Cost ExampleMatthew Berman · Forward FutureMatthew Berman separates planning, implementation and review to explain how different models can fit different tasks.
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Jane Street· 6 jul 2026Inside Jane Street’s Internship: Projects, Mentorship and LearningCody · Jane StreetInterns and employees describe collaborative interviews, learning finance from the basics, and working on projects used by the firm.
0:20ENTheo - t3․gg· 6 jul 2026Theo on Markdown Files as Instructions for Coding AgentsTheo Browne · Ping LabsA short observation about how agent tools can change the scale of a software idea.
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20VC with Harry Stebbings· 6 jul 2026Pódcast · 2 vocesMike Mignano on AI Applications, Open Models and Venture StrategyInvitado: Mike Mignano · Presenta: Harry StebbingsThe USV partner discusses AI agents, token spending and the opportunities and risks for startups building above the model layer.
43:15ENTheo - t3․gg· 6 jul 2026Theo’s Fable 5 Workflow: Model Routing, PR Review, and VerificationTheo Browne · Ping LabsA practical walkthrough of delegating tasks across models and turning a stalled backlog into reviewed work, with cost and deployment boundaries.
1:11:53EN20VC with Harry Stebbings· 4 jul 2026Pódcast · 2 vocesSierra Co-founder Clay Bavor on Open Models, Enterprise AI and Building TeamsInvitado: Clay Bavor · Presenta: Harry StebbingsBavor discusses model selection and compute costs, deploying AI agents for enterprises, and how Sierra approaches hiring and company culture.
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Cognitive Revolution "How AI Changes Everything"· 4 jul 2026Pódcast19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every ChipPresenta: Nathan LabenzRamin Hasani traces liquid neural networks from a worm's 300-cell brain to a 600-megabyte model that will talk from inside a Mercedes, and explains why architecture search now beats architecture avengers.
23:24ENTheo - t3․gg· 4 jul 2026Fable 5: Theo’s Take on Fallbacks, Subscription Limits, and CostTheo Browne · Ping LabsTheo Browne examines performance claims and shares the cost-saving workflow he used during a limited subscription window.
0:28ENTheo - t3․gg· 3 jul 2026Theo on the AI Bubble and the Value Beneath ItTheoTheo thinks AI is in a bubble, but says its underlying value remains an open question. He contrasts NFTs with the internet and its dot-com bust.
38:05ENTheo - t3․gg· 3 jul 2026Why Theo Moved His Agent Work to Linux MachinesTheoLong-running coding agents, laptop CPU load and slow small-file operations led Theo to build a networked fleet. He demonstrates SSH, a hardware KVM and T3 Code for remote work.
1:18:07EN20VC with Harry Stebbings· 2 jul 2026Pódcast · 3 voces20VC Roundtable: AI Spending, Model Competition and Software AcquisitionsInvitado: Jason Lemkin, Rory O’Driscoll · Presenta: Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll debate enterprise AI returns, prediction markets, SaaS roll-ups and the cost of raising capital.
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No Priors: AI, Machine Learning, Tech, & Startups· 2 jul 2026Pódcast · 2 vocesTwo Years and Four Months to a Live Reactor: Valar Atomics Wants Energy Ten Times CheaperPresenta: Sarah Guo, Elad GilIsaiah Taylor walks Sarah Guo through Ward 250 in Utah and argues that nuclear is a hardware-iteration problem, not a paper-design one.
1:29:02ENCognitive Revolution "How AI Changes Everything"· 1 jul 2026PódcastFrom 50 Designs a Day to 1,500: How AI Changed What Jaguar Land Rover Can ExplorePresenta: Nathan LabenzNeural Concept’s Thomas von Tschammer on specialist physics models, engineering copilots, and why Formula 1 already runs thousands of designs overnight.
28:37ENTheo - t3․gg· 1 jul 2026Theo Tests Sonnet 5 and Explains Fable’s ReturnTheoTheo compares model benchmarks and his own coding tests, finding promise in Sonnet’s subagent orchestration but questioning its task costs.
2:19ENTheo - t3․gg· 1 jul 2026Theo on Sonnet 5: Agent Orchestration and Token CostsTheoTheo welcomes Sonnet 5's ability to coordinate subagents while questioning its token efficiency. He also discusses the introductory pricing announced at release.
31:30ENTheo - t3․gg· 30 jun 2026Why Some AI Models Use Fewer Tokens to Solve a TaskTheoTheo explains input, output, caching and reasoning tokens, then explores a hypothesis about terse internal reasoning.Cargar másMostrando 24 de 3725