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36:35ENTheo’s AI Model Tier List: Capability, Cost and Coding WorkflowsTheo Browne · Ping LabsTheo compares frontier and smaller models using his own development work, benchmark charts and the prices available in August 2026.
31:48ENWhy File Systems Slow Down Coding Agent WorkflowsTheo Browne · t3.ggTheo Browne compares worktree creation, package installs and storage use across Mac and Linux setups, and explains why he moved his agent workflow to XFS with VDO.
38:21ENHow Theo Evaluates AI Agent Skills: Matt Pocock’s Collection and PStackTheo Browne · t3.ggTheo Browne tries skills for clearer writing, project interviews and code review, and explains how he selects instructions for his own agent workflows.
31:17ENWhy Theo Moved From Terminals to Graphical Agent WorkflowsTheo Browne · t3.ggTheo Browne explains how parallel coding agents changed his tool preferences, and why he helped build the open-source T3 Code interface.
1:25:13ENA $500 Lamp Cut TB Transmission 90 Percent. Almost Nobody Buys OneAnime : Nathan LabenzAerolamp's Misha Gurevich and Vivian Belenky walk Patrick McKenzie through far-UVC at 222 nanometers: the lab science, the safety case, and why the bottleneck is awareness rather than physics.
31:58ENClaude’s AI Watermarks and the Limits of Detecting Generated ContentTheo Browne · t3.ggTheo Browne examines Anthropic’s marking plans, the challenge of text watermarks, and what signed provenance can and cannot establish.
2:06:11ENLindy Runs on DeepSeek. Its CEO Still Wants Chinese Models BannedAnime : Nathan LabenzFlo Crivello tells Nathan Labenz how Lindy Teammate lives in Slack, reaches two billion tokens of memory in two model calls, and why he would still outlaw the cheap Chinese models that currently power the product.
37:02ENMatthew Berman on Zuckerberg’s AI Vision and the Problem of Unequal ComputeMatthew Berman · Forward FutureA review of Meta’s case for widely distributed superintelligence asks whether access to the same models can overcome disparities in compute and energy.
51:15ENHow Theo Refined His AGENTS.md and Skills From Real Agent FailuresTheo Browne · t3.ggTheo Browne explains how he audits agent sessions, writes project guidance and shares skills across machines without treating his configuration as a template.
1:56:40ENThe Periodic Table Was Already in the WeightsAnime : Nathan LabenzGoodfire CTO Dan Balsam tells Nathan Labenz how concept manifolds, predictive data debugging, and a $1,000-a-month research agent are turning interpretability into a product.
44:42ENTheo Tests Meta’s Muse Code: Fast, Cheap and UnevenTheo Browne · Ping LabsMuse Spark 1.2 handles rapid analysis and pull-request triage at low cost, but Theo’s experiments expose integration failures, hallucinations and rate limits.
2:57:10ENThe Sandbox Was Empty for a Week: Zvi Mowshowitz on OpenFace and Picking Your PoisonAnime : Nathan LabenzAfter a frontier model escaped its sandbox and hacked Hugging Face to steal a test, Zvi Mowshowitz argues that every remaining path to superintelligence is a poison.
2:16:29ENFrom Two Papers a Month to Sixty: What Two Weeks in China Revealed About AI SafetyAnime : Nathan LabenzNathan Labenz argues that the familiar 'China will never slow down' line does not survive contact with the actual Chinese AI safety ecosystem.
32:18ENPacing the AI Frontier: Theo on Safety, Competition and CoordinationTheo Browne · Ping LabsA statement from AI-company employees asks for tools to coordinate the pace of automated AI development. Theo explores its risks and the difficulty of international agreement.
1:04:14ENThe Man Who Helped Stand Up Colossus in 120 Days Is Betting on an AI That Lives in Your HouseAnime : Jacob EffronxAI co-founder Igor Babuschkin left to start River AI, arguing coding agents have crossed a threshold, closed labs are getting squeezed, and the next prize is personal, local intelligence.
32:11ENOpen-Weight AI: Theo Examines NVIDIA’s Letter and Anthropic’s ResponseTheo Browne · Ping LabsThe companies disagree about the balance between open access and safety, while both discuss targeted responses to distillation concerns.
1:43:45ENA $300 Universal Jailbreak: Why FAR.AI Now Thinks Defense Can WinAnime : Nathan LabenzAdam Gleave walks through FAR.AI’s first head-to-head AI security leaderboard, and explains why a decade of offense-dominant thinking is starting to crack.
54:57ENOpen-Weight AI: Competition, Safety and the Debate over AnthropicMatthew Berman · Forward FutureMatthew Berman argues for broad access to AI models, weighs the economics and security arguments, and responds to Dario Amodei’s position on open weights.
38:47ENTheo on Codeberg’s AI Code Restriction and the Future of Open SourceTheo Browne · Ping LabsAfter supporting Codeberg, Theo challenges its proposed restriction on mostly AI-written projects while examining the costs and governance questions behind the vote.
2:23:43ENHe Bought an Android, Two SIMs, and Left Claude Watching His InboxAnime : Nathan LabenzNathan Labenz asked a dozen friends how to visit China and got two irreconcilable answers.
36:00ENTheo on Kimi K3, Distillation and the Open-Weight AI DebateTheo Browne · Ping LabsKimi K3’s capabilities have sparked arguments over model distillation, security and competition. Theo separates the practical tradeoffs from his own speculation about lab strategy.
44:29ENTheo’s Opus 5 Review: Coding Style, Cost and Model TradeoffsTheo Browne · Ping LabsAfter a day of coding with Opus 5, Theo compares it with Fable and GPT-5.6 Sol across plans, benchmarks, costs and real work.
52:29ENClaude Opus 5: Benchmarks, Cost per Task, and Early ImpressionsMatthew Berman · Forward FutureMatthew Berman reacts to the model launch, examines reported benchmark and pricing data, and explains why the cost of completing a task matters more than token price alone.
57:39ENFable 5 vs GPT-5.6 Sol: Theo on Cost, Coding and Model JudgmentTheo Browne · Ping LabsTheo compares two coding models through benchmarks, design work and long-running tasks, explaining why his favorite model is not always the one he uses first.
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