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1,571개정렬
20:46ENOpen-Weight AI Models: Token Share, Spending and Strategic TradeoffsMatthew Berman · Forward FutureMatthew Berman examines a Vercel AI Gateway snapshot and argues that model usage and spending can tell very different stories.
0:48ENMatthew Berman on Earning From Idle Mac Compute With DarkbloomMatthew Berman · Forward FutureA proposed network of Apple Silicon Macs could serve AI inference, but the earnings shown are projections that depend on hardware, availability and demand.
0:55ENAGI, Recursive Self-Improvement and SuperintelligenceMatthew Berman · Forward FutureMatthew Berman introduces three AI terms and explains his expectations about their possible progression.
0:36ENUsing a Grok Bot for Online ErrandsMatthew Berman · Forward FutureMatthew Berman describes using a bot to handle routine website tasks, including an Amazon return.
33:48ENIs Coding Solved? Theo Separates Code Generation from EngineeringTheo Browne · Ping LabsA Claude Code UI defect sparks a debate about what agents can implement and what it takes to verify and maintain good software.
2:32:27EN19 Crossings, Zero Warnings: The Summer AI Agents Went Off-Script진행자 Nathan LabenzNathan Labenz compresses four mornings and nine guests into one question: once agents go to work, who is actually watching the frontier, and who pays for the machine underneath?
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.
21:58ENHow Matthew Berman Uses Grok Bot for Email, Meetings and Everyday TasksMatthew Berman · Forward FutureA tour of connected bots covers practical routines, reported coding workflows and features the host has not yet tried.
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.
9:15ENSix Open-Source Projects for Local AI, Agents, and 3D DesignMatthew Berman · Forward FutureMatthew Berman tours tools for running and training models, giving agents new skills, coordinating work, browsing, and generating 3D meshes.
1:25:13ENA $500 Lamp Cut TB Transmission 90 Percent. Almost Nobody Buys One진행자 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 Banned진행자 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.
25:31ENGrok 4.6: Better Agent Benchmarks, With Tradeoffs in Speed and CostTheo Browne · t3.ggTheo Browne tests Grok 4.6 on design, games and real code, weighing reported benchmark gains against his experience of slower and costlier tasks.
1:07ENMatthew Berman on Relay: Routing Coding Work Across ModelsMatthew Berman · Forward FutureA short demonstration of a free coding skill that assigns planning, implementation and review to different models. Its cost comparison is one example, not a guarantee of savings or equivalent quality.
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.
18:17ENMCP’s Stateless Redesign: What Changed and Why Theo Is OptimisticTheo Browne · Ping LabsThe July 2026 MCP specification replaces protocol sessions with self-describing requests. Theo examines the benefits, examples, and the problem of migrating older clients and servers.
1:56:40ENThe Periodic Table Was Already in the Weights진행자 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.
13:58ENGoogle’s AI Leadership Changes and the Innovator’s DilemmaMatthew Berman · Forward FutureMatthew Berman considers Google’s research history, two leadership changes and an open-model strategy in August 2026.
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 Poison진행자 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.
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