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1:43:45ENA $300 Universal Jailbreak: Why FAR.AI Now Thinks Defense Can WinModeration: 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.
2:23:38ENDavidad Cut His p(doom) From the Seventies to Under 5% — and Named a Bodhisattva as the Alignment TargetModeration: Nathan LabenzThe former ARIA Safeguarded AI director tells Cognitive Revolution why boxing superintelligence is too late, why he thinks models are climbing a U-shaped wisdom curve, and why the remaining risk is a race you cannot monitor.
36:00ENGPT-5.6 Reviewed: Strengths, Costs, and Coding-Agent TradeoffsTheo Browne · Ping LabsTheo Browne assesses Sol, Terra and Luna through benchmark results and hands-on coding experience.
2:06:41ENZero the J-Space and a Model's Hidden Goal Lights Up on Token OneModeration: Nathan LabenzA weekly Cognitive Revolution cut of Anthropic's global-workspace paper, AI superforecasters, open video world models, and a chip that treats inference as data movement.
24:43ENGrok 4.5 for Coding: Theo’s Benchmarks and Early ExperienceTheo Browne · Ping LabsTheo Browne examines Grok 4.5’s cost, benchmark caveats, coding work and 3D experiments after early access in Cursor.
23:24ENFable 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.
36:19ENThe Benchmark Grid Is Broken: Why Test-Time Compute Has Outrun How We Score ModelsModeration: Sarah Guo, Elad GilOpenAI researcher Noam Brown argues that static leaderboards hide how long a model is allowed to think — and that safety evals, research taste, and the release cycle have not caught up.
2:14:33ENA 90-Minute Ultimatum, an Emoji Wall, and a Rule: Don't Fight WashingtonModeration: Nathan LabenzZvi Mowshowitz reads Fable's system card, then Nathan Labenz stress-tests the export-control fight against lawyers, safety researchers, and builders who did not pause.
16:11ENSeven AI Coding Agent Loops and When to Use ThemMatthew Berman · Forward FutureMatthew Berman explains how triggers, goals and repeatable checks can turn coding tasks into agent workflows, with examples for performance, documentation and product quality.
38:45ENThe 25-agent town that became a Fortune 500 decision sandboxOn the day before Valentine's Day in a Stanford simulation, cafe owner Isabella decided to throw a party — no human wrote the plot.
1:44:28ENFable launch week: a model that refuses, a two-year alignment clock, and a Twitter account handed overModeration: Nathan LabenzNathan Labenz’s AI in the AM highlights reel from June 2026 covers Anthropic’s new frontier model, the founding of Sequent, and a week that settled one argument: AI is not slowing down.
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.
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.
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.
32:30ENTheo Reviews DeepSWE and the Limits of Coding BenchmarksTheoAn investor in DataCurve examines its coding benchmark, the results shown in the video and their limitations.
2:22ENPioneer Agent and Automated Fine-Tuning of Small ModelsMatthew Berman · Forward FutureIn a Fastino-sponsored video, Matthew Berman describes a system that automates parts of model adaptation and discusses its reported benchmark results.
2:34:17ENMatthew Berman Tests Claude Opus 4.8 and Dynamic Workflows LiveMatthew Berman · Forward FutureA launch-day walkthrough compares Anthropic’s reported benchmarks with informal coding experiments and a multi-agent website redesign.
17:03ENDeepSWE: Testing Coding Agents on Longer Software TasksMatthew Berman · Forward FutureMatthew Berman reviews Datacurve’s benchmark, its verifier audit and the tradeoffs of comparing models under a shared harness.
37:30ENCursor Composer 2.5: Speed, Coding Benchmarks, and the Limits of EvaluationTheo Browne · T3Theo examines Cursor’s coding model, its training methods, practical performance, and the difficulty of independent testing.
41:45ENAI Cyberattacks and Defenses: What Recent Security Incidents ShowMatthew Berman · Forward FutureMatthew Berman examines supply-chain attacks, AI-assisted vulnerability research and the economics of defending software as models improve.
1:23:53ENCreators Cheer Filler-Word Removal and Boo Generative VideoModeration: Nathan LabenzDescript CEO Laura Burkhauser maps the same customers' three-speed reaction to AI: deterministic buttons they love, an agentic co-editor they want but scold, and generative video they actively hate.
39:48EN400,000 Customers, 20,000 APIs: SAP's CTO on the Hard Exam of Enterprise AIModeration: Sarah Guo, Elad GilPhilipp Herzig tells No Priors how SAP is rebuilding the company operating system for AI, and why scale, evals, and pricing will decide who wins.
3:10:49ENCrunch Time: Ajeya Cotra's Playbook for the Months Before SuperintelligenceModeration: Nathan LabenzA conversation on recursive self-improvement, public warning systems, and using each generation of AI to align and control the next.
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