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7:14ENAWS AgentCore Adds Policy Controls, Evaluations and Episodic MemoryMatthew Berman · Forward FutureMatthew Berman examines AWS’s December 2025 agent-platform announcements and the enterprise problems they aim to address.
42:06ENAfter SWE-bench Hits 80.9%, Dianne Na Penn Reckons with Opus 4.5Presenta: Jacob EffronAnthropic’s head of product for research on computer use, deceptive token prices, thin harnesses, and why alignment makes a model a better thinker.
7:49ENDeepSeek V3.2: Reasoning, Sparse Attention and Agent TrainingMatthew Berman · Forward FutureMatthew Berman examines DeepSeek’s December 2025 model release, its benchmark results and the techniques used to improve long-context efficiency and tool use.
50:08EN1Mind's AI Superhuman Now Sources 76% of the PipelinePresenta: Nathan LabenzAmanda Kahlow tells Zapier CEO Wade Foster why she tore up the sales org — and why a face on an agent is mostly a trick to get buyers talking.
1:37:25ENFin Climbed From 35% to 65% Resolution. Intercom Says the Models Only Did a Few PointsPresenta: Nathan LabenzEoghan McCabe and Fergal Reid on production A/B tests, 99-cent outcome pricing, and why GPT-4 was already smart enough for most customer service.
15:29ENBuilding a Multi-Agent Research Team with Strands AgentsMatthew Berman · Forward FutureMatthew Berman builds from a calculator agent to a multi-agent business-report demo, with examples of tools, model selection and orchestration.
1:48:49EN$500, 2,000 Steps, and a Vending Machine: Grok 4 Profited, Claude Called the FBIPresenta: Nathan LabenzAndon Labs put frontier models in charge of simulated and real vending machines to see what breaks when nobody is in the loop.
24:25ENBuilding a Sleep Tracker With Pythagora 2.0Matthew Berman · Forward FutureMatthew Berman demonstrates an AI-assisted development workflow, from an editable specification to testing and debugging a sleep-tracking prototype.
38:48ENTask Length Doubles Every Few Months. Nathan Labenz Still Wants Humans in ChargePresenta: Nathan LabenzAt Imagine AI Live, the Cognitive Revolution host maps structured AI agents against autonomous agentic systems—and tells businesses to keep final control.
18:13ENDarwin Gödel Machine: How a Coding Agent Tests Changes to Its Own SoftwareMatthew Berman · Forward FutureMatthew Berman explains Sakana AI’s evolutionary search over agent code, its benchmark results and the limits of claims about recursive self-improvement.
1:01:51ENClaude 3.7 Circumvented Replit's Guardrails, Then Tried to Trick the UserPresenta: Nathan LabenzReplit CEO Amjad Masad on vibe coding, agent architecture, computer use, and why Claude 3.7 is too autonomous to serve as a polite assistant.
57:31ENThe New Ruler for Models Is How Long They Can WorkPresenta: Jacob EffronOn Claude 4's launch day, Anthropic researcher Sholto Douglas argued that the next phase of AI is less about harder puzzles and more about hours of unsupervised work.
47:00ENAn Eval Lasts Three Months — and a Frozen Frontier Would Still Feed Startups for a DecadePresenta: Jacob EffronOpenAI’s GPT-4.1 post-training lead Michelle Pokrass tells Unsupervised Learning how the team spent three months on evals before training, why agents fail on wiring more than intelligence, and when to reach for RFT.
14:04ENQwen3: Open Weights, Adjustable Reasoning and Tool UseMatthew Berman · Forward FutureMatthew Berman reviews the April 2025 Qwen3 family, its benchmark claims, training pipeline and local demonstration.
19:06ENSleep-Time Compute: Preparing AI Context Before a QuestionMatthew Berman · Forward FutureMatthew Berman reviews a 2025 paper on moving some reasoning ahead of a user query, and explains where its experiments found benefits and limits.
1:26:21ENFor under $10, Google's AI independently recovered a lab result nobody had publishedPresenta: Nathan LabenzVivek Natarajan and Anil Palepu tell Nathan Labenz how AMIE beats primary-care doctors on treatment plans, and how Co-Scientist matched Imperial College's unpublished bacterial-resistance mechanism.
23:50ENPaperBench: How AI Agents Attempt to Replicate Machine-Learning ResearchMatthew Berman · Forward FutureMatthew Berman examines OpenAI’s research-replication benchmark, its partial-credit scoring and the prospect of faster AI research.
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.
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.
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.
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