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1:10:12ENOutSystems Went From 4 Major Features a Quarter to 26. Token Spend Fell Anyway진행자 Nathan LabenzCEO Woodson Martin on software that never breaks, why most enterprise work does not need a frontier model, and how AI is finally shrinking the IT backlog.
0:29ENTheo’s Ultrafast Test: $600 of Usage for Two PR ReviewsTheo Browne · Ping LabsA short example illustrates how quickly token costs can rise when using Ultrafast for everyday review work.
21:29ENMistral Large 4 Preview: European Open Weights, Cyber Benchmarks and Setup FrictionMatthew Berman · Forward FutureMatthew Berman reviews the model’s reported specifications and benchmarks, then tests it in an agent coding workflow.
0:39ENFinding Nano Banana 2.1 in Google AI StudioMatthew Berman · Forward FutureMatthew Berman shows the model selector and generates a close-up portrait in a short October 2026 demonstration.
25:39ENPersonal AI Assistants in Practice: Briefs, Family Logistics, Email and BillsMatthew Berman · Forward FutureMatthew Berman describes how he connects assistants to everyday workflows and sets approval rules for consequential actions.
12:49ENAlex Mashrabov: Higgsfield agents that choose models and launch their own GPUsAlex Mashrabov · HiggsfieldAt OpenAI DevDay 2026, Higgsfield's CEO walks through why a continuous media experience needs an agent that picks models, scores its own output, and provisions GPUs — including a live 10-hour AI stream small teams can now ship.
13:12ENAlexandra Lato on Building Stack Overflow for Agents and Stack Internal with CodexAarti Bagul, Alexandra Lato · OpenAIStack Overflow’s VP of Product explains how a small team used Codex with opposite constraints on two products—and why agent-native design means letting agents contribute knowledge, not just read it.
28:17ENUltrafast Coding: A Live Design Loop With a Steep CostTheo Browne · Ping LabsTheo Browne explores how fast inference changes his workflow, and why he still advises against upgrading solely for Ultrafast.
1:04:26ENAt 100,000 Accelerators, Something Fails Every HourGoogle AI infrastructure chief Amin Vahdat tells Sequoia's Sonya Huang why FLOPS is a vanity metric, why the TPU line split in two, and why he would rather wait on a utility than build his own gigawatt.
56:31ENPost-Training Wins Inference: Why Owning the Weights Beats Betting on One Lab진행자 Jacob EffronApplied Compute CEO Yash Patil argues that control, private evals, and post-training on the biggest workloads matter more than fearing that frontier labs will turn malicious.
1:10:29ENHow Anthropic Used Claude to Improve App PerformanceTheo Browne · Ping LabsTheo Browne examines a two-week performance sprint, its measurement tools, human review and the tradeoffs behind faster interfaces.
1:11:14ENVenky Ganesan on AI Venture Investing, Ownership and the Cost of Missing Out게스트 Venky Ganesan · 진행자 Harry StebbingsMenlo Ventures' partner discusses seed bets, concentrated follow-ons, market cycles, investor liquidity and the discipline needed when AI valuations accelerate.
0:26ENA DeepSeek V4.1 Flash Portrait Painted Through a Browser ToolMatthew Berman · Forward FutureMatthew Berman compares a reference headshot with a stylized result made using a Paint-like website.
1:05:01ENChase Lochmiller on AI Data Centers, Energy and GPU Economics게스트 Chase Lochmiller · 진행자 Harry StebbingsCrusoe’s CEO discusses the constraints on AI infrastructure, the economics of GPU capacity and his company’s approach to energy and managed inference.
1:30:54ENHumanoids Outran Usain Bolt. DeepMind Still Scores Robotics as GPT-2진행자 Nathan LabenzGoogle DeepMind's Gemini Robotics lead on why sprinting is easy, frying an egg is hard, and one brain should drive any body.
35:39ENCompute Scaled a Millionfold. Bandwidth Only 40x. Fractile Wants to Fix That Ratio진행자 Sarah Guo, Elad GilIn the summer of 2022, Walter Goodwin founded Fractile in London to build very fast inference chips for the world's largest models.
1:06:36ENTheo’s Guide to Running Coding Agents in ParallelTheo Browne · T3Theo explains his approach to subscription usage, agent delegation, review and remote machines, while acknowledging that parts of his setup may violate provider rules.
1:20:28ENAI Valuations, Talent Wars and the Venture Capital Tradeoffs Behind Them게스트 Jack Altman, Jason Lemkin, Rory O’Driscoll · 진행자 Harry StebbingsHarry Stebbings, Jack Altman, Jason Lemkin and Rory O’Driscoll debate large early-stage bets, open-weight models and the changing market for exits.
1:06ENUsing Meta’s Muse for Meal Planning, Refunds and To-Do ListsMatthew Berman · Forward FutureMatthew Berman demonstrates four tasks for Meta’s personal AI agent, with user approval before selected actions.
38:10ENFrom deepfakes to DNA: how SynthID watermarks AIHannah Fry, Pushmeet Kohli, Jeremy Ratcliffe · Google DeepMindHannah Fry sits down with Pushmeet Kohli and Jeremy Ratcliffe to explain SynthID: a mathematical watermark now used on text, images and video, and being extended to protein sequences so DNA synthesis companies can tell AI-designed molecules from nature.
1:28:08ENThe same H100 costs 3x at AWS, and a four-month-old lab is catching genes the top sequencers missed진행자 Nathan LabenzA Cognitive Revolution weekly briefing on a possible U.S.–China AI hotline, why hyperscalers charge two to three times as much for identical chips, co-writing a novel with frontier models, and an AI loop that re-diagnosed a child a premier prenatal lab had cleared.
10:00ENOpenAI DevDay: Dots, Faster Inference, Codex and ChatGPT SpaceMatthew Berman · Forward FutureMatthew Berman reviews the event’s personal assistant, model, developer tooling and collaboration announcements.
30:58ENGPT-6.1 Sol: Cheap, Thorough at Code Review, but Uneven at Long BuildsTheo Browne · T3Theo compares early tests of GPT-6.1 Sol with competing models, from benchmark cost to real code reviews and a 3D game demo.
16:59ENClaude Sonnet 5.5 Tested: Games, 3D Scenes and a Lower-Cost Opus AlternativeMatthew Berman · Forward FutureMatthew Berman demonstrates generated projects and compares Sonnet’s reported benchmark scores and API prices with Opus.
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