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23:22ENNoyan Tokgozoglu: How Optiver Builds an AI Platform for Fast, Measurable DecisionsNoyan Tokgozoglu · OptiverThe trading firm’s AI engineering lead explains same-day model adoption, on-premises infrastructure, cost controls and the limits of replaying agent evaluations.
34:21ENMatthew Berman Examines Anthropic’s IPO Filing, AI Growth and GovernanceMatthew Berman, Sam Altman · Forward FutureThe presenter reviews the S-1’s financial metrics, compute strategy and voting structure while questioning the tension between rapid AI development and safety.
36:07ENTheo on Token Costs, Coding Agents, and the Price of AI CapabilityTheo Browne · Ping LabsA viral estimate of Lauren's AI spending prompts a closer look at cache pricing, benchmarks, and the changing work of coding agents.
1:11:27ENCliff Sosin: What Remains Valuable When AI Intelligence Gets CheapInvitado: Cliff Sosin · Presenta: Patrick O'ShaughnessyThe investor explores the limits of prediction, the economics of AI infrastructure and the assets that may complement abundant intelligence.
16:38ENAiden Sochowski: Securing 300 Agents in a 60-Person CompanyAiden Sochowski · RunlayerRunlayer’s founding engineer explains what session monitoring revealed about agent permissions, prompt injection, tool errors and runaway cost.
55:06ENAnthropic's S-1: Revenue, Compute Costs and the Race to ScaleThe SemiAnalysis panel examines Anthropic’s filing, from improving compute economics to customer concentration and competition.
20:55ENJesse Hall: Build Voice Agents for Conversations, Not LeaderboardsJesse Hall · LiveKitLiveKit’s Jesse Hall explains how to evaluate voice agents as real-time systems: understand callers, handle interruptions, keep talking while tools run, and measure the delay people actually hear.
18:27ENDaksh Gupta on Building a Better AI Code Review AgentDaksh Gupta · GreptileGreptile co-founder Daksh Gupta explains why a webhook plus a coding agent is not enough for reliable pull-request review—and how targeted prompts, incident data, model inversion, codebase context, browser testing, and task-specific model routing can help.
23:48ENSatya Nadella on Zero Trust for AI and Why Every Company Should Own Its IntelligenceInvitado: Satya Nadella · Presenta: Harry StebbingsThe Microsoft CEO argues that capable agents need security boundaries even as alignment research remains unsettled, and explains why firms should retain the value created by their own AI use.
1:50:48ENWhy Inference Matters 12× More Than TrainingFrançois Chaubard, Dan Fu, Jeff Morgan, Joe Fioti, Liangsheng Yin · Y CombinatorYC Paper Club walks the inference stack from an API request down to GPU kernels. Four talks from Together AI, Ollama, Luminal, and SGLang argue that serving quality, not just training FLOPs, is where most of the compute and the money now sit.
25:50ENKimi K3.1 Pro Tested: Strong 3D Demos, Uneven Results and Competitive PricingMatthew Berman · Forward FutureMatthew Berman tests the open-weight model on coding, 3D rendering and visual explanations, then compares benchmark results and prices.
32:20ENWho Is Local AI For? The Costs, Trade-offs and a Hybrid FutureMatthew Berman · Forward FutureMatthew Berman weighs data control and independence against hardware cost, setup complexity and inference speed.
1:09:00ENDwarkesh Patel: What will computer chips look like in 2045?Invitado: Chris Auth, Kevin Fischer, Jack Kavalieros, Tyler Osborn, Pushkar Ranade, Gary Dickerson, Peter Wennink, Elon Musk · Presenta: Dwarkesh PatelAfter two days inside Intel’s most advanced fab, Dwarkesh Patel walks through gate-all-around, backside power, High-NA EUV, ruthenium, CFET, and hybrid bonding — and asks Intel’s leadership how the industry can possibly meet AI’s 3×-a-year compute demand when the world’s chipmaking tools cannot.
59:41EN20VC: Venture Fund Size, AI Valuations and the Changing Software MarketInvitado: Jason Lemkin, Rory O’Driscoll · Presenta: Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O'Driscoll debate venture concentration, infrastructure risk, code review and the assumptions behind fast-growing AI companies.
1:25:33ENWhy GPU Capacity Comes in Three-Year Rectangles — Erik Bernhardsson, ModalInvitado: Erik Bernhardsson · Presenta: Vibhu SapraModal’s CEO tells Latent Space why AI demand almost never looks like a three-year GPU contract, how the company pools compute across thousands of customers, and why sandboxes grew from a product they almost killed into a third of revenue.
17:42ENIs a Faster Model Actually Faster? Measure the Finished Job, Not the TokensMorgan Suo · MiniMaxMiniMax's Morgan Suo takes the engineering changes inside M3.1 Flash one by one and asks the question that matters to users: does the job an analyst needs actually get done sooner, cheaper and correctly?
1:17:09EN20VC on Pro Rata Rights, AI Pricing and the Changing Software MarketInvitado: Jason Lemkin, Rory O’Driscoll · Presenta: Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll debate investor rights, model economics and the choices facing software companies and their employees.
38:30ENTheo Tests Gemini 4 Argon: Design Strengths and Code-Review ConcernsTheo Browne · Ping LabsA strong result on a narrow skateboarding benchmark contrasts with poor findings in Theo’s own codebase audits.
10:36ENMeta Muse Wonder Tested: Strong Benchmarks, Mixed Demos and Quota FrictionMatthew Berman · Forward FutureMatthew Berman tests Meta’s models on browser demos and reviews their published benchmark scores, availability and cost.
38:02ENMeta’s Muse Wonder Full: A Coding Agent Tested Against Opus and SolTheo Browne · Ping LabsTheo Browne tests Meta’s new model on code review, debugging, delegation and benchmarks, finding promising strengths alongside important limits.
18:18ENWhy AI Bills Can Rise as Intelligence Gets CheaperTheo Browne · Ping LabsTheo Browne explains the difference between token prices, task costs and capability, and why more useful agents can still drive larger bills.
0:23ENWhy Theo Would Wait Before Upgrading for UltrafastTheo Browne · Ping LabsA short cost comparison leads Theo Browne to caution against upgrading to the $500 tier solely for Astra Ultrafast.
41:10ENHaiku 5.5: Where a Cheaper Small Model Helps Coding AgentsTheo Browne · Ping LabsTheo Browne examines Haiku 5.5 pricing, benchmark results and practical tests, including a failed pull-request audit.
1:26:46ENThere Likely Is a Level of Intelligence We Shouldn't Go PastPresenta: Nathan LabenzNathan Labenz brings notes from The Curve, a chip startup whose token bill beat payroll, and a software industry that now performance-reviews people for Claude slop.
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