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4:41EN
Jane Street· 2026年7月6日Inside Jane Street’s Internship: Projects, Mentorship and LearningCody · Jane StreetInterns and employees describe collaborative interviews, learning finance from the basics, and working on projects used by the firm.CareersCompany CultureMachine Learning+1
スライド0:20EN
Theo - t3․gg· 2026年7月6日Theo on Markdown Files as Instructions for Coding AgentsTheo Browne · Ping LabsA short observation about how agent tools can change the scale of a software idea.コーディングエージェントProduct Strategyエージェント工学
1:11:01EN
20VC with Harry Stebbings· 2026年7月6日ポッドキャスト · 2 人Mike Mignano on AI Applications, Open Models and Venture Strategyゲスト Mike Mignano · ホスト Harry StebbingsThe USV partner discusses AI agents, token spending and the opportunities and risks for startups building above the model layer.Venture CapitalAI StrategyAI agents+2
スライド 8 枚43:15EN
Theo - t3․gg· 2026年7月6日Theo’s Fable 5 Workflow: Model Routing, PR Review, and VerificationTheo Browne · Ping LabsA practical walkthrough of delegating tasks across models and turning a stalled backlog into reviewed work, with cost and deployment boundaries.コーディングエージェントAgent orchestration開発ワークフローとテスト+2
1:11:53EN
20VC with Harry Stebbings· 2026年7月4日ポッドキャスト · 2 人Sierra Co-founder Clay Bavor on Open Models, Enterprise AI and Building Teamsゲスト Clay Bavor · ホスト Harry StebbingsBavor discusses model selection and compute costs, deploying AI agents for enterprises, and how Sierra approaches hiring and company culture.エンタープライズ AIOpen-weight modelsAI agents+2
1:47:38EN
Cognitive Revolution "How AI Changes Everything"· 2026年7月4日ポッドキャスト19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every Chipホスト Nathan LabenzRamin Hasani traces liquid neural networks from a worm's 300-cell brain to a 600-megabyte model that will talk from inside a Mercedes, and explains why architecture search now beats architecture avengers.モデルと学習Local inferenceScaling Laws+3
スライド 7 枚23:24EN
Theo - t3․gg· 2026年7月4日Fable 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.コーディングエージェント安全性とガバナンスAI cost & performance+2
0:28EN
Theo - t3․gg· 2026年7月3日Theo on the AI Bubble and the Value Beneath ItTheoTheo thinks AI is in a bubble, but says its underlying value remains an open question. He contrasts NFTs with the internet and its dot-com bust.AI StrategyInvesting
スライド 4 枚38:05EN
Theo - t3․gg· 2026年7月3日Why Theo Moved His Agent Work to Linux MachinesTheoLong-running coding agents, laptop CPU load and slow small-file operations led Theo to build a networked fleet. He demonstrates SSH, a hardware KVM and T3 Code for remote work.コーディングエージェント開発ワークフローとテストインフラとデプロイ+1
1:18:07EN
20VC with Harry Stebbings· 2026年7月2日ポッドキャスト · 3 人20VC Roundtable: AI Spending, Model Competition and Software Acquisitionsゲスト Jason Lemkin, Rory O’Driscoll · ホスト Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll debate enterprise AI returns, prediction markets, SaaS roll-ups and the cost of raising capital.AI cost & performanceVenture Capitalエンタープライズ AI+2
1:01:27EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026年7月2日ポッドキャスト · 2 人Two Years and Four Months to a Live Reactor: Valar Atomics Wants Energy Ten Times Cheaperホスト Sarah Guo, Elad GilIsaiah Taylor walks Sarah Guo through Ward 250 in Utah and argues that nuclear is a hardware-iteration problem, not a paper-design one.インフラとデプロイCompany Building安全性とガバナンス+3
1:29:02EN
Cognitive Revolution "How AI Changes Everything"· 2026年7月1日ポッドキャストFrom 50 Designs a Day to 1,500: How AI Changed What Jaguar Land Rover Can Exploreホスト Nathan LabenzNeural Concept’s Thomas von Tschammer on specialist physics models, engineering copilots, and why Formula 1 already runs thousands of designs overnight.企業と戦略ファインチューニングAgent orchestration+3
スライド 6 枚28:37EN
Theo - t3․gg· 2026年7月1日Theo Tests Sonnet 5 and Explains Fable’s ReturnTheoTheo compares model benchmarks and his own coding tests, finding promise in Sonnet’s subagent orchestration but questioning its task costs.AnthropicコーディングエージェントAgent orchestration+2
スライド 2 枚2:19EN
Theo - t3․gg· 2026年7月1日Theo on Sonnet 5: Agent Orchestration and Token CostsTheoTheo welcomes Sonnet 5's ability to coordinate subagents while questioning its token efficiency. He also discusses the introductory pricing announced at release.AnthropicコーディングエージェントAgent orchestration+1
スライド 6 枚31:30EN
Theo - t3․gg· 2026年6月30日Why Some AI Models Use Fewer Tokens to Solve a TaskTheoTheo explains input, output, caching and reasoning tokens, then explores a hypothesis about terse internal reasoning.AI cost & performanceReasoning & test-time computeKV caching & prefix reuse+2
0:33EN
Theo - t3․gg· 2026年6月30日Theo on Shared AI Conversations and Team CollaborationTheoA shared Claude conversation in Slack lets teammates see and continue the same work. Theo argues that this kind of collaboration differs from a GitHub-centered workflow.Human-AI Collaboration開発ワークフローとテスト
3:51:47EN
Lex Fridman· 2026年6月30日ポッドキャスト · 2 人Forty-Six Percent of Emperors Were Overthrown. The Empire Lasted Anywayゲスト Anthony Kaldellis · ホスト Lex FridmanHistorian Anthony Kaldellis walks Lex Fridman through 2,200 years of Roman history and argues that what we call Byzantium was Rome itself.Political PhilosophyGeopoliticsLeadership
1:10:15EN
Sequoia Capital· 2026年6月30日ポッドキャストThe 100x lives between the layers: Dylan Patel on co-design and a 60x yearSemiAnalysis’s founder argues that matching models, kernels, and silicon is what turns a 2x here and a 2x there into 100x, while equivalent-quality inference has gotten about 60 times cheaper in a year.インフラとデプロイInferenceBenchmarks+3
0:42EN
Matthew Berman· 2026年6月30日Matthew Berman's Concern About Access to Frontier AIMatthew Berman · Forward FutureIn a short commentary, Berman argues that restricted model access could disadvantage startups and slow US innovation.AI RegulationOpen-weight modelsAI Strategy
1:06:10EN
20VC with Harry Stebbings· 2026年6月29日ポッドキャスト · 2 人K. R. Sridhar on Distributed Power, AI Demand and Energy Accessゲスト K. R. Sridhar · ホスト Harry StebbingsBloom Energy’s CEO discusses data-center power, manufacturing, natural gas and his vision for broader electricity access.EnergyLeadershipインフラとデプロイ+2
スライド 4 枚22:43EN
Theo - t3․gg· 2026年6月29日Mac Prices, Unified Memory and Local AI: Theo’s Buying Trade-offsTheoTheo explains why high-memory Macs appealed for local inference and how rising component prices changed his comparison with PCs.Local inferenceインフラとデプロイAI cost & performance+1
スライド 5 枚12:26EN
Matthew Berman· 2026年6月28日Hermes Agent: Hosted Setup, Skills, Scheduled Tasks and TelegramMatthew Berman · Forward FutureIn a sponsored June 2026 tutorial, Matthew Berman demonstrates a managed Hermes installation and explores its tools, memory and messaging integrations.エージェントAgent skillsWorkflow automation+2
スライド 6 枚30:08EN
Theo - t3․gg· 2026年6月27日GPT-5.6’s Limited Preview: Benchmarks, Agent Risks and AccessTheoTheo reviews the launch-era announcement, published evaluations and reported agent incidents, while questioning the balance between safety and broad access.OpenAI安全性とガバナンスエージェント工学+2
0:25EN
Matthew Berman· 2026年6月27日Apple’s June 2026 Price Increases and the Memory ShortageMatthew Berman · Forward FutureMatthew Berman links higher Mac and iPad prices to the demand for memory driven by AI infrastructure.PricingAI cost & performance
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