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슬라이드1:02:09EN
Sources Podcast· 2026년 7월 9일팟캐스트 · 3명Jon Steinback on Marker, AI and the Thinking Behind Writing게스트 Jon Steinback · 진행자 Alex Heath, Ellis HamburgerThe Marker founder argues for an editor that asks questions instead of writing for the user; the hosts examine where AI fits in their own work.Product DesignCreativityAI Product Management+1
슬라이드 6장24:43EN
Theo - t3․gg· 2026년 7월 9일Grok 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.코딩 에이전트평가(Evals)AI cost & performance+2
50:57EN
Unsupervised Learning: With Jacob Effron· 2026년 7월 9일팟캐스트A Trillion Dollars of GPUs Will Be Worth $100 Billion in Five Years, Says LSTM's Jürgen Schmidhuber진행자 Jacob EffronThe AI pioneer tells Unsupervised Learning's Jacob Effron why he is wildly optimistic about the technology and deeply pessimistic about the model companies buying the chips.모델과 학습AGI(범용 인공지능)AI research+3
1:27:05EN
20VC with Harry Stebbings· 2026년 7월 9일팟캐스트 · 3명20VC on AI Regulation, Compute Economics and Enterprise Adoption게스트 Jason Lemkin, Rory O’Driscoll · 진행자 Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll debate reported AI policy proposals, infrastructure spending, software deployment and startup liquidity.AI StrategyVenture Capital엔터프라이즈 AI+2
41:05EN
No Priors: AI, Machine Learning, Tech, & Startups· 2026년 7월 9일팟캐스트 · 2명There is no moat: Booking’s CEO on a $1 stock, agentic travel, and why AI still doesn’t move the numbers진행자 Sarah Guo, Elad GilGlenn Fogel cashed his 1999 bonus, joined Priceline in February 2000, and watched the Nasdaq peak a week later — then spent 25 years turning a near-delisting into a thousand-fold ride he now wants to spend on AI travel agents.기업과 전략엔터프라이즈 AIAI Strategy+3
슬라이드 2장1:06EN
Matthew Berman· 2026년 7월 9일Two GPT-5.6 Coding Demos: A Block World and a SpreadsheetMatthew Berman · Forward FutureMatthew Berman shows a Minecraft-like game and an Excel-like application built with Codex and GPT-5.6.코딩 에이전트Computer useDeveloper productivity
0:20EN
Theo - t3․gg· 2026년 7월 8일Theo on Guilt-Merging Pull Requests and Questioning CodeTheo Browne · Ping LabsA short reflection on why developers sometimes accept changes they do not think are right.Code review & verificationSoftware engineeringCoding Culture
슬라이드 8장25:34EN
Matthew Berman· 2026년 7월 8일Anthropic’s J-Space Research: What Its Experiments Reveal and What Remains UnknownMatthew Berman · Forward FutureMatthew Berman examines experiments on internal representations in Claude, from causal interventions to safety auditing and the limits of consciousness claims.Model InterpretabilityAI researchAI Safety+2
1:53EN
Matthew Berman· 2026년 7월 8일What Anthropic’s J-Space Research Suggests About AI ReasoningMatthew Berman · Forward FutureMatthew Berman discusses internal model representations, interventions and the question of consciousness, while the research itself describes important limits.Model InterpretabilityReasoning & test-time computeConsciousness & Intelligence
슬라이드 7장28:11EN
Theo - t3․gg· 2026년 7월 7일The Tradeoffs of Running Open-Weight AI Models LocallyTheo Browne · Ping LabsTheo Browne separates the value of open weights from the hardware, concurrency and cost constraints of local inference.Local inferenceOpen-weight modelsAI cost & performance+2
0:22EN
Theo - t3․gg· 2026년 7월 7일Theo Asks Why Teams Need a Separate System for Environment FilesTheo Browne · Ping LabsA brief prompt to reconsider how development teams share environment configuration.개발 워크플로와 테스트보안과 안전Software engineering
55:19EN
Sequoia Capital· 2026년 7월 7일팟캐스트The drone is 15% of Zipline: 140 million miles, zero incidentsKeller Rinaudo Cliffton and Eric Watson explain why the aircraft is the small part of an automated logistics system now cheaper than a car.인프라와 배포RoboticsAutonomous Systems+3
슬라이드0:24EN
Matthew Berman· 2026년 7월 7일Claude Fable 5 Access Extended Through July 12, 2026Matthew Berman · Forward FutureMatthew Berman reports a short extension for paid Claude subscribers, without a reset of their existing usage quota.모델과 학습
슬라이드 3장18:34EN
Matthew Berman· 2026년 7월 7일Model Routing for AI Coding: A Worked Cost ExampleMatthew Berman · Forward FutureMatthew Berman separates planning, implementation and review to explain how different models can fit different tasks.AI cost & performance에이전트 엔지니어링Developer productivity
4:41EN
Jane Street· 2026년 7월 6일Inside 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
슬라이드0:20EN
Theo - t3․gg· 2026년 7월 6일Theo 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.코딩 에이전트Product Strategy에이전트 엔지니어링
1:11:01EN
20VC with Harry Stebbings· 2026년 7월 6일팟캐스트 · 2명Mike Mignano on AI Applications, Open Models and Venture Strategy게스트 Mike Mignano · 진행자 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
슬라이드 8장43:15EN
Theo - t3․gg· 2026년 7월 6일Theo’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.코딩 에이전트Agent orchestration개발 워크플로와 테스트+2
1:11:53EN
20VC with Harry Stebbings· 2026년 7월 4일팟캐스트 · 2명Sierra Co-founder Clay Bavor on Open Models, Enterprise AI and Building Teams게스트 Clay Bavor · 진행자 Harry StebbingsBavor discusses model selection and compute costs, deploying AI agents for enterprises, and how Sierra approaches hiring and company culture.엔터프라이즈 AIOpen-weight modelsAI agents+2
1:47:38EN
Cognitive Revolution "How AI Changes Everything"· 2026년 7월 4일팟캐스트19 Neurons Can Drive a Car. Liquid AI Wants Foundation Models on Every Chip진행자 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.모델과 학습Local inferenceScaling Laws+3
슬라이드 7장23:24EN
Theo - t3․gg· 2026년 7월 4일Fable 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.코딩 에이전트안전과 거버넌스AI cost & performance+2
0:28EN
Theo - t3․gg· 2026년 7월 3일Theo 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
슬라이드 4장38:05EN
Theo - t3․gg· 2026년 7월 3일Why 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.코딩 에이전트개발 워크플로와 테스트인프라와 배포+1
슬라이드 9장18:02EN
AI Explained· 2026년 7월 2일Fable 5 and GPT-5.6 Sol: An Early Look at Capability, Price and SafetyWith Sol still in limited preview, AI Explained compares the available system cards and examines access restrictions and safety tradeoffs.모델과 학습BenchmarksAI Safety+1
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