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슬라이드 3장25:17EN
Peter Yang· 2026년 11월 11일팟캐스트Peter Yang splits Claude Code work between Opus and FableHe uses Opus for routine execution and reserves Fable for harder decisions, code audits and family-care coordination.코딩 에이전트AI cost & performanceHuman-AI Collaboration
슬라이드 2장19:44EN
OpenAI· 2026년 11월 11일What a managed agent harness has to do to keep workingCharlie, Steve · OpenAIOpenAI engineers explain remote sandboxes, long-running state and a human-approved flight rebooking demo.코딩 에이전트Agent orchestration
1:24:54EN
Invest Like The Best· 2026년 11월 11일팟캐스트 · 2명Zach Reitano: US healthcare must answer to patients게스트 Zach Reitano · 진행자 Patrick O'ShaughnessyRo's founder argues for transparent prices and patient choice, and describes the company's 2022 reset.Public HealthCompany BuildingEntrepreneurship+1
1:13:14EN
Reid Hoffman· 2026년 11월 11일팟캐스트 · 3명Ronnie Chatterji: AI may change work before it changes job counts게스트 Ronnie Chatterji · 진행자 Reid Hoffman, Aria FingerOpenAI’s chief economist expects productivity gains, but says attributing them to AI and managing uneven effects will take work.Future of WorkEconomicsAI Regulation+1
27:14EN
Bloomberg Live· 2026년 11월 11일John Kerry: Cheaper clean energy needs faster deploymentAaron Rutkoff, John Kerry · BloombergKerry argues clean energy can compete on price, while warning that permitting delays and climate damage add costs.EnergyGeopoliticsEconomics
59:16EN
Conversations with Tyler· 2026년 11월 11일팟캐스트 · 2명Terence Tao: AI proofs make mathematical understanding more urgent게스트 Terence Tao · 진행자 Tyler CowenTao explains why proof abundance may change research, education and the value of human explanation.MathematicsAI in Education
슬라이드26:47EN
Every· 2026년 11월 11일팟캐스트 · 2명Dan Shipper: AI makes generating ideas cheap; people still choose what matters진행자 Natalia QuinteroThe Every co-founder uses one customer survey to explain why different perspectives can produce different work from the same model.Future of WorkHuman-AI CollaborationAI agents
슬라이드 3장27:09EN
OpenAI· 2026년 11월 11일A six-week coding agent run and what it took to superviseOpenAI engineers describe a CI maintenance agent, long-running context and the cost of keeping it working.코딩 에이전트Agent orchestration
슬라이드 3장20:48EN
OpenAI· 2026년 11월 11일Sites adds personalized connectors and agent-friendly web appsKatia, John · OpenAIOpenAI demonstrates scheduled updates, per-user plugins and WebMCP in two Sites applications.Product engineeringMCP코딩 에이전트
슬라이드 2장29:37EN
Theo - t3․gg· 2026년 11월 11일Theo finds a security use for Gemini 4 Carbon despite coding frustrationsTheoHis tests show fewer false code-analysis claims than Argon, but latency and reliability still push him toward other models.코딩 에이전트모델과 학습AI cost & performance+1
21:35EN
Masters of Scale· 2026년 11월 11일팟캐스트 · 2명Eric Ries: Why successful companies lose the purpose that made them work게스트 Eric Ries · 진행자 Krista TippettRies argues that pressure from capital can erode a company’s mission, and that trust deserves a place in business decisions.Company BuildingCompany CultureLeadership+1
56:06EN
a16z· 2026년 11월 11일Mike Volpi: AI infrastructure can endure a market correctionRaghu Raghuram, Guido Appenzeller, Mike Volpi · Andreessen HorowitzThe former Cisco executive sees useful assets beyond the hype, but questions who will own them and how systems will evolve.인프라와 배포SemiconductorsVenture Capital
1:42:10EN
Jane Street· 2026년 11월 11일How quickly could AI improve itself? Four forecasters disagreeYaron Minsky, Jaime Sevilla, Ege Erdil, Ryan Greenblatt, Daniel Kokotajlo · Jane StreetOne forecaster puts AI research automation at 50% by 2028; another sees a slower path as more likely, with a real chance of rapid progress.AGI TimelinesAI researchAI Safety+2
슬라이드 3장18:18EN
Matthew Berman· 2026년 11월 11일Fable 5.2 leads a week of model releases, but cost changes the choiceMatthew Berman · Forward FutureMatthew Berman compares Fable and Gemini Carbon, reviews smaller models and discusses Nvidia’s investigation.Machine LearningAI agents
슬라이드 3장12:38EN
AI Engineer· 2026년 11월 11일How Duolingo uses agents to add tests without skipping human reviewKush Agrawal · DuolingoA scheduled pipeline raised iOS coverage by generating tests, repairing CI and routing pull requests to engineers for approval.코딩 에이전트개발 워크플로와 테스트Software engineering
1:03:19EN
Stanford Online· 2026년 11월 11일Manage AI sources: retrieve selectively and withhold context when usefulCynthia Bailey · Stanford UniversityStanford lecturer Cynthia Bailey explains when to retrieve documents, leave context out and guard against instructions hidden in sources.RAG와 지식컨텍스트 엔지니어링Prompt injection+1
2:55:43EN
PowerfulJRE· 2026년 11월 11일팟캐스트 · 3명Paddy Pimblett on fighting, weight cuts and the lightweight division게스트 Paddy Pimblett · 진행자 Joe RoganPimblett explains his Saint Denis finish, his difficult recovery from ankle surgery, and why he refuses to fight teammates.Combat SportsMartial ArtsJiu Jitsu+1
슬라이드 4장48:20EN
Theo - t3․gg· 2026년 11월 10일Fable 5.2 is powerful, but Theo Browne still prefers Opus for everyday codingTheo Browne · T3After a day of tests, Browne compares benchmarks, usage limits and the mistakes that still require a human reviewer.코딩 에이전트Benchmarks모델과 학습
43:35EN
Silicon Valley Girl· 2026년 11월 10일Isomorphic Labs’ Max Jaderberg on narrowing drug designs with AI게스트 Max Jaderberg · 진행자 Marina MogilkoThe researcher explains virtual screening, real laboratory checks and why agent performance must be measured against useful outcomes.Drug DiscoveryAI for scienceAI agents+2
슬라이드 4장38:50EN
AI Engineer· 2026년 11월 10일LinkedIn’s self-improving agent first had to fix its judgesZiwei Guo, Saloni Gandhi · LinkedInA prompt-optimization loop improved a career agent, but unreliable evaluators required human calibration first.에이전트 엔지니어링평가와 관측 가능성Agent orchestration+1
12:48EN
AI Engineer· 2026년 11월 10일Brian Douglas: Turn agent corrections into reusable review knowledgeBrian Douglas · Paper ComputeThe Paper Compute developer captures expert pushback in coding sessions and tests ways to reuse it during review.코딩 에이전트개발 워크플로와 테스트Software engineering+1
59:06EN
a16z· 2026년 11월 10일Dharmesh Shah: Find startup opportunities beyond the AI labs’ pathJoe Schmidt, Dharmesh Shah · Andreessen HorowitzHubSpot’s co-founder explains how to test narrow ideas, build around customer work and use AI without relying on a temporary model gap.AI startups & small teamsProduct Strategy엔터프라이즈 AI+2
슬라이드12:20EN
AI Engineer· 2026년 11월 10일Ayush Bhardwaj: Agent workarounds are feedback for your CLIAyush Bhardwaj · Allos AIAn audit of coding sessions shows where output, errors and stale instructions force agents to improvise.코딩 에이전트개발 워크플로와 테스트에이전트 엔지니어링+1
1:46:17EN
The Knowledge Project Podcast· 2026년 11월 10일팟캐스트 · 2명Jon McNeill on Tesla’s speed: delete steps before automating게스트 Jon McNeill · 진행자 Shane ParrishThe former Tesla president explains the sales bottleneck, product feedback and five-step simplification method behind rapid growth.LeadershipDecision MakingProduct Management+2
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