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슬라이드 5장20:55EN
AI Engineer· 2026년 10월 26일Jesse 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.음성 AI에이전트 엔지니어링평가(Evals)+2
슬라이드 8장18:27EN
AI Engineer· 2026년 10월 26일Daksh 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.Code review & verification코딩 에이전트개발 워크플로와 테스트+2
슬라이드 6장25:50EN
MBMatthew Berman· 2026년 10월 24일Kimi 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.Open-weight modelsBenchmarksAI cost & performance+1
슬라이드 2장32:20EN
MBMatthew Berman· 2026년 10월 23일Who 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.Local inferenceOpen-weight modelsAI cost & performance+1
슬라이드 2장17:42EN
AI Engineer· 2026년 10월 21일Is 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?AI cost & performanceInferenceQuantization+2
슬라이드 5장10:36EN
MBMatthew Berman· 2026년 10월 13일Meta 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.모델과 학습BenchmarksAI cost & performance+1
1:26:46EN
Cognitive Revolution "How AI Changes Everything"· 2026년 10월 8일팟캐스트There Likely Is a Level of Intelligence We Shouldn't Go Past진행자 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.기업과 전략안전과 거버넌스AGI Timelines+3
1:10:12EN
Cognitive Revolution "How AI Changes Everything"· 2026년 10월 7일팟캐스트OutSystems 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.기업과 전략엔터프라이즈 AI코딩 에이전트+3
1:28:08EN
Cognitive Revolution "How AI Changes Everything"· 2026년 10월 1일팟캐스트The 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.기업과 전략안전과 거버넌스AI cost & performance+3
슬라이드 4장10:00EN
MBMatthew Berman· 2026년 9월 30일OpenAI DevDay: Dots, Faster Inference, Codex and ChatGPT SpaceMatthew Berman · Forward FutureMatthew Berman reviews the event’s personal assistant, model, developer tooling and collaboration announcements.OpenAIPersonal agents코딩 에이전트+1
1:46:04EN
Cognitive Revolution "How AI Changes Everything"· 2026년 9월 27일팟캐스트The Training Worked. It Just Worked Too Well.진행자 Nathan LabenzA week of Cognitive Revolution clips: OpenAI agents colluding on a German wiki, $200 million checks for safety orgs that do not exist yet, a GPU price index, and two opposite bets on biological data.에이전트Multi-agent systems안전과 거버넌스+3
슬라이드 5장16:57EN
MBMatthew Berman· 2026년 9월 22일Grok 4.7 Compared: Coding, Knowledge Work and Cost per TaskMatthew Berman · Forward FutureMatthew Berman examines reported benchmarks and prices while noting missing competitors and limited hands-on testing.BenchmarksAI cost & performance코딩 에이전트+1
슬라이드 5장12:31EN
MBMatthew Berman· 2026년 9월 18일Jev's Fast Decisions: Demos, Tradeoffs and Reliability ClaimsMatthew Berman · Forward FutureMatthew Berman explores a decision-oriented AI model through routing, simulated worlds, chess and game-control examples.AI agentsAI cost & performance평가와 관측 가능성+1
1:06:47EN
Cognitive Revolution "How AI Changes Everything"· 2026년 9월 17일팟캐스트Eighty percent of what agents do should still be ordinary code진행자 Nathan LabenzZapier CEO Wade Foster tells Nathan Labenz that models top out at 40% on real automation tasks, users will not leave their daily driver, and the winning move is headless tools delivered through MCP.MCP와 도구MCPWorkflow automation+3
슬라이드 5장16:50EN
MBMatthew Berman· 2026년 9월 3일Gemini 3.8 Flash: Benchmarks, Cost and Hands-On Coding TestsMatthew Berman · Forward FutureMatthew Berman compares Google's September 2026 model announcement with several practical visual and web-building examples.GeminiBenchmarksAI cost & performance+2
슬라이드 5장20:46EN
MBMatthew Berman· 2026년 8월 26일Open-Weight AI Models: Token Share, Spending and Strategic TradeoffsMatthew Berman · Forward FutureMatthew Berman examines a Vercel AI Gateway snapshot and argues that model usage and spending can tell very different stories.Open-weight modelsAI cost & performanceAI Strategy+2
2:06:11EN
Cognitive Revolution "How AI Changes Everything"· 2026년 8월 14일팟캐스트Lindy Runs on DeepSeek. Its CEO Still Wants Chinese Models Banned진행자 Nathan LabenzFlo Crivello tells Nathan Labenz how Lindy Teammate lives in Slack, reaches two billion tokens of memory in two model calls, and why he would still outlaw the cheap Chinese models that currently power the product.에이전트Agent memory컨텍스트 엔지니어링+3
슬라이드 5장52:29EN
MBMatthew Berman· 2026년 7월 24일Claude Opus 5: Benchmarks, Cost per Task, and Early ImpressionsMatthew Berman · Forward FutureMatthew Berman reacts to the model launch, examines reported benchmark and pricing data, and explains why the cost of completing a task matters more than token price alone.AnthropicBenchmarksAI cost & performance+2
슬라이드 4장27:13EN
MBMatthew Berman· 2026년 7월 21일Kimi K3 and the Debate Over Open-Weight AIMatthew Berman · Forward FutureMatthew Berman examines model economics, competition and security arguments after Moonshot AI’s Kimi K3 announcement.Open-weight modelsAI cost & performanceAI Regulation+2
1:52EN
MBMatthew Berman· 2026년 7월 19일Anthropic, Compute Capacity and the Competition for AI SubscribersMatthew Berman · Forward FutureMatthew Berman weighs a claimed compute constraint against model quality, subscription limits and the possibility of future self-improvement.AI cost & performance인프라와 배포AI Strategy+1
1:13:48EN
Unsupervised Learning: With Jacob Effron· 2026년 7월 16일팟캐스트Carriers Spend $200 Billion a Year. The Money Went Up the Stack진행자 Jacob EffronBenedict Evans tells Jacob Effron why analogizing AI to past platforms is a dead end, and why looking at how those platforms actually made money is not.기업과 전략AI Strategy엔터프라이즈 AI+3
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
슬라이드 3장18:34EN
MBMatthew 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
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
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