최근 업데이트된 채널

선택하면 해당 채널만 표시모든 채널 보기 →

필터 결과

28개
정렬
슬라이드 5장38:47EN
Theo - t3․gg· 2026년 10월 28일Theo’s Long-Running Agent Experiments: Verification, Compute and CostTheo Browne · Ping LabsA skateboard game and two compiler projects show how repeated checks and flexible compute can sustain agent work—and how expensive those loops can become.코딩 에이전트에이전트 엔지니어링AI cost & performance+2
슬라이드 5장36:07EN
Theo - t3․gg· 2026년 10월 27일Theo 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.AI cost & performance코딩 에이전트Inference+1
슬라이드 7장38:30EN
Theo - t3․gg· 2026년 10월 14일Theo 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.Gemini코딩 에이전트평가(Evals)+2
슬라이드 8장38:02EN
Theo - t3․gg· 2026년 10월 13일Meta’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.코딩 에이전트AI cost & performance모델과 학습
슬라이드 8장41:10EN
Theo - t3․gg· 2026년 10월 9일Haiku 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.코딩 에이전트AI cost & performance모델과 학습
슬라이드 6장33:33EN
Theo - t3․gg· 2026년 10월 7일Is the $200 Codex Plan Still Worth It?Theo Browne · Ping LabsTheo Browne compares subscription usage, API-equivalent estimates, model efficiency and the cost of Ultrafast.코딩 에이전트AI cost & performance모델과 학습
슬라이드 5장1:06:36EN
Theo - t3․gg· 2026년 10월 2일Theo’s Guide to Running Coding Agents in ParallelTheo Browne · T3Theo explains his approach to subscription usage, agent delegation, review and remote machines, while acknowledging that parts of his setup may violate provider rules.코딩 에이전트Agent orchestrationDeveloper productivity+2
슬라이드 6장30:58EN
Theo - t3․gg· 2026년 9월 29일GPT-6.1 Sol: Cheap, Thorough at Code Review, but Uneven at Long BuildsTheo Browne · T3Theo compares early tests of GPT-6.1 Sol with competing models, from benchmark cost to real code reviews and a 3D game demo.코딩 에이전트AI cost & performance평가(Evals)+2
슬라이드 7장31:46EN
Theo - t3․gg· 2026년 9월 29일Claude Sonnet 5.5: A Fast Research Assistant for Coding AgentsTheo Browne · T3Theo tests Sonnet 5.5 on pricing, reasoning effort, codebase analysis and a 3D game, and finds a surprising role for it alongside larger models.코딩 에이전트AI cost & performance평가(Evals)+2
슬라이드 8장40:14EN
Theo - t3․gg· 2026년 9월 23일Opus 5.5: Theo’s First Day with a New Coding ModelTheo Browne · T3Theo compares price, benchmarks, coding work and game demos while cautioning that his assessment rests on a single day of use.코딩 에이전트AI cost & performance평가(Evals)+2
슬라이드 10장30:29EN
Theo - t3․gg· 2026년 9월 21일Jev: A Fast Classifier for Structured DecisionsTheo Browne · T3Theo Browne explores Typesafe AI’s Jev through classification, game and developer-workflow demos, and explains where he thinks a reasoning model is still needed.Structured outputsModel routing & gateways코딩 에이전트+2
슬라이드 7장44:42EN
Theo - t3․gg· 2026년 8월 7일Theo Tests Meta’s Muse Code: Fast, Cheap and UnevenTheo Browne · Ping LabsMuse Spark 1.2 handles rapid analysis and pull-request triage at low cost, but Theo’s experiments expose integration failures, hallucinations and rate limits.코딩 에이전트AI cost & performanceSoftware engineering+2
슬라이드 7장36:00EN
Theo - t3․gg· 2026년 7월 26일Theo on Kimi K3, Distillation and the Open-Weight AI DebateTheo Browne · Ping LabsKimi K3’s capabilities have sparked arguments over model distillation, security and competition. Theo separates the practical tradeoffs from his own speculation about lab strategy.Open-weight modelsDistillationAI security+2
슬라이드 10장44:29EN
Theo - t3․gg· 2026년 7월 25일Theo’s Opus 5 Review: Coding Style, Cost and Model TradeoffsTheo Browne · Ping LabsAfter a day of coding with Opus 5, Theo compares it with Fable and GPT-5.6 Sol across plans, benchmarks, costs and real work.코딩 에이전트AI cost & performanceBenchmarks+2
슬라이드 9장57:39EN
Theo - t3․gg· 2026년 7월 18일Fable 5 vs GPT-5.6 Sol: Theo on Cost, Coding and Model JudgmentTheo Browne · Ping LabsTheo compares two coding models through benchmarks, design work and long-running tasks, explaining why his favorite model is not always the one he uses first.코딩 에이전트AI cost & performance개발 워크플로와 테스트+2
슬라이드 11장41:35EN
Theo - t3․gg· 2026년 7월 17일Kimi K3 in Practice: Coding, Visual Work, Cost and LimitationsTheo Browne · Ping LabsTheo tests Moonshot’s planned open-weight model on long coding tasks, UI design and a 3D game, while examining benchmarks and security concerns.코딩 에이전트Open-weight modelsAI cost & performance+2
슬라이드 8장30:09EN
Theo - t3․gg· 2026년 7월 13일Theo on Managing GPT-5.6 Sol Usage and Agent WorkTheo Browne · Ping LabsA practical review of reasoning effort, long runs, delegation and stopping points, grounded in the limits and products available in July 2026.코딩 에이전트AI cost & performanceAgent orchestration+2
슬라이드 6장36:00EN
Theo - t3․gg· 2026년 7월 12일GPT-5.6 Reviewed: Strengths, Costs, and Coding-Agent TradeoffsTheo Browne · Ping LabsTheo Browne assesses Sol, Terra and Luna through benchmark results and hands-on coding experience.코딩 에이전트AI cost & performance평가(Evals)+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
슬라이드 7장37:30EN
Theo - t3․gg· 2026년 5월 24일Cursor Composer 2.5: Speed, Coding Benchmarks, and the Limits of EvaluationTheo Browne · T3Theo examines Cursor’s coding model, its training methods, practical performance, and the difficulty of independent testing.코딩 에이전트모델과 학습AI cost & performance+2
슬라이드 4장39:05EN
Theo - t3․gg· 2026년 5월 19일Why GitHub Copilot Changed Its Billing for Agent WorkflowsTheo Browne · T3Theo explains why one agent request can consume vastly different resources, and what that means for subscription pricing.코딩 에이전트AI cost & performancePricing Strategy+2
슬라이드 4장45:51EN
Theo - t3․gg· 2026년 5월 14일Claude Subscription Credits and the Debate Over Third-Party Agent ToolsTheo Browne · T3Theo explains why a separate programmatic allowance affects T3 Code and questions the line between interactive and automated use.코딩 에이전트AI cost & performance에이전트 엔지니어링+2
슬라이드 5장35:13EN
Theo - t3․gg· 2026년 5월 7일Theo on Anthropic’s SpaceX Compute Deal and Claude Usage LimitsTheo Browne, Dario Amodei · Ping LabsThe May 2026 partnership expands capacity for Claude while raising questions about AI infrastructure, training data and competition.Anthropic인프라와 배포코딩 에이전트+2
슬라이드 4장41:11EN
Theo - t3․gg· 2026년 5월 5일Theo and ThePrimeagen on AI Subscriptions, Compute and Model EconomicsTheo Browne, ThePrimeagen, Dario Amodei · Ping LabsA discussion of usage limits, training costs and why the price of a token differs from the cost of useful work.AI cost & performance코딩 에이전트인프라와 배포+2
더 보기28개 중 24개 표시