최근 업데이트된 채널

선택하면 해당 채널만 표시모든 채널 보기 →

필터 결과

11개
정렬
슬라이드 7장18:18EN
Theo - t3․gg· 2026년 10월 12일Why AI Bills Can Rise as Intelligence Gets CheaperTheo Browne · Ping LabsTheo Browne explains the difference between token prices, task costs and capability, and why more useful agents can still drive larger bills.AI cost & performance코딩 에이전트모델과 학습
슬라이드 7장28:17EN
Theo - t3․gg· 2026년 10월 6일Ultrafast Coding: A Live Design Loop With a Steep CostTheo Browne · Ping LabsTheo Browne explores how fast inference changes his workflow, and why he still advises against upgrading solely for Ultrafast.코딩 에이전트AI cost & performanceDeveloper productivity
슬라이드 7장27:53EN
Theo - t3․gg· 2026년 9월 22일Grok 4.7: Strong Codebase Investigation, Uneven ValueTheo Browne · T3Theo compares launch claims, token costs, benchmarks and his own codebase and game tests, finding useful review behavior alongside significant tradeoffs.코딩 에이전트AI cost & performance평가(Evals)+2
슬라이드 4장27:09EN
Theo - t3․gg· 2026년 9월 18일Why Theo Values Reliable Coding Agents Over Peak PerformanceTheo Browne · T3Theo Browne argues that a model’s weakest moments matter when a coding task stretches from investigation through testing and review.코딩 에이전트Developer productivityAI cost & performance+2
슬라이드 8장25:31EN
Theo - t3․gg· 2026년 8월 13일Grok 4.6: Better Agent Benchmarks, With Tradeoffs in Speed and CostTheo Browne · t3.ggTheo Browne tests Grok 4.6 on design, games and real code, weighing reported benchmark gains against his experience of slower and costlier tasks.코딩 에이전트평가(Evals)AI cost & performance+2
슬라이드 9장25:58EN
Theo - t3․gg· 2026년 7월 14일Theo on Codex Ultra: Reasoning Effort, Sub-Agents and UsageTheo Browne · Ping LabsTheo examines the Ultra mode he tested, its effect on multi-agent work, and why he prefers explicit workflow stages.코딩 에이전트Agent orchestrationAI cost & performance+2
슬라이드 6장26:09EN
Theo - t3․gg· 2026년 7월 10일What Theo Built with GPT-5.6 During Six Weeks of Early AccessTheo Browne · Ping LabsFrom mobile rewrites to a compiler prototype and remote machine repair, Theo Browne shares unusually large-scale experiments and their limits.코딩 에이전트Computer use개발 워크플로와 테스트+2
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
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
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
슬라이드 3장23:36EN
Theo - t3․gg· 2026년 5월 20일Gemini 3.5 Flash, Antigravity CLI, and Railway’s Cloud OutageTheo Browne · T3Theo questions a model launch, a developer-tool transition, and a cloud outage while examining the costs and dependencies behind each.코딩 에이전트GeminiAI cost & performance+2