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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
1:34:29EN
Cognitive Revolution "How AI Changes Everything"· 2026년 2월 18일팟캐스트Three IMO Golds Missed the Same Problem. Harmonic Wants Math to Compile진행자 Nathan LabenzVlad Tenev and Tudor Achim built Aristotle to emit Lean proofs a kernel can check—and they argue that is how mathematical superintelligence stays trustworthy.모델과 학습Reasoning & test-time computeAI research+3
1:41:34EN
Cognitive Revolution "How AI Changes Everything"· 2025년 12월 24일팟캐스트They Owned the Camera Partition—and Still Couldn't Crash the Helicopter진행자 Nathan LabenzKathleen Fisher and Byron Cook tell Nathan Labenz how formal methods turn some software bugs into closed cases, from a DARPA helicopter to AWS policies checked a billion times a second.보안과 안전AI security안전과 거버넌스+3
1:25:10EN
Cognitive Revolution "How AI Changes Everything"· 2024년 3월 12일팟캐스트Writing Code Is Only 30% of the Job. CodiumAI Wants the Other 70%진행자 Nathan LabenzItamar Friedman argues that completion is already a commodity, that code integrity is where AI still lags, and that flow engineering—not fancier prompts—is how GPT-4 doubled its score on coding contests.코딩 에이전트개발 워크플로와 테스트Code review & verification+3
1:25:13EN
Lenny's Podcast팟캐스트Codex Is Not Just a Coding Tool: OpenAI's Plan for an Agent That Behaves Like a Teammate진행자 Lenny RachitskyCodex product lead Alexander Embiricos explains the 20x growth, why every useful agent may need to write code, and why human review speed is the real bottleneck.코딩 에이전트Code review & verificationDeveloper productivity+3
1:07:48EN
Lenny's Podcast팟캐스트Most Productivity Metrics Are a Lie: Nicole Forsgren on Measuring Developer Experience in the AI Era진행자 Lenny RachitskyThe creator of DORA and SPACE explains why lines of code and old pipeline metrics fall short with AI, and how to start improving developer experience by listening, surveying and tying results to what leaders care about.평가와 관측 가능성Developer productivity개발 워크플로와 테스트+3