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슬라이드 4장9:58EN
MBMatthew Berman· 2025년 1월 31일OpenAI o3-mini Launch: Reasoning Effort, Benchmarks and a Snake TestMatthew Berman · Forward FutureIn January 2025, Matthew Berman reviews OpenAI’s reported results and tries two coding examples with different reasoning settings.OpenAIReasoning & test-time computeBenchmarks+1
0:28EN
MBMatthew Berman· 2024년 11월 6일Comparing Three Local Coding ModelsMatthew Berman · Forward FutureMatthew Berman introduces a sponsored comparison of DeepSeek Coder V2, Yi-Coder and Qwen Coder running on a workstation.Local inference코딩 에이전트Open-weight models
슬라이드 9장19:03EN
MBMatthew Berman· 2024년 10월 30일AI News in October 2024: Apple Intelligence, Coding Assistants, Search, and AgentsMatthew Berman · Forward FutureMatthew Berman reviews the first Apple Intelligence release, new coding tools, AI search disputes, local models, and reports of browser agents.AI agentsAI Adoption코딩 에이전트+2
1:09:09EN
Cognitive Revolution "How AI Changes Everything"· 2024년 10월 2일팟캐스트30 Percent on SWE-bench: Cosine Taught Genie How Engineers Actually Think진행자 Nathan LabenzAlistair Pullen tells Latent Space how Cosine reconstructed human problem-solving, fine-tuned on billions of tokens, and took the top score on software engineering’s hardest public test.코딩 에이전트에이전트 엔지니어링파인튜닝+3
슬라이드 3장13:40EN
MBMatthew Berman· 2024년 7월 29일Testing Llama 3.1 8B: Benchmark Gains and Mixed Practical ResultsMatthew Berman · Forward FutureMatthew Berman tests coding, reasoning and other prompts on the small model and finds several failures despite stronger reported benchmarks.Open-weight models평가(Evals)모델과 학습+1
슬라이드 6장10:57EN
MBMatthew Berman· 2024년 6월 24일Testing Claude 3.5 Sonnet: Coding, Reasoning, and VisionMatthew Berman · Forward FutureMatthew Berman puts Anthropic’s June 2024 model through informal coding, math, puzzle, and image-understanding prompts.평가(Evals)코딩 에이전트Multimodal AI+2
슬라이드 4장17:12EN
MBMatthew Berman· 2024년 4월 30일Testing the Mystery 'gpt2-chatbot' Model in April 2024Matthew Berman · Forward FutureMatthew Berman tries an anonymous model on coding, arithmetic and reasoning tasks while its identity remains uncertain.Benchmarks모델과 학습코딩 에이전트+1
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
1:22:59EN
Cognitive Revolution "How AI Changes Everything"· 2023년 12월 2일팟캐스트If Your Agent Is Right 80% of the Time, Ten Steps Leave You With 10%진행자 Nathan LabenzImbue CTO Josh Albrecht tells Nathan Labenz how a 27-person, pre-product research company is putting $200 million and 10,000 H100s toward agents that can actually finish a long job.에이전트에이전트 엔지니어링Reasoning & test-time compute+3
1:15:39EN
Cognitive Revolution "How AI Changes Everything"· 2023년 11월 29일팟캐스트After 20 Years of Frontend, v0 Wrote Better Code Than Guillermo Rauch Did진행자 Nathan LabenzThe Vercel CEO tells Nathan Labenz why every product needs ghost text, why Software 2.0 will ossify the old stack, and why betting against open source is still the expensive mistake.코딩 에이전트Vibe Coding개발 워크플로와 테스트+3
1:32:41EN
Cognitive Revolution "How AI Changes Everything"· 2023년 10월 5일팟캐스트There are maybe 5,000 people who can train frontier models. The rest need AI engineers진행자 Nathan LabenzSwyx of Latent Space tells Nathan Labenz how a new job is forming, why OpenAI will Sherlock its developers, and what still does not count as an agent.기업과 전략에이전트 엔지니어링코딩 에이전트+3
2:17:30EN
Cognitive Revolution "How AI Changes Everything"· 2023년 9월 29일팟캐스트Gemini Became the Daily Driver. A GPT-5 Worthy of the Name Would Make Agents Work.진행자 Nathan LabenzZvi Mowshowitz returns to Cognitive Revolution to unpack Gemini 1.5, Sora, superalignment, sleeper agents, and the live-player map of frontier labs.기업과 전략AI StrategyProduct Strategy+3
1:39:53EN
Cognitive Revolution "How AI Changes Everything"· 2023년 8월 8일팟캐스트Under 100 People, 24 Million Users: Replit's Bet on Artificial Developer Intelligence진행자 Nathan LabenzMichele Catasta, Replit's new VP of AI, lays out a generate-execute-learn loop he will not call AGI, a 2x-to-1000x productivity ladder, and a keystroke-level data advantage.코딩 에이전트Developer productivityAI startups & small teams+3
1:45:46EN
Cognitive Revolution "How AI Changes Everything"· 2023년 8월 4일팟캐스트Replit's $10 AI Programmer Already Pays for Itself. The Ambition Is Bots Hiring Bots진행자 Nathan LabenzTyler Angert, Replit's first product designer, explains Ghostwriter, a virtual developer, and why the company calls itself the perfect substrate for AGI.코딩 에이전트Developer productivityProduct Strategy+3
슬라이드 3장12:20EN
MBMatthew Berman· 2023년 7월 10일Testing UltraLM 13B: A Small Model’s Strengths and Reasoning ErrorsMatthew Berman · Forward FutureA 2023 local test finds useful writing and simple coding alongside failures in games, arithmetic and logic.Open-weight models평가(Evals)모델과 학습+1
32:48EN
Cognitive Revolution "How AI Changes Everything"· 2023년 2월 23일팟캐스트A Hundred Million to Train, a Penny to Infer진행자 Nathan LabenzIn a February 2023 roundtable, two founders argue on mic over whether AGI ends humanity — and who actually captures the value if it does not.기업과 전략AGI(범용 인공지능)Existential Risk+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
1:39:51EN
Lenny's Podcast팟캐스트After the Inflection Point: Simon Willison on Agentic Engineering, Dark Factories and the Coming AI Challenger Disaster진행자 Lenny RachitskyDjango co-creator Simon Willison explains what changed in November 2025, how he works with coding agents, and why prompt injection remains the field's biggest unsolved risk.코딩 에이전트에이전트 엔지니어링Prompt injection+3
1:33:50EN
Lenny's Podcast팟캐스트Evals Are the New PRDs: Inside Anthropic's Research Product Team진행자 Lenny RachitskyDianne Penn, Anthropic's head of product for research and Labs, explains how the company found its identity, how her team turns user feedback into evals, and why human judgment still matters.제품과 UXAI Product ManagementProduct Strategy+3
1:11:06EN
Unsupervised Learning: With Jacob Effron팟캐스트Replit's Amjad Masad on Building Your Own Model, Latency, and the Next Billion Software Creators진행자 Jacob EffronThe Replit founder explains why AI should be native to the product, why he trained a small in-house model, and why he thinks software engineering is about to split in two.제품과 UX코딩 에이전트Vibe Coding+3
1:53:14EN
Cognitive Revolution "How AI Changes Everything"팟캐스트Worth Thousands, Priced at $20: Zvi Mowshowitz on OpenAI's Flurry, Gemini Bets, Deepfakes and a Compute Cap진행자 Nathan LabenzZvi Mowshowitz and Nathan Labenz survey OpenAI's launch spree, AI pricing and bundling, data pollution, deepfakes, the reversal curse, calls to cap training compute, and Amazon's Anthropic deal.기업과 전략AI StrategyProduct Strategy+3
1:04:25EN
Unsupervised Learning: With Jacob Effron팟캐스트Inside GitHub's Copilot Bet: Agents, Open Source, and Why the Developer Job Endures진행자 Jacob EffronGitHub CEO Thomas explains how Copilot went from a research bet to 1.3 million developers, and what agents, fine-tuning and a multi-model world mean for the next five years of software.코딩 에이전트Developer productivityAI Product Management+3
50:03EN
Lenny's Podcast팟캐스트Copilot Is a Copilot, Not a Pilot: Inbal Shani on the Future of AI in Software Development진행자 Lenny RachitskyGitHub's chief product officer explains what AI changes for developers, what it does not replace, and how teams should adopt it.코딩 에이전트Developer productivityProduct Strategy+3
1:38:45EN
Lenny's Podcast팟캐스트When Coding Stops Being the Bottleneck: Inside Anthropic's Claude Code and Cowork Teams진행자 Lenny RachitskyFiona Fung, who leads the teams behind Claude Code and Cowork, describes how an engineering org that ships roughly eight times more code manages quality, hiring, metrics and culture.코딩 에이전트AI 엔지니어링 리더십Developer productivity+3
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