絞り込み結果
87 件並び順
7:37ENSmol Developer: Generating a Small Python Project From a PromptMatthew Berman · Forward FutureMatthew Berman walks through a 2023 project generator, from a simple Ruby example to a multi-file ChatGPT API program.
5:49ENIan on Software Engineering at Jane StreetIan · Jane StreetA London desk developer explains code review, OCaml training, intern projects and the feedback that comes from sitting near users.
41:40ENEvery 10 Milliseconds Cost Copilot 1% of Completionsホスト Sarah Guo, Elad GilGitHub Copilot's chief architect, Alex Graveley, walks through how a leftover code model with a sub-10% test pass rate became a product developers would not quit — and what he is building next at Minion AI.
58:08ENAmjad Masad on Replit, Company Culture and AI-Assisted Softwareゲスト Amjad Masad · ホスト Harry StebbingsThe Replit founder discusses hiring, developer productivity and the opportunities and risks he saw in AI in 2023.
14:55ENBuilding a Simple Chatbot With Python or BubbleMatthew Berman · Forward FutureMatthew Berman walks through a historical OpenAI API demo using Colab and Gradio, then a Bubble no-code workflow.
12:17ENA 2023 Guide to Prompting ChatGPT: Instructions, Examples, and LimitationsMatthew Berman · Forward FutureMatthew Berman walks through prompt components, common tasks, examples, and adversarial prompting in an early ChatGPT tutorial.
3:15:51ENPython Is a Recipe Written for Two Readersゲスト Guido van Rossum · ホスト Lex FridmanGuido van Rossum on CPython’s 3.11 speedups, indentation, the GIL, and why a 4.0 would hurt extensions more than syntax.
3:08:32ENNinety Minutes With the Door Shut: Cal Newport on Deep Work, Email, and a Life Built for the Worst Caseゲスト Cal Newport · ホスト Lex FridmanThe Georgetown computer scientist talks with Lex Fridman about attention, digital minimalism, a world without email, and why relationships are the only honest worst-case analysis.
2:46:57ENProgramming Languages Are Bicycles for the Mindゲスト Chris Lattner · ホスト Lex FridmanChris Lattner talks with Lex Fridman about Swift, LLVM, RISC-V, and why the next leap in computing is as much a language problem as a silicon one.
59:33ENLaurent Mazare on Python, OCaml and Machine LearningYaron Minsky, Laurent Mazare · Jane StreetA researcher compares exploratory notebooks with robust production systems, and explains how language interoperability and resource management connect the two.
1:23:49ENSteve Lee on PowerShell 7: Compatibility, New Features and the RoadmapSteve Lee · MicrosoftA historical look at the move from Windows PowerShell to cross-platform PowerShell, including demonstrations of the version 7 preview and its compatibility trade-offs.
1:10:58ENThe Hadoop Lesson That Made Google Give TensorFlow Awayゲスト Rajat Monga · ホスト Lex FridmanIn November 2015, Google put its core internal machine-learning system on GitHub. Rajat Monga explains why a company of that size would hand over the hard-to-copy part.
1:03:45ENJane Street and the OCaml CompilerYaron Minsky · Jane StreetRon Minsky traces an accidental language adoption into a long-term commitment to compiler engineering and a shared open-source ecosystem.
1:14:23ENCristina Rosu: Building Dynamic OCaml Web Apps with Incr_domCristina Rosu · Jane StreetA practical introduction to the Elm architecture, virtual DOM and incremental computation, followed by a live counter-app demonstration.
28:31ENIncremental: Self-Adjusting Computations in OCamlSebastian Funk · Jane StreetSebastian explains Jane Street’s dynamic dependency graph library and the algorithms behind efficient updates.
1:06:39ENWhy Jane Street Uses OCamlYaron Minsky · Jane StreetA Jane Street talk explains how functional programming and static types support reliable trading software, and examines the costs of choosing a less common language.
1:04:56ENYaron Minsky on Incremental: From Research Idea to Production LibraryYaron Minsky · Jane StreetA history of the algorithms, memory problems and performance tradeoffs behind Jane Street’s OCaml library for self-adjusting computations.
1:25:13ENCodex Is Not Just a Coding Tool: OpenAI's Plan for an Agent That Behaves Like a Teammateホスト 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.
1:39:51ENAfter the Inflection Point: Simon Willison on Agentic Engineering, Dark Factories and the Coming AI Challenger Disasterホスト 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.
1:11:06ENReplit's Amjad Masad on Building Your Own Model, Latency, and the Next Billion Software Creatorsホスト 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.
1:04:25ENInside GitHub's Copilot Bet: Agents, Open Source, and Why the Developer Job Enduresホスト 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.
1:23:15ENCamille Fournier on Rewrites, One-on-Ones and Building Platform Teamsゲスト Camille Fournier · ホスト Lenny RachitskyThe author of The Manager's Path explains what annoys engineers about PMs, why rewrites are a trap, how to move into management, and what makes platform teams work.
1:32:32ENDevin's Scott Wu on Building an AI Software Engineer and Turning Coders into Architectsゲスト Scott Wu · ホスト Lenny RachitskyThe Cognition co-founder explains how his 15-person team uses fleets of Devins to build Devin, what the product can and can't do, and why he expects more engineers, not fewer.
50:03ENCopilot Is a Copilot, Not a Pilot: Inbal Shani on the Future of AI in Software Developmentホスト Lenny RachitskyGitHub's chief product officer explains what AI changes for developers, what it does not replace, and how teams should adopt it.
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