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21:58ENHow Matthew Berman Uses Grok Bot for Email, Meetings and Everyday TasksMatthew Berman · Forward FutureA tour of connected bots covers practical routines, reported coding workflows and features the host has not yet tried.
1:06ENTwo GPT-5.6 Coding Demos: A Block World and a SpreadsheetMatthew Berman · Forward FutureMatthew Berman shows a Minecraft-like game and an Excel-like application built with Codex and GPT-5.6.
18:34ENModel Routing for AI Coding: A Worked Cost ExampleMatthew Berman · Forward FutureMatthew Berman separates planning, implementation and review to explain how different models can fit different tasks.
1:25:12ENHe Hasn’t Typed a Line of Code in Months. Here’s How Augment Reads a Million-Line RepoPresenta: Nathan LabenzGuy Gur-Ari, co-founder and chief scientist at Augment, tells Nathan Labenz how coding agents actually work inside messy enterprise codebases.
1:24:29ENStackBlitz Almost Shut Down. Then Bolt Hit $20 Million ARR in Eight Weeks.Presenta: Nathan LabenzEric Simons tells Nathan Labenz how a seven-year browser operating system, Claude Sonnet 3.5, and a text box replaced the local toolchain.
55:16ENGemini’s API Grew 14× in Six Months. Google’s PMs Explain the Catch-Up.Presenta: Nathan LabenzLogan Kilpatrick and Shrestha Basu Mallick walk through search grounding, Gemini Flash’s price-latency quadrant, and why a near-tied leaderboard still leaves Google third in most developers’ queues.
15:59ENTail Calls and Local Regions in OCamlA list-counting example reveals why a local closure can escape at a tail call, and how regional mode and [@nontail] affect the result.
1:05:52ENInfinite AI Interns Are Already on the JobPresenta: Nathan LabenzNathan Labenz tells computer-science students how to stand out when models are beating doctors on routine work and firms are hiring fewer juniors.
1:25:10ENWriting Code Is Only 30% of the Job. CodiumAI Wants the Other 70%Presenta: 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.
1:39:53ENUnder 100 People, 24 Million Users: Replit's Bet on Artificial Developer IntelligencePresenta: 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.
1:45:46ENReplit's $10 AI Programmer Already Pays for Itself. The Ambition Is Bots Hiring BotsPresenta: Nathan LabenzTyler Angert, Replit's first product designer, explains Ghostwriter, a virtual developer, and why the company calls itself the perfect substrate for AGI.
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.
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.
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.
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 OCamlA 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 TeammatePresenta: 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 DisasterPresenta: 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 CreatorsPresenta: 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 EnduresPresenta: 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.
50:03ENCopilot Is a Copilot, Not a Pilot: Inbal Shani on the Future of AI in Software DevelopmentPresenta: Lenny RachitskyGitHub's chief product officer explains what AI changes for developers, what it does not replace, and how teams should adopt it.
1:38:45ENWhen Coding Stops Being the Bottleneck: Inside Anthropic's Claude Code and Cowork TeamsPresenta: 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.
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