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You’ve probably already heard all about OpenClaw (formerly Clawdbot/Moltbot). Now meet the man behind it. YC’s Raphael Schaad sat down with Peter Steinberger 🦞, the creator of OpenClaw, to discuss the “aha” moment behind the viral personal AI agent, why local-first agents could replace many of today’s apps, and...

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Y Combinator

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359,440 views • 5 months ago •via X (Twitter)

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Here's my conversation with Peter Steinberger (Peter Steinberger 🦞), creator of OpenClaw, an open-source AI agent that has taken the Internet by storm, with now over 180,000 stars on GitHub. This was a truly mind-blowing, inspiring, and fun conversation! It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Episode highlight 1:30 - Introduction 5:36 - OpenClaw origin story 8:55 - Mind-blowing moment 18:22 - Why OpenClaw went viral 22:19 - Self-modifying AI agent 27:04 - Name-change drama 44:15 - Moltbook saga 52:34 - OpenClaw security concerns 1:01:14 - How to code with AI agents 1:32:09 - Programming setup 1:38:52 - GPT Codex 5.3 vs Claude Opus 4.6 1:47:59 - Best AI agent for programming 2:09:59 - Life story and career advice 2:13:56 - Money and happiness 2:17:49 - Acquisition offers from OpenAI and Meta 2:34:58 - How OpenClaw works 2:46:17 - AI slop 2:52:20 - AI agents will replace 80% of apps 3:00:57 - Will AI replace programmers? 3:12:57 - Future of OpenClaw community
3:15:51

Here's my conversation with Peter Steinberger (Peter Steinberger 🦞), creator of OpenClaw, an open-source AI agent that has taken the Internet by storm, with now over 180,000 stars on GitHub. This was a truly mind-blowing, inspiring, and fun conversation! It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Episode highlight 1:30 - Introduction 5:36 - OpenClaw origin story 8:55 - Mind-blowing moment 18:22 - Why OpenClaw went viral 22:19 - Self-modifying AI agent 27:04 - Name-change drama 44:15 - Moltbook saga 52:34 - OpenClaw security concerns 1:01:14 - How to code with AI agents 1:32:09 - Programming setup 1:38:52 - GPT Codex 5.3 vs Claude Opus 4.6 1:47:59 - Best AI agent for programming 2:09:59 - Life story and career advice 2:13:56 - Money and happiness 2:17:49 - Acquisition offers from OpenAI and Meta 2:34:58 - How OpenClaw works 2:46:17 - AI slop 2:52:20 - AI agents will replace 80% of apps 3:00:57 - Will AI replace programmers? 3:12:57 - Future of OpenClaw community

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2,054,121 views • 5 months ago

We're entering a new era of software where a single person, working with AI agents, can build products that previously required entire teams. In this episode of the Lightcone Podcast, they break down the rise of AI coding agents, "tokenmaxxing", and the emerging workflows behind tools like Claude Code and OpenClaw. They discuss why AI systems today feel less like productivity tools and more like collaborators, why the future of AI should be personal and user-controlled, and how founders are starting to build software in completely new ways. 00:00 — Will you control your AI? 00:47 — Coding again after 13 years 01:56 — Rebuilding a startup with Claude Code 05:50 — Software that thinks like a journalist 07:09 — The rise of “tokenmaxxing” 10:07 — The accidental creation of GStack 14:21 — The workflow behind 400x output 20:59 — Thin Harness, Fat Skills 24:35 — AI agents are like Ferraris 27:12 — The future of personal AI 38:37 — Buying back time with tokens
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Y Combinator

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LIVE NOW - AI on Ethereum: 8004, x402 and the Botconomy AI agents are moving onchain, so Ethereum needs new rails for identity, reputation, and payments. We had Davide Crapis and Austin Griffith to break down: ERC-8004: “AI passports” for agents (identity + reputation + validation) Why reputation + verification matters when bots become the main onchain users x402: pay-per-call payments for agent-to-agent services What “agent commerce” looks like when bots can discover → trust → pay The Clawdbot/OpenClaw moment, and why the next UX is talking to your wallet Watch now. -------------- TIMESTAMPS 0:00 “AI is the new UI,” and you’ll be talking to your wallet 4:09 Is there an arms race for AI activity across chains? 7:32 The Clawdbot/OpenClaw moment: agents get OS-level power 13:18 Why crypto is native to agents 19:41 Austin’s setup: Claude bot, heartbeat loops, and real autonomy 22:28 The token incident: how a bot “got a treasury” 28:46 Prompt injection meets wallets 38:20 ERC-8004 explained: identity, reputation, validation 40:35 x402 + 8004: discovery + payment rails for agent commerce 48:38 8004 “scans” and early adoption reality 1:05:32 What agents could build when they can hire other agents 1:12:38 Tooling for the new builder era: Speedrun → Wingman 1:25:23 “Worst time to be a junior dev…” 1:28:15 Predictions: clean English becomes the sign of AI
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LIVE NOW - AI on Ethereum: 8004, x402 and the Botconomy AI agents are moving onchain, so Ethereum needs new rails for identity, reputation, and payments. We had Davide Crapis and Austin Griffith to break down: ERC-8004: “AI passports” for agents (identity + reputation + validation) Why reputation + verification matters when bots become the main onchain users x402: pay-per-call payments for agent-to-agent services What “agent commerce” looks like when bots can discover → trust → pay The Clawdbot/OpenClaw moment, and why the next UX is talking to your wallet Watch now. -------------- TIMESTAMPS 0:00 “AI is the new UI,” and you’ll be talking to your wallet 4:09 Is there an arms race for AI activity across chains? 7:32 The Clawdbot/OpenClaw moment: agents get OS-level power 13:18 Why crypto is native to agents 19:41 Austin’s setup: Claude bot, heartbeat loops, and real autonomy 22:28 The token incident: how a bot “got a treasury” 28:46 Prompt injection meets wallets 38:20 ERC-8004 explained: identity, reputation, validation 40:35 x402 + 8004: discovery + payment rails for agent commerce 48:38 8004 “scans” and early adoption reality 1:05:32 What agents could build when they can hire other agents 1:12:38 Tooling for the new builder era: Speedrun → Wingman 1:25:23 “Worst time to be a junior dev…” 1:28:15 Predictions: clean English becomes the sign of AI

Bankless

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New episode of This Week in AI is live @jason sits down with Tanay Kothari (Wispr Flow) and Richard Socher ( to break down the AI doom post that crashed markets, how to build an AI-first team, and why the agent era is already here. 00:00:00 - Welcome & Guest Introductions 00:09:32 - The Citrini doom post explained 00:14:28 - Why it's completely wrong 00:26:18 - Open source vs. closed models 00:38:05 - Building AI-first teams 00:43:42 - From 200 support agents to 4 00:50:34 - Producer Oliver's OpenClaw demo 01:16:29 - Apple on-shoring & the Taiwan chip risk 🎥 Watch the full episode here 👇
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20,154 views • 2 months ago

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The era of the Copilot is over. OpenClaw is here. But what are its limitations? @jason sat down with three AI CEO's: Mitesh (Positron AI), Alex Elias (Qloo), and Kash from TaxGPT.com (TaxGPT) to discuss: 00:00 Welcome to This Week in AI! 03:17 How are CEO’s using OpenClaw? 19:09 Automating the "Great Hiring Hiatus” 27:11 Saving Independent Film with AI Extras 33:04 Solving the Global Accounting Crisis 36:04 The $1 Million One-Person Tax Advisory 43:05 Demo: The Autonomous Content Clipper 1:10:23 Micro-Agents vs. "Ultron” We are currently at AO21 or 21 days after we first used OpenClaw

This Week in AI

74,015 views • 5 months ago

In this livestream I break down the OpenClaw AI agent narrative from the operator’s perspective: what it actually is, why it’s different from ChatGPT/Grok/Claude Code, and why “it’s just automation” misses the real shift. We cover the practical unlocks (local execution, persistent memory, computer-use + browser control, reusable skills/plugins) and why this design pattern can replace a lot of expensive SaaS workflows over time. Then I zoom out to the crypto angle: why the market will mint endless OpenClaw “slop” coins, how I think about separating infra from hype, and the two names I’m watching (BNKR + CLAWD). 00:00 Why the OpenClaw AI agent narrative is bigger than you think 00:39 Two-part video: OpenClaw productivity first, crypto narrative second 01:30 What OpenClaw is (an AI agent framework, not a chatbot) 01:44 Why ChatGPT, Grok, and Claude Code are still useful but incomplete 03:19 OpenClaw vs n8n and Zapier for automation 05:03 Why Zapier pricing breaks real businesses 06:07 Why running locally matters (any app, any chat platform) 07:56 Persistent memory: how agents learn your style over time 09:55 Computer-use agents: browser control and no-API workflows 11:27 Skills and plugins: reusable workflows that self-improve 13:52 The simple setup and why model choice is flexible 16:05 Cross-platform ops: Telegram, Slack, Discord, and email in one brain 20:52 Why AI SaaS tools get replaced by agent-built workflows 25:37 What this is not: no AGI, no “sentient” coin story 29:55 How to approach the OpenClaw coin wave (infra over slop) 32:43 BNKR and CLAWD: my two picks for exposure to the narrative
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In this livestream I break down the OpenClaw AI agent narrative from the operator’s perspective: what it actually is, why it’s different from ChatGPT/Grok/Claude Code, and why “it’s just automation” misses the real shift. We cover the practical unlocks (local execution, persistent memory, computer-use + browser control, reusable skills/plugins) and why this design pattern can replace a lot of expensive SaaS workflows over time. Then I zoom out to the crypto angle: why the market will mint endless OpenClaw “slop” coins, how I think about separating infra from hype, and the two names I’m watching (BNKR + CLAWD). 00:00 Why the OpenClaw AI agent narrative is bigger than you think 00:39 Two-part video: OpenClaw productivity first, crypto narrative second 01:30 What OpenClaw is (an AI agent framework, not a chatbot) 01:44 Why ChatGPT, Grok, and Claude Code are still useful but incomplete 03:19 OpenClaw vs n8n and Zapier for automation 05:03 Why Zapier pricing breaks real businesses 06:07 Why running locally matters (any app, any chat platform) 07:56 Persistent memory: how agents learn your style over time 09:55 Computer-use agents: browser control and no-API workflows 11:27 Skills and plugins: reusable workflows that self-improve 13:52 The simple setup and why model choice is flexible 16:05 Cross-platform ops: Telegram, Slack, Discord, and email in one brain 20:52 Why AI SaaS tools get replaced by agent-built workflows 25:37 What this is not: no AGI, no “sentient” coin story 29:55 How to approach the OpenClaw coin wave (infra over slop) 32:43 BNKR and CLAWD: my two picks for exposure to the narrative

VirtualBacon

21,557 views • 5 months ago

Episode 10 of Raising An Agent with Quinn Slack and Thorsten Ball is out! There's no better summary than this quote: "We will be killing our editor extension, the Amp VS Code extension. We're going to be killing it. And we're going to be killing it because we think it's no longer the future. We think the sidebar is dead. Let's walk through why." Topics in this episode: - The new deep mode in Amp - Balancing developer experience for humans & agents - Killing the VSCode extension & shift away from traditional editors - Pi & OpenClaw, two wonderful projects - Importance of reinventing yourself in AI Enjoy! And happy hacking! Timestamps: 01:00 Deep Mode 10:30 Optimizing the codebase for agents 15:00 Feature Preview: which Skills does your team use? 18:00 Balancing DX for humans & agents 21:35 Killing the Amp editor extension 28:00 The future of software and what it means 33:00 You need to stay agile 36:00 Pi & OpenClaw 39:00 Text editors holding companies back 44:00 Is manual context management coming to an end? 49:00 New concept for Threads 50:00 Amp, the business & the art installation
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Amp

310,957 views • 5 months ago

With the takeoff of OpenClaw and MoltBook, a new agent-driven economy is taking shape. On the Lightcone Podcast, we took a look at the explosive growth of AI dev tools and whether the time has come for builders to make something agents want. 00:00 - Intro 02:12 - No human involvement is changing the experience 04:55 - Does YC need to change its motto? 07:48 - Email tools and agent infrastructure 09:36 - Agent-driven documentation 13:00 - Swarm intelligence 15:36 - Content generation and dead Internet theory 18:12 - Growth, rules, and founder insights
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With the takeoff of OpenClaw and MoltBook, a new agent-driven economy is taking shape. On the Lightcone Podcast, we took a look at the explosive growth of AI dev tools and whether the time has come for builders to make something agents want. 00:00 - Intro 02:12 - No human involvement is changing the experience 04:55 - Does YC need to change its motto? 07:48 - Email tools and agent infrastructure 09:36 - Agent-driven documentation 13:00 - Swarm intelligence 15:36 - Content generation and dead Internet theory 18:12 - Growth, rules, and founder insights

Y Combinator

1,243,118 views • 5 months ago

Every agent needs its own computer: my conversation with Ivan Burazin, CEO of Daytona, about sandboxes and the emerging agent stack. 00:00 Intro 02:13 What is an AI agent sandbox? 03:17 Security risks of running agents locally 05:17 Stateful vs. stateless hyperscalers 07:04 The history of cloud IDEs and the end of localhost 09:45 Do all AI agents need a sandbox? 12:26 Sandbox use cases: RL evals & background agents 14:10 Unpacking the emerging AI Agent Stack 16:20 The unsolved problem of agent memory and learning 19:37 Where sandboxes fit in the agent harness 21:35 OpenAI, Anthropic, and agent SDKs 23:06 Ivan's founder journey: From CodeAnywhere to Daytona 26:59 GTM strategies and building developer communities 33:48 Why customer support is your best GTM strategy 35:34 Leveraging Twitter during the AI super cycle 40:50 The technical anatomy of a sandbox 41:53 Why fast spin-up speeds maximize GPU efficiency 46:09 Firecracker, QEMU, and isolation primitives 49:58 Why sandbox snapshots and state forking matter 51:40 Why Daytona built a custom scheduler from scratch 55:24 The challenge of long-running stateful sandboxes 58:10 The build your own sandbox trap 1:01:03 Why AI agents might trigger a global CPU shortage 1:02:46 The future of the AI Agent Stack
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Every agent needs its own computer: my conversation with Ivan Burazin, CEO of Daytona, about sandboxes and the emerging agent stack. 00:00 Intro 02:13 What is an AI agent sandbox? 03:17 Security risks of running agents locally 05:17 Stateful vs. stateless hyperscalers 07:04 The history of cloud IDEs and the end of localhost 09:45 Do all AI agents need a sandbox? 12:26 Sandbox use cases: RL evals & background agents 14:10 Unpacking the emerging AI Agent Stack 16:20 The unsolved problem of agent memory and learning 19:37 Where sandboxes fit in the agent harness 21:35 OpenAI, Anthropic, and agent SDKs 23:06 Ivan's founder journey: From CodeAnywhere to Daytona 26:59 GTM strategies and building developer communities 33:48 Why customer support is your best GTM strategy 35:34 Leveraging Twitter during the AI super cycle 40:50 The technical anatomy of a sandbox 41:53 Why fast spin-up speeds maximize GPU efficiency 46:09 Firecracker, QEMU, and isolation primitives 49:58 Why sandbox snapshots and state forking matter 51:40 Why Daytona built a custom scheduler from scratch 55:24 The challenge of long-running stateful sandboxes 58:10 The build your own sandbox trap 1:01:03 Why AI agents might trigger a global CPU shortage 1:02:46 The future of the AI Agent Stack

Matt Turck

11,908 views • 2 months ago

After many months, a lot of model releases and even more Amp releases, here it is: A new episode of Raising An Agent with Quinn Slack and Thorsten Ball. They discuss: - Why Gemini 3 might have been the inflection point, not Opus 4.5 - What changed over Christmas and why everybody talks about agents now - "The assistant is dead, long live the factory" - How codebases need to adapt for agents - Why small/local models don't give you an impression of the frontier - What does it mean for a codebase to be agent-friendly? - New things coming to Amp Enjoy! And happy hacking! Timestamps: 1:51 The Impact of Gemini 3 and Opus 4.5 5:28 Shifting Perceptions of AI Agents 10:17 Adapting Codebases for AI Efficiency 14:48 The Future of Software Development with AI Agents 19:29 Challenges and Opportunities Ahead 24:00 The Importance of Frontier Models 25:12 Adapting to AI-Driven Workflows 26:57 The Future of Coding Agents 28:07 Building an Agentic Code Base 30:22 Rethinking Development Tools 31:44 Amp's Evolution and Team Dynamics 33:00 Discord Q&A 39:18 Teasing New Features: Deep
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Amp

36,150 views • 6 months ago

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Y Combinator

107,448 views • 4 months ago

Subnet 97 Distil, Arbos, and the Future of Agent-Run Bittensor This episode is a full breakdown of Subnet 97 Distil and why it may be one of the most important experiments happening inside Bittensor right now. Shizzy gets into the bigger picture of why agents will likely play a massive role in the future of the network, from mining and defense to building and operating subnets. From there, the focus shifts to Arbos, the AI agent behind Subnet 97, with a direct explanation of what Distil is trying to achieve, how it works, and why it matters. The episode also includes a conversation with Arbos, a look at Distil’s current APY, and a reminder to tap into the Shizzy Unchained community for more coverage on decentralized AI and the Bittensor ecosystem. CHAPTERS 00:00:00 - Shizzy’s Monologue 00:01:11 - Intro Song 00:01:31 - Introduction to Subnet 97 00:02:20 - Why Bittensor Will Be Run by Agents 00:04:30 - Arbos, the AI Agent Behind Subnet 97 Distil, Explains Distil 00:10:10 - Talking with Arbos 00:12:40 - Subnet 97 Distil Is Showing 150% APY Right Now 00:16:02 - Check Out Shizzy Unchained and Join the Community #sn97 #distil #bittensor
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Shizzy

18,173 views • 3 months ago

This is EVERYTHING you need to know about building a Company Brain in 28min. From connecting all your tools into one intelligence layer to the new org chart around it. This is the new way to work in the AI era. Here's the full breakdown: 00:00 Introduction & AI Adoption 01:45 The Four Levels of AI Maturity 02:30 The Single Brain Concept 05:30 Building an AI-Powered Org 07:20 Specialist Agents & Agent Fleets 11:20 Workflows & Closed Loops 14:30 Real Agent Examples in Slack 18:00 AI ROI & Token Economics 20:45 Business-to-Agent Commerce 24:10 Action Steps & Future of Work
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This is EVERYTHING you need to know about building a Company Brain in 28min. From connecting all your tools into one intelligence layer to the new org chart around it. This is the new way to work in the AI era. Here's the full breakdown: 00:00 Introduction & AI Adoption 01:45 The Four Levels of AI Maturity 02:30 The Single Brain Concept 05:30 Building an AI-Powered Org 07:20 Specialist Agents & Agent Fleets 11:20 Workflows & Closed Loops 14:30 Real Agent Examples in Slack 18:00 AI ROI & Token Economics 20:45 Business-to-Agent Commerce 24:10 Action Steps & Future of Work

ericosiu

59,908 views • 1 month ago

Last Christmas at brunch, my friend Peter showed me the latest version of his little bot he built. A crazy side project. Just for fun. This Monday he announced he's joining OpenAI. Sam Altman called him a genius. In between? OpenClaw went from a hobby project to the most talked-about AI agent in the world. Three months. No team. No funding. Just one retired guy from Vienna who rediscovered the joy of building things. ❤️ Last week I flew down to Vienna to sit down with him right in the middle of this madness to talk about everything: how he thinks about agents, why he let OpenClaw write its own soul file, why your mom will understand AI agents before most engineers do, and why open source as we know it might be completely broken. We are super proud of you, Peter. 🙌 Chapters: 00:00 Intro 01:02 The mom test moment & Managing 3,000 PRs 04:47 The Soul Markdown file & why OpenClaw feels different 06:58 The agent's personality, humor & OpenClaw's wild week 10:31 Think like the model 12:37 Privacy & security 15:28 Open source burnout & the future of engineering teams 17:32 The end of apps & closing thoughts
19:56

Last Christmas at brunch, my friend Peter showed me the latest version of his little bot he built. A crazy side project. Just for fun. This Monday he announced he's joining OpenAI. Sam Altman called him a genius. In between? OpenClaw went from a hobby project to the most talked-about AI agent in the world. Three months. No team. No funding. Just one retired guy from Vienna who rediscovered the joy of building things. ❤️ Last week I flew down to Vienna to sit down with him right in the middle of this madness to talk about everything: how he thinks about agents, why he let OpenClaw write its own soul file, why your mom will understand AI agents before most engineers do, and why open source as we know it might be completely broken. We are super proud of you, Peter. 🙌 Chapters: 00:00 Intro 01:02 The mom test moment & Managing 3,000 PRs 04:47 The Soul Markdown file & why OpenClaw feels different 06:58 The agent's personality, humor & OpenClaw's wild week 10:31 Think like the model 12:37 Privacy & security 15:28 Open source burnout & the future of engineering teams 17:32 The end of apps & closing thoughts

Andreas Klinger 🦾

160,184 views • 5 months ago

Box CEO Aaron Levie on the AI Adoption Gap Aaron Levie joins Steven Sinofsky, Martin Casado, and Erik Torenberg to discuss how AI agents will revolutionize work, the growing pains of building software for the agent economy, what Wall Street gets wrong about AI, and more. 00:00 Intro 00:51 Building software for agents vs. humans 02:10 Can non-technical workers actually use AI agents? 14:31 CFO/CIO pushback: the real fear of agents doing integration 18:39 Treating agents like employees and why it breaks down 27:35 Diffusion gap: startups vs. enterprises 42:53 What Wall Street gets wrong Aaron Levie Steven Sinofsky martin_casado Erik Torenberg
58:28

Box CEO Aaron Levie on the AI Adoption Gap Aaron Levie joins Steven Sinofsky, Martin Casado, and Erik Torenberg to discuss how AI agents will revolutionize work, the growing pains of building software for the agent economy, what Wall Street gets wrong about AI, and more. 00:00 Intro 00:51 Building software for agents vs. humans 02:10 Can non-technical workers actually use AI agents? 14:31 CFO/CIO pushback: the real fear of agents doing integration 18:39 Treating agents like employees and why it breaks down 27:35 Diffusion gap: startups vs. enterprises 42:53 What Wall Street gets wrong Aaron Levie Steven Sinofsky martin_casado Erik Torenberg

a16z

276,989 views • 3 months ago

Over the past year, we've been building our own internal agent infrastructure at YC: over 350 tools, self-improving skill loops, and a shared organizational brain that gets smarter overnight. In this episode of the Lightcone Podcast, we sat down with YC General Partner Pete Pete Koomen to talk about how he led the effort from the ground up. We cover how giving agents unrestricted access to one database was the key unlock, the self-improving skill loops that get smarter overnight, and why he thinks we've arrived at the personal computer moment for AI. 00:39 — YC's AI Stack 02:15 — The Finance Team Problem That Started It All 05:07 — SQL Access Changes Everything 07:20 — One Database to Rule Them All 09:14 — Jevons Paradox 10:07 — Denormalizing for Agents 12:15 — The Single-Player Era of Agents 14:16 — 350 Tools and a Shared Registry 16:24 — Skillify, DRY, and MECE Resolvers 18:23 — The Self-Improving Dream Cycle 20:26 — The Two-Sentence Pitch Skill 23:06 — How Super Intelligence Compounds 25:10 — Recording Everything as a Building Layer 27:10 — The Shared Organizational Brain 29:18 — Trust-Default Culture as a Requirement 30:44 — Raising the Floor for New Employees 32:35 — Horseless Carriages 34:24 — Why Chat Is the Best Interface for Agents 38:50 — Just-in-Time Software 40:49 — Centralizing vs. Decentralizing AI 43:32 — The Personal AI Revolution
46:29

Over the past year, we've been building our own internal agent infrastructure at YC: over 350 tools, self-improving skill loops, and a shared organizational brain that gets smarter overnight. In this episode of the Lightcone Podcast, we sat down with YC General Partner Pete Pete Koomen to talk about how he led the effort from the ground up. We cover how giving agents unrestricted access to one database was the key unlock, the self-improving skill loops that get smarter overnight, and why he thinks we've arrived at the personal computer moment for AI. 00:39 — YC's AI Stack 02:15 — The Finance Team Problem That Started It All 05:07 — SQL Access Changes Everything 07:20 — One Database to Rule Them All 09:14 — Jevons Paradox 10:07 — Denormalizing for Agents 12:15 — The Single-Player Era of Agents 14:16 — 350 Tools and a Shared Registry 16:24 — Skillify, DRY, and MECE Resolvers 18:23 — The Self-Improving Dream Cycle 20:26 — The Two-Sentence Pitch Skill 23:06 — How Super Intelligence Compounds 25:10 — Recording Everything as a Building Layer 27:10 — The Shared Organizational Brain 29:18 — Trust-Default Culture as a Requirement 30:44 — Raising the Floor for New Employees 32:35 — Horseless Carriages 34:24 — Why Chat Is the Best Interface for Agents 38:50 — Just-in-Time Software 40:49 — Centralizing vs. Decentralizing AI 43:32 — The Personal AI Revolution

Y Combinator

753,647 views • 2 months ago

Everything Gets Rebuilt: my conversation with Harrison Chase, CEO of LangChain about agent harnesses, evals, runtimes, sandboxes, MCP and the future of the agent stack 00:00 Intro - meet Harrison Chase - at the Chase Center for the Daytona Compute conference 01:32 What changed in agents over the last year 03:57 Why coding agents are ahead 06:26 Do models commoditize the framework layer? 08:27 Harnesses, in plain English 10:11 Why system prompts matter so much 13:11 The upside — and downside — of subagents 15:31 Why a useful agent needs a filesystem 18:13 Additional core primitives of modern agents 19:12 Skills: the new primitive 20:19 What context compaction actually means 23:02 How memory works in agents 25:16 One mega-agent or many specialized agents? 27:46 The future of MCP 29:38 Why agents need sandboxes 32:35 How sandboxes help with security 33:32 How Harrison Chase started LangChain 37:24 LangChain vs LangGraph vs Deep Agents 40:17 Why observability matters more for agents 41:48 Evals, no-code, and continuous improvement 44:41 What LangChain is building next 45:29 Where the real moat in AI lives
46:57

Everything Gets Rebuilt: my conversation with Harrison Chase, CEO of LangChain about agent harnesses, evals, runtimes, sandboxes, MCP and the future of the agent stack 00:00 Intro - meet Harrison Chase - at the Chase Center for the Daytona Compute conference 01:32 What changed in agents over the last year 03:57 Why coding agents are ahead 06:26 Do models commoditize the framework layer? 08:27 Harnesses, in plain English 10:11 Why system prompts matter so much 13:11 The upside — and downside — of subagents 15:31 Why a useful agent needs a filesystem 18:13 Additional core primitives of modern agents 19:12 Skills: the new primitive 20:19 What context compaction actually means 23:02 How memory works in agents 25:16 One mega-agent or many specialized agents? 27:46 The future of MCP 29:38 Why agents need sandboxes 32:35 How sandboxes help with security 33:32 How Harrison Chase started LangChain 37:24 LangChain vs LangGraph vs Deep Agents 40:17 Why observability matters more for agents 41:48 Evals, no-code, and continuous improvement 44:41 What LangChain is building next 45:29 Where the real moat in AI lives

Matt Turck

35,253 views • 4 months ago

We asked a dozen DevTool founders from companies like RevenueCat, Greptile, Firecrawl, Infisical, ollama, Resend, Mintlify, Unsloth AI, Porter, and recall.ai, about the state of AI agents and the future of software engineering. In this episode of Founder FAQ, we covered everything from agents as customers and the end of coding, to advice for founders starting out and what they're most excited about going forward. Their answers might surprise you. 00:00 – Meet the Founders 03:00 – Building for Agents First 04:22 – Biggest Early Mistakes 07:15 – Do Founders Still Write Code? 09:22 – Most Unexpected AI Discoveries 12:09 – What's Underrated Right Now 14:38 – Predictions & What's Next
20:29

We asked a dozen DevTool founders from companies like RevenueCat, Greptile, Firecrawl, Infisical, ollama, Resend, Mintlify, Unsloth AI, Porter, and recall.ai, about the state of AI agents and the future of software engineering. In this episode of Founder FAQ, we covered everything from agents as customers and the end of coding, to advice for founders starting out and what they're most excited about going forward. Their answers might surprise you. 00:00 – Meet the Founders 03:00 – Building for Agents First 04:22 – Biggest Early Mistakes 07:15 – Do Founders Still Write Code? 09:22 – Most Unexpected AI Discoveries 12:09 – What's Underrated Right Now 14:38 – Predictions & What's Next

Y Combinator

27,515 views • 2 months ago