Crucible Moments will be back shortly with season 2. You’ll hear from the founders of YouTube, DoorDash, Reddit, and more. In the meantime, we’d love to introduce you to a new original podcast, Training Data, where Sequoia partners learn from builders, researchers and founders who are defining the technology wave of the future: AI. The following conversation with Harrison Chase of LangChain is all about the future of AI agents—why they’re suddenly seeing a step change in performance, and why they’re key to the promise of AI.  Follow Training Data wherever you listen to podcasts, and keep an eye out for Season 2 of Crucible Moments, coming soon. LangChain’s Harrison Chase on Building the Orchestration Layer for AI Agents Hosted by: Sonya Huang and Pat Grady, Sequoia Capital Mentioned:  ReAct: Synergizing Reasoning and Acting in Language Models, the first cognitive architecture for agents SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering, small-model open-source software engineering agent from researchers at Princeton Devin, autonomous software engineering from Cognition V0: Generative UI agent from Vercel GPT Researcher, a research agent  Language Model Cascades: 2022 paper by Google Brain and now OpenAI researcher David Dohan that was influential for Harrison in developing LangChain Transcript: https://www.sequoiacap.com/podcast/training-data-harrison-chase/