Harrison Chase (Co-founder & CEO of LangChain) joins Jay to discuss the evolution from LangChain's Twitter origins to becoming the infrastructure backbone for thousands of production agents.
Harrison talks about how LangChain started on Twitter and quickly grew into a multi-product ecosystem including; LangChainLangSmithLangGraph, and LangGraph Platform.
The conversation revolves around deep agents, permission models, the issue with memory, and what the future holds for the coding space.
Harrison explains why competing directly with model providers on their specialized domains (like Anthropic's Claude Code) is nearly impossible, but argues the real opportunity lies in UX innovation and bringing these capabilities into existing workflows.
Tune into the full episode to learn why memory isn't the bottleneck yet and how the bitter lesson applies to agent architecture!
HIGHLIGHTS:
0:00 Intro
1:24 LangChain's evolution from Twitter prototype to production platform
3:23 Model capabilities progression from 2023 to today
4:05 Deep agents - planning, subagents, and file systems for long-term tasks
6:37 Why string replacement beats line-by-line editing for Claude
8:14 The impossible challenge of competing with Claude Code directly
11:28 UX differentiation and workflow integration as winning strategies
13:55 Unix commands and composability for non-coding agents
16:14 Sandboxing approaches - individual VMs vs shared environments
20:03 Agent runtime primitives - streaming, human-in-loop, time travel
22:55 Why CLI tools might beat MCP for agent interactions
25:13 Why base performance matters more than persistence
28:10 External vs model-weight memory systems for auditability
30:12 Product admiration - from cooking to Cursor's UX mastery
Connect with Harrison - https://www.linkedin.com/in/harrison-chase-961287118/
Connect with Jay - https://www.linkedin.com/in/jayhack/ or https://x.com/mathemagic1an
Visit https://langchain.com/ for agent development tools