LangChain SF Meetup: LLM Wikis and Giving Your Agents Memory
- WHO IT IS FOR: AI engineers, developers, and product architects interested in improving LLM agent performance through better context management.
- WHAT IT IS ABOUT: The implementation of LLM wikis and structured knowledge bases to provide agents with long-term memory and domain-specific context.
- FORMAT: An in-person evening event featuring two expert technical presentations, Q&A sessions, and professional networking.
Unlock the full potential of your AI agents at the LangChain SF Meetup. While many agents struggle due to a lack of context rather than model weakness, LLM wikis are emerging as a powerful solution. By creating structured knowledge bases that agents can query, developers can significantly improve how AI understands complex codebases, products, and specific domains.
This event features deep dives from Brace Sproul of LangChain and Jacob Teo of Cognition. You'll learn about the newly open-sourced OpenWiki project and get an inside look at Cognition's DeepWiki. The discussions will tackle the hardest parts of building these systems, whether wikis are the right abstraction for agent memory, and how to maintain utility as your product evolves.
Join a community of AI builders in San Francisco for an evening of technical insights and networking. From breaking down the architecture of LLM wikis to discussing the future of agentic memory, this is an essential gathering for anyone building production-ready AI agents.