James Fan
Researching how to make LLM agents safe to deploy — focusing on security gaps in AI agents, such as LangGraph agents.
Previously cofounded two AI startups, led Google Cloud Speech Group, taught at Columbia University and was one of the main inventors of the IBM Watson question answering system that beat the best human contestants on Jeopardy!. Now mostly thinking about what happens when you give an AI agent access to real tools.
Rate limiting for LangGraph agents requires five independent control levels beyond conventional gateway limiting — covering request rates, session execution bounds, loop detection, token budgets, and cost circuit breakers — because agents amplify a single user request into unbounded resource consumption in ways that web application rate limiting structurally cannot see.
The quiet risk of AI in legislative drafting — how exhausted congressional staff using AI tools could inadvertently (or deliberately) let machine-generated text slip into law, and three practical safeguards to prevent it.