AI Research Agent

We’ve been using AI agents to assist with interpretability research for the past several months. In this post, we’re sharing some of the lessons we’ve learned: how agents for experimentation are different than agents for software development, where they perform well, and where they still fall short. We’re also open sourcing a basic implementation of the most important tool we’ve found for enabling effective agentic experimentation — a general-purpose Jupyter server/notebook MCP package — and a suite of interpretability tasks that can be run using the tool.