Research Lessons I Learned at MATS & Redwood
Provides concrete research frameworks and tips for AI safety practitioners working on empirical alignment problems.
AI Summary
Researcher shares empirical AI safety lessons from MATS and Redwood Research apprenticeships, focusing on misalignment auditing and sabotage capabilities.
Excerpt
Good empirical safety research is heavily bottlenecked on thinking more clearly. This post shares a few frames and tips I found useful, illustrated with concrete examples. I spent the better part of 2026 in empirical AI safety research apprenticeships. I was mentored by Alex Turner and Alex Cloud as part of MATS 9 Team Shard, where my collaborator and I worked on finetuning-based misalignment auditing. I then interned at Redwood Research, managed by Aryan Bhatt, where I worked on sabotage capabi
