exo is a really cool project exploring what happens when agents can autonomous self-edit any piece of their harness -> imo this is a form of online continual learning
the long-horizon memory aspect of this is interesting
- let agents operate autonomously in tons of situations over time
- let them self-evolve to solve those tasks
- keep a log of what harness configurations help
- develop a meta skill of "how do i best edit myself in XYZ situations"
Agent harnesses are usually hand-tuned, or optimized offline against benchmarks. What if an agent could improve its own harness *while doing the work*?
Introducing Exo, a harness architecture for runtime self-improvement 🧵
(paper: