[P] Combining Stanford's ACE paper with the Reflective Language Model pattern - agents that write code to analyze their own execution traces at scale

I combined two recent approaches, Stanford's ACE and the Reflective Language Model pattern, to build agents that write code to analyze their own execution traces. Quick context on both: ACE ( arxi ): agents learn from execution feedback through a Reflector (LLM-as-a-judge) and SkillManager that curate a Skillbook of strategies. No fine-tuning, just in-context learning. RLM ( arxi ): instead of loading full input into context, an LLM writes and executes code in a sandbox to selectively explore the data. The problem ACE had: the Reflector reads execution traces in a single pass.