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AI Agents

DiagEvo

What's this about?

Diagnosis-guided self-evolution via hierarchical error memory — improve by first diagnosing what went wrong, and keep a structured memory of errors organised by level. 15 upvotes.

Why organise errors hierarchically?

Because "it failed" is not actionable and "line 47 threw a null pointer" does not generalise. A hierarchy separates the levels: a strategic error (wrong approach entirely), a tactical one (right approach, wrong sequence), an execution one (right step, wrong argument). Each demands a different correction, and lumping them together means the system learns the wrong lesson from the wrong level — patching a symptom when the plan was wrong, or rethinking the plan when it was a typo.

Why does this matter to you?

  1. "Diagnose before improving" is the same ordering argument as "evaluate before improving" from the rubric-induction paper.
  2. Error memory that persists across runs is the durable-value argument that WikiSkill and Warp's self-improving reviewer both make.
  3. The hierarchy is the contribution; flat error logs are what everyone already has and they do not help.
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