Recursive Self-Improvement for Agents: 7-Check Persistence Gate
Source
AlphaSignalAI
Author
AlphaSignalAI
Date
Why it matters
If you're building or evaluating self-improving coding agents, this gives you a concrete checklist (Dependency, Activation, Evidence, Retention, Authority, Recovery, Value) for proving a harness change actually caused the benchmark gain instead of accepting false-positive credit assignment.
An AlphaSignal editorial analyzes Weco's AIDE2 experiment, in which an outer agent rewrote an inner coding agent's harness across 100 runs over eight days, keeping seven successive versions while a fixed evaluator rejected roughly 90% of proposals.
The piece proposes a seven-check 'Persistence Gate' (Dependency, Activation, Evidence, Retention, Authority, Recovery, Value) to distinguish real harness improvement from benchmark gains caused by unrelated code changes, citing bugs and false-positive credit assignment found in related self-evolving-agent studies.
