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Zhang et al.: archive-based empirical self-modification of coding agents

Contribution grade

Self-improving coding-agent systems · Human-designed research method or resource

Reference score75,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Maintained a diverse archive of coding-agent programs, selected variants for LLM-guided self-modification and evaluated them on coding benchmarks, allowing improvements to the agent harness itself.

Scientific scope

Maintained a diverse archive of coding-agent programs, selected variants for LLM-guided self-modification and evaluated them on coding benchmarks, allowing improvements to the agent harness itself. Frozen foundation models, evolutionary search and coding benchmarks are inherited. Despite its name, the system empirically tests changes rather than proving Gödel-machine utility improvement. Benchmarks do not certify safe or unbounded recursive intelligence growth.

Evidence

The linked original sources describe this contribution and its evidence limits. WRS has not independently reconstructed the full scientific claims. Frozen foundation models, evolutionary search and coding benchmarks are inherited. Despite its name, the system empirically tests changes rather than proving Gödel-machine utility improvement. Benchmarks do not certify safe or unbounded recursive intelligence growth.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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