@zostaff: This paper completely changed how I think about self-evolving codebases: Backlog -> Ideate -> Triage -> Execute -> Poli…
Summary
This paper presents a six-phase blueprint for self-evolving codebases using LLMs, emphasizing convergence toward a specification rather than metrics.
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This paper completely changed how I think about self-evolving codebases:
Backlog -> Ideate -> Triage -> Execute -> Polish -> Regress
Here is the 6-phase blueprint:
Backlog: The loop doesn’t close tickets, it systematically exercises the product’s entire specification the way a user would.
Ideate: “As a User x 1000” - an LLM agent runs that surface as a synthetic power user at 1,000x human cadence.
Triage: Every finding passes through unbeatable tests - ground-truth verification the code author cannot fake.
Execute: Changes land under one unified trust model anchored to the spec, not to a metric.
Polish: Drift control measures quality continuously and pauses itself through automatic gates.
Regress: A regression oracle catches rollbacks and keeps them at zero.
The key insight: 38 green tests coexisted with a completely broken product - the loop must converge toward a spec, not a metric.
Across 285+ iterations this produced 1,094+ merged pull requests with zero regressions.
Read this, then check the article below.
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