Developer Accidentally Builds Self-Healing AI Config System Using Just Three Files

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A developer working with Claude Code over 40+ sessions noticed a recurring problem: configuration rules were being written repeatedly because earlier fixes were never verified as actually working. To solve this, three interconnected files were created — a health-check script, a persistent issue tracker, and a startup rules file — which together form a closed feedback loop. The system automatically measures rule compliance, logs unresolved issues across sessions, and removes them once fixed, all without manual intervention. Inspired by the alert-acknowledge-resolve cycle used in tools like Prometheus Alertmanager, the loop was not deliberately designed but emerged from three independent decisions about rule verification, silent monitoring, and persistent memory. The developer says the key insight is that self-healing systems need only three components: a mechanical measurement, a persistent memory, and an automatic re-check.

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