We present Sentinel, an AI agent architecture that autonomously discovers, plans, and executes modifications to its own source code under constitutional safety guarantees. Unlike existing AI coding assistants that respond to human invocation, Sentinel operates in a closed self-evolution loop: its Reconnaissance layer performs multi-metric static analysis to identify technical debt, its Navigation layer ranks candidate modifications by risk and benefit, and its Execution layer generates AST-based code changes with automatic compilation validation and rollback. Safety is enforced through a deterministic constitutional enforcement layer — a set of 12 inviolable rules that intercept premature task completions, inject mandatory quality gates, and trigger automatic rollbacks when regression thresholds are exceeded. Over a 5-week observation window (90 commits, 1,354-line evolution log), Sentinel autonomously added 12 new functions (+367 LOC), with the constitutional layer intercepting 28.6% of premature completion attempts (2 of 7). Every step approved by the constitution succeeded (100% allowed success rate). Sentinel demonstrates that AI agents can safely modify their own architectures under deterministic guardrails — moving beyond "AI that writes code" toward "AI that evolves itself."
Yahua Ruan (Tue,) studied this question.