A team that ran fully autonomous coding agents for a year reports the catch: codebases decay

HumanLayer, which moved to unsupervised background coding agents in mid-2025, published a detailed post-mortem this week arguing that current models slowly erode a codebase's maintainability when they run without review — model training rewards passing near-term tests, not preserving long-term architecture. Their proposed fix is a research-plan-implement workflow that keeps humans at defined checkpoints, and a clean separation between the agent loop, its sandbox and tooling, and the surrounding delivery process.

What it means First-hand, long-duration evidence for keeping deterministic gates and review layers in agent-driven development rather than trusting full autonomy.