The Nightly Review Pattern: How to Keep AI Agents Aligned Over Time

Most people configure their AI agents once and walk away. That works for a week. Then behavior drifts, edge cases accumulate, and you wonder why the agent that worked great on day 3 is making weird decisions on day 30. The fix isn't more constraints up front. It's a nightly review loop. What the Nightly Review Does Once per day (or per session cycle), your agent runs a structured self-check: What tasks did I complete today? What did I escalate or skip? Did I stay within my defined ownership zone? What decisions did I make that surprised me? These answers go into a nightly-review.md file. The next session starts by reading it. Why This Works Agents drift because feedback loops are too long. You deploy a config, run it for a week, notice a problem, and by then you've lost the context to debug it. The nightly review compresses that loop to 24 hours. It also creates a paper trail. When something goes wrong, you don't have to reconstruct what the agent was doing — it told you. The SOUL.md R