Regression is not just a code problem

An autonomous product can regress when no application code changes. A model snapshot becomes more concise and stops asking a useful clarification. A tool description changes when the agent chooses it. A context compactor removes an objection that should have shaped the next action. A new safety rule causes the workflow to stop too early.

Each component can look reasonable in isolation. The regression appears only after they interact over time. That is why a conventional release checklist catches syntax and service failures but misses many behavioral ones.

The clean comparison is simple in principle: give the current and candidate systems the same people, conditions, tools, timing, and random seeds. Measure the outcomes that customers care about, then inspect the trajectories where the versions diverge.

Paired simulation separates a real behavioral change from audience noise. It can show that a new version converted more warm prospects while creating more opt-outs among skeptical ones. That tradeoff is far more useful than a single average score because a product owner can decide whether the release fits the intended market.

The evidence should include the system version, scenario coverage, outcome deltas, guardrail breaches, and a replay for representative failures. When a metric moves, the team should be able to trace it back to a decision and the state that informed it.

This turns model and prompt changes into governed product changes. It also prevents a familiar cycle where a team fixes the latest visible complaint, deploys, and discovers that the same change weakened a different customer path.