Keep AI Models Out of Canary Release Decisions, Developers Warned

Software engineers are cautioning against letting AI language models control canary deployment decisions, arguing that release authority must stay with deterministic, code-based gate logic. The core concern is that a model completion can silently rewrite a cautious 'hold' verdict into a confident 'promote', binding release availability to the reliability of a writing tool. Developers recommend a minimal gate contract where numeric signals such as error ratios, burn rates, and latency percentiles produce a fixed enum verdict that a deploy controller reads directly. A language model's appropriate role is drafting human-readable incident notes after the verdict is sealed, not influencing the verdict itself. Teams are advised to derive burn limits and latency budgets from their own SLO documents and subject those thresholds to the same policy-review process as any other production configuration.