Your AI Coding Agent Needs a Change Budget
Why passing tests is not enough to keep autonomous code changes safe, reviewable, and reversible.
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Why passing tests is not enough to keep autonomous code changes safe, reviewable, and reversible.
A passing test is not the same as a change your engineering team can safely merge.
Why production AI agents need execution receipts, not just prompts, traces, and chat logs.
How to decide which model actions may execute now, for this target, with this payload.
Why multi-model AI products must classify the whole request before choosing a model route.
How to prevent primary and fallback AI routes from receiving more tool access than the workflow actually needs.
How to decide what an AI workflow can safely keep, reduce, or stop when its preferred model route degrades.
How circuit breakers protect multi-model AI apps from degraded routes, wasted retries, and late fallbacks.
How to use idempotency keys and durable job state to prevent repeated model calls, tool runs, and side effects.