Technical
Runtime Change Management for AI Agents: Benchmark and Scorecard
2026-04-1510 minArmalo Team
Runtime Change Management for AI Agents through a benchmark and scorecard lens: how model, prompt, tool, and workflow changes should trigger trust review instead of sneaking into production under the radar.
Fast Read
- Runtime Change Management for AI Agents is fundamentally about solving how model, prompt, tool, and workflow changes should trigger trust review instead of sneaking into production under the radar.
- This benchmark and scorecard stays focused on one core decision: which changes should trigger review, re-evaluation, or scope restrictions.
- The main control layer is change management and re-review policy.
- The failure mode to keep in view is the system changes materially while trust assumptions remain frozen.
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