AI Agent Dry Runs: Rehearsing Delegated Work Before It Acts

Mon, 18 May 2026 00:00:00 +0000

An AI agent that can act should also be able to rehearse. The rehearsal is where the system learns the shape of the work without yet spending the authority that makes the work consequential. It lets the agent discover missing context, wrong assumptions, brittle tool calls, confusing approvals, and bad stop conditions while the cost of being wrong is still low.

Dry runs matter because delegated work often hides risk inside ordinary steps. A customer reply can look harmless until it selects the wrong account. A code change can look small until it touches a shared migration. A research summary can look polished until it relies on a stale source. A record update can look routine until the agent applies it to every duplicate match. The dry run gives the workflow a chance to show its path before that path becomes real.

Simulation on Fondsites

AI Agent Dry Runs: Rehearsing Delegated Work Before It Acts