Agent 'done' may not mean done; dev tests 'receipt' checks

The author, a developer, is grappling with a fundamental trust issue in AI agents: the gap between an agent's reported completion and the actual outcome. The idea stems from observing that a tool can return success and the trace can look fine, yet the external system ends up in the wrong state. This is a common pain point for those building agents with real side effects.

The proposed solution is a 'receipt' concept that separates the agent's claim from an independent check. This could be a database write verification, an API state check, or a handoff confirmation. The developer is uncertain whether to build a separate layer or rely on existing tracing and custom checks, and is seeking community input.

For businesses, this matters because AI agents are increasingly used for actions that have real-world consequences. If an agent says it completed a task but didn't, it could lead to errors, data corruption, or broken workflows. The outcome of this experiment could influence how agent reliability is ensured in the future, though the article doesn't provide a conclusion yet.