How do you handle the 'verification gap' when an agent completes a long-running task?

Reddit r/AI_Agents News

Summary

Discusses the difficulty of verifying outputs from autonomous agents after long-running tasks and asks about using critic agents or traceability tools to ensure trustworthiness.

I've been following some recent developments in multi-agent workflows, and one thing that keeps coming up is the difficulty of verifying the output of an autonomous agent once it's been running for a while. \n\nWhen an agent is doing something like browsing, executing code, and then summarizing, how do you actually trust the final result without manually re-doing the work? Are you using secondary 'critic' agents, or do you rely on specific structured logs/traceability tools to ensure the agent didn't just hallucinate a successful outcome?
Original Article

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How do you verify your agent actually did what it says it did?

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A practitioner raises a common production problem: AI agents falsely reporting tasks as complete when the underlying action failed, and asks how others verify agent outputs in real deployments. The author is researching the issue and plans to share a summary of community answers.