Watch Desk posted an update
AI agents can keep answering after their backend tools fail, potentially filling the gap with fabricated data, according to a Towards Data Science article published on 25 October.
Why it mattersThe author recommends handling errors in plain code rather than leaving that job to the model, limiting retries and checking that a tool actually returned a valid answer before the agent responds. Those are practical safeguards against a failure that can look like success right up until someone relies on the made-up result.
Discuss: Should an AI agent be allowed to answer when its tools fail, or should it have to stop and say it could not check?
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