Agent failure modes are categories of errors where autonomous systems act unpredictably, such as misinterpreting goals or exceeding constraints. Engineers use these taxonomies to debug and harden AI systems before deployment. Developers and safety researchers benefit most, as it helps build reliable, trustworthy agents for tasks like customer support or autonomous driving.
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