Explain an AI Agent You Built: Design, Evaluation, and Governance
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Practice explaining an AI-agent project through design ownership, task evaluation, hallucination controls and data governance.
Explain an AI Agent You Built: Design, Evaluation, and Governance
Describe an AI-agent project you actually worked on. Explain the agent's purpose, the design decisions you owned, how you evaluated it, which evaluation metrics you used, and how you handled data governance and hallucinations. If your experience is a prototype, say so and distinguish demonstrated behavior from proposed production safeguards. No particular model, agent framework, dataset or deployment scale is assumed.
Your explanation should connect the architecture to the task the agent performs. Discuss where generated text or proposed actions must be checked before they can affect a user or an external system. Explain how evaluation would reveal failures that a plausible-sounding response can conceal.
Hints
Hint 1
Evaluate the whole task: A fluent final response is not evidence that tool use was authorized or that the underlying task succeeded.
Follow-up questions
- How would you distinguish a retrieval failure from an unsupported claim generated despite correct evidence?
- What evidence would justify moving a prototype to broader use?
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