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How do you detect hallucinations in LLM output (as opposed to preventing them)?

Preventing hallucinations is one job; catching the ones that slip through at runtime is another. The signal is the detection toolkit, why each signal is imperfect, and how you combine them into an action.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

Preventing hallucinations is one job; catching the ones that slip through at runtime is another. The signal is the detection toolkit, why each signal is imperfect, and how you combine them into an action.

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These lessons teach the material this question tests, in order and from the beginning.

Applied AI Engineering·How language models work, enough to build onFree13mWhy a model states something false with total confidenceHallucination is not a bug that will be patched out. It follows from what the model is built to do. Understanding why changes how you design around it, and separates engineers who mitigate it from those who keep hoping the next model fixes it.
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