Why GenAI hallucinates

Hallucinations aren’t random: they fall out of how LLMs are trained and prompted. Here’s the intuition.

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People talk about hallucinations like they’re a bug. They’re better understood as a predictable failure mode.

The intuition

An LLM is trained to predict the next token based on patterns in data. It doesn’t “look up facts” by default — it generates text that sounds plausible given the prompt and its training.

When the model doesn’t have enough grounding (or the prompt pushes it), it fills gaps with plausible completions. That’s a hallucination.

Why this matters

If you deploy an LLM for anything factual, regulated, or high-stakes, you must assume:

• The model will occasionally be confidently wrong
• Style can mask uncertainty
• Users will over-trust fluent answers

What helps

Ground the model with the right information at the right time (e.g., retrieval) and test for failure modes the way you test for performance and security.

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