Hallucinations

Hallucinations are errors where a language model confidently gives you wrong information. A model generates the most likely text rather than checking facts, so it can invent a source, an API method that doesn't exist or a number that isn't in your docs.

Why hallucinations happen:

• The data wasn't in the training set or the context
• The question is ambiguous
• The model fills in the answer based on similar examples
• The context is overloaded and key details get lost

How to reduce them:

• Give the model sources through RAG and ask it to cite them
• Connect accurate docs instead of relying on the model's memory
• Have a person review important answers
• Let the model say “I don't know”

When an agent works with the Pachca API, it doesn't need to guess methods: up-to-date docs are available in llms.txt, through the Context7 MCP server, in Agent Skills and in the OpenAPI spec.