AI Hallucination
"The phenomenon where a Large Language Model generates information that is factually incorrect or logically inconsistent while maintaining a confident tone. Solved via Surgical Architecture."
Operator's Perspective
Hallucination is a natural byproduct of how LLMs work—they predict the next most likely token based on probability, not verification. To eliminate hallucinations in production, you must build guardrails around the model: feeding it validated source documents (RAG), checking outputs with code compilers, or using multiple agents to review each other's work.
Technical Application
Implement Retrieval-Augmented Generation (RAG). Add a system constraint: "If the provided context does not contain the answer, reply with 'I do not know'. Do not make up information."
Founder_Note
"Never trust an LLM to remember facts. Always retrieve the facts from a database or search engine first, and then instruct the LLM to write the response *only* using that retrieved context."