Your LLM Cannot Tell When It Is Wrong, Build for That

Every LLM hallucinates, and it is not a bug the next model release will fix. Next-token prediction rewards fluent, plausible text, and a confident fabrication scores exactly like a confident fact. The model has no internal mechanism that separates the two.

That means the reliable systems are the ones engineered around the model:

Users forgive a system that says it is unsure. They do not forgive one that invents an answer with a straight face.

There is a full developer guide covering the architecture, a taxonomy of hallucination types, and implementation walkthroughs here: https://www.adaptiverecall.com/ai-hallucinations/