Grounding means providing an AI model with specific facts, documents, or data it can cite and reference when responding. Without it, models generate plausible-sounding answers from patterns in their training data, which can feel authoritative but might be entirely invented.
Grounding is the practice of providing AI with specific, reliable source material, such as a document, a set of data points, or a block of text, and instructing it to base its response only on that information rather than its general training knowledge. This technique keeps AI tethered to facts you have verified instead of facts it believes it knows.
Grounding is one of the most practical skills for anyone using AI in high-stakes situations like research, legal review, financial planning, or medical questions, because it sharply reduces the risk of plausible-sounding but inaccurate outputs. When accuracy is non-negotiable, grounding turns AI from a confident guesser into a focused analyst working from your approved sources.
Peri can explain this concept, give practical examples, help you decide whether it applies to your situation, or recommend a journey if appropriate.
Explore related journeys or tell Peri what you're working through.