Instead of relying on what an AI model learned during training, you can feed it fresh information from your own documents, databases, or files right before asking a question. This keeps answers grounded in your actual data rather than the AI's general knowledge, which matters when accuracy and currency matter more than creativity.
Retrieval augmented prompting is the practice of pasting relevant source material, documents, or data directly into your prompt so the AI generates its response based on that specific information rather than relying solely on its training knowledge.
This technique sharply reduces hallucination risk and makes AI outputs verifiable, which is essential any time accuracy matters more than speed and you need answers grounded in your actual files, notes, or research.
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.