AI Dictionary › Prompting
Generated knowledge prompting is a two-stage technique in which the model is first asked to generate information or knowledge relevant to a topic, and only afterward is asked to use that information to answer the question or carry out the actual task. The model thus supplies on its own the context it will later use.
In the first stage, the prompt explicitly asks the model to list facts, definitions or relevant considerations about the topic, without yet addressing the final question. In the second stage, that generated information is included in the subsequent prompt together with the original question, so the model reasons with both the query and an explicit knowledge base already recalled in front of it.
This technique is useful for questions requiring reasoning over general domain knowledge, where the model possesses the information but might not spontaneously activate it in a direct answer: asking it to first list relevant economic factors and then use them to assess a business scenario, for example, or first recalling applicable rules and then analyzing their application to a case.
The name precisely describes the mechanism: it is knowledge generated by the model itself, not supplied by the user nor retrieved from an external source, and then reused as input for the subsequent reasoning step.
Grace looks favorably on scenarios where you first have the model recall the relevant knowledge and then use it to build the final answer.
From our network
HSE Genius: AI for Safety Data Sheets
Extract SDS data, H phrases and ECHA compliance checks in seconds, powered by AI.
Visit hsegenius.com →From the Agora Intelligence blog
📱 Download the Android app (beta) iOS coming soon
Say what you mean. Get what you need.
Grace Certified, the AI coach that trains and certifies your prompt engineering, by Agora Intelligence.