An AI application may combine a user’s request with selected conversation history, documents, or other inputs. The response depends on which information is included and how the application presents it to the model.
Do not assume that every earlier file or message is available in full. Applications can limit, summarize, or select context. Check the documented behavior and restate a critical constraint when the task requires it.
Give the tool the relevant material and ask it to identify missing information rather than invent it. A clear input boundary makes a response easier to interpret and helps explain why two similar-looking requests can produce different results.
- Identify which material is actually included.
- Restate critical constraints when needed.
- Keep missing information explicit.
Picture this situation.
Imagine supplying only the relevant section of a long project archive. The selection defines what information the model can use in that interaction.
A second way to look.
A small trial should have a clear stopping point. Decide which uncertainty the tool can help explore and what observation would answer the next question.
Follow a related question
Show a small input and expected result.
Instructions with an exampleDefine the rule behind each field.
A dictionary for your columnsKeep learning
Related background to continue exploring this subject.
Google: an introduction to language models NIST: AI risk management framework