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.

Imagine a practical setting.

Imagine supplying only the relevant section of a long project archive. The selection defines what information the model can use in that interaction.

Before the next experiment.

Treat an example as part of the instruction. Its omissions and boundaries can influence a result as much as the words that describe the task.
A few starting points
  1. Identify which material is actually included.
  2. Restate critical constraints when needed.
  3. Keep missing information explicit.

Follow a related question

Compare one object under two light sources.

A color depends on the light

Match precision to the reader’s task.

Rounding without losing the point

Keep learning

Related background to continue exploring this subject.

Google: an introduction to language models NIST: AI risk management framework
Explore a possibility