How to get better AI answers with context and criteria
To get better AI answers, explain the task and how you will assess the result. Useful context and observable criteria let you improve a request without relying on magic phrases.
This guide goes beyond assigning a role to a chatbot: you will create a small delivery agreement, including the input information and a way to check the output.
1. Start with the expected result
Replace “help me with an announcement” with a concrete deliverable, such as a maintenance notice that customers can understand. Define who will read it and what that person should do.
If the goal remains vague, even a well-written answer may solve the wrong problem. Before opening the chat, complete this sentence: “when finished, I need to have…”.
2. Include context that changes the answer
Provide the situation, audience and available facts. For a maintenance notice, the time, affected service and support channel matter more than a lengthy company history.
Separate confirmed information from unresolved details. Labels such as “confirmed time” and “impact to confirm” help avoid presenting a hypothesis as a fact.
3. Turn preferences into criteria
“Good writing” is hard to check; “under 120 words, including the date, impact and next step” makes review more objective.
| Vague preference | Observable criterion |
|---|---|
| Be clear | Explain the action in one direct sentence |
| Be complete | Include the three required facts |
| Be brief | Stay within the specified limit |
The OpenAI prompting documentation describes instructions and context as parts of a request. The structure below is an editorial exercise for applying that principle.
4. Test a complete request
Use fictional information to try the format before working with real material. This example does not depend on a particular tool or subscription plan.
Task: write a maintenance notice for customers.
Audience: readers without technical knowledge.
Confirmed facts: maintenance on the 10th, from 10pm to 11pm; dashboard unavailable.
Missing facts: month and support channel.
Criteria: under 120 words; explain impact and next action; do not promise a different deadline.
Before drafting, ask for missing required information.The desired answer begins by identifying gaps, rather than inventing a month for the notice. That behavior is part of the quality criterion for this exercise.
5. Review one dimension at a time
First check whether the facts are present, then examine tone. If the text is too long, request a shorter version preserving required information instead of starting again without explaining the problem.
Keep the task stable during comparison. Changing the audience, format and goal together makes it harder to discover which instruction improved the delivery.
6. Save a version you can assess
Record the request, an example input and the criteria used. That lets you repeat the test when you switch tools or adjust the activity.
This method improves work organization, but instructions are not a guarantee of accuracy. For the technological background, read what an LLM is.
Frequently asked questions
Do prompts need to be long?
No. Include information that changes the decision or output format, and test whether each part helps.
Does a detailed prompt guarantee a correct answer?
No. Clear instructions help direct the task, but facts and results still need review.
What if information is missing?
Ask the AI to identify gaps and ask questions before concluding, rather than filling missing information with assumptions.