Better questions, more useful answers
Build a Question That Gives AI a Better Job
If you already use AI but often receive generic, overconfident or difficult to use answers, the problem may start before the answer. Practise turning a vague request into a clear question you can inspect, challenge and improve.
Three prepared challengesNo typing or accountNothing is sent or saved
- Goal
- Useful context
- Constraints
- Privacy
- Evidence
- Next turn
Start with the right expectation
A Better Question Helps, but It Does Not Make an Answer True
A clear request can make an answer more relevant and reviewable. It cannot guarantee accuracy, replace a reliable source or transfer responsibility to the AI.
Prepared choices only
The workshop runs in this page. It has no account, open text field, score, timer or result submission. Your challenge choices are not stored in the browser or sent to a server. The site's separately disclosed traffic measurement does not include your prepared choices.
The question blueprint
Six Parts You Can Reuse
You will not need every detail every time. The useful habit is to make deliberate choices instead of hoping the AI guesses what matters.
Interactive practice
Assemble the Question, One Decision at a Time
Choose a challenge, then find the strongest prepared move at each stage. An answer explains every choice. There is no ability score.
Static Question Workshop
The interactive controls have not loaded, but you can still use the complete method with six parts. Start with “Explain solar panels” and rebuild it in this order:
- Goal: Explain how rooftop solar panels turn sunlight into electricity.
- Useful context: It is for a curious learner aged 12 preparing a class talk lasting two minutes.
- Constraints: Use plain language, one simple analogy and no more than 180 words.
- Privacy: Do not assume my location or include personal details.
- Evidence: Separate established facts from simplifications and name two reliable source types to check.
- Next turn: Finish by asking one question that would help improve the explanation.
The result is not a magic formula. It is a clearer starting point for a conversation you still need to review.
Choose a challenge
What Kind of Question Are You Building?
3 challenges · 6 decisions each
- Goal
- Context
- Limits
- Privacy
- Evidence
- Next turn
Current decision
Question assembled
Review Before You Use It
You found the strongest prepared move in all six stages. That means this example follows the workshop method. It does not guarantee that an AI answer will be accurate or useful.
- Remove details the AI does not need.
- Check whether the format fits the real task.
- Verify important claims with suitable current sources.
- Keep the final decision and responsibility with a person.
Move from practice to real use
Adapt the Blueprint, Then Challenge the Answer
Do not paste the longest possible request into every conversation. Use only the parts that materially help the current task.
Before sending
Make the Job Reviewable
- Can you state what a useful answer would help you do?
- Have you removed details that are private or irrelevant?
- Have you named the format, limits and important unknowns?
After receiving
Do Not Stop at Fluency
- Which claims matter enough to verify?
- What assumption or counterargument is missing?
- What should change in your next question?
For direct practice checking an answer against source evidence, continue to the Claim Check Lab.
Evidence boundary
The Method Is Practical Guidance, Not a Validated Assessment
Completing a challenge does not establish prompting skill, AI literacy, safety or a better result in real life. The activity provides authored examples for discussion and practice.
Privacy and verification still matter
The Office of the Australian Information Commissioner advises care with personal information in commercially available AI products. NIST describes risks from confidently false generative AI output and the role of testing and evaluation.
Your next practice loop
Ask Better, Then Check Better
Use the workshop to frame the task, then use the Claim Check Lab to practise matching important claims to evidence.