Planning basics: frame a problem with AI
Use illustrated notes to separate a user’s difficulty from a proposed feature.
About 15 min readingAs of Oct 2026
Lesson guide · goals & preparation
By the end of this guide
- Separate facts from hypotheses.
- Write a user-centred problem.
- Compare options against evidence.
Who this is for
- People learning to structure this work with AI
- People who want to check a draft against evidence
What you need
- All cases, records and numbers here are fictional teaching material, not recorded model replies or research findings.
- Paper and a pen are enough. To try a prompt, use an assistant you already have and only the fictional material.
This lesson’s terms, in plain language
Read the short meanings here. Open a term for a fuller explanation and example.
- hypothesis
- An unverified idea that can be investigated through observation or a test.
- user story
- A short description of who needs to do what and why.
This reading lesson explains how to use external AI tools. Read from theory to the workflow, examples and explanations, or use the contents to jump to a section.
1 / 4
Theory
Understand what to ask AI to do, how to ask, and the ideas behind the workflow.
Start with a stuck moment
“Add AI recommendations” sounds like a plan, but whose difficulty would it solve? Use three fictional notes: A says a new reading-group member asked where the next meeting was; B says the venue is at the bottom of the announcement; C says the organiser wants automatic replies.
Figure: Three notes pass through a magnifier into one venue-finding problem brief. · AI Ping The cards in the drawing represent these notes. The magnifier asks where each claim came from. The final sheet should describe a difficulty, such as finding the venue, while keeping automatic replies as one possible solution. Moving the venue higher might also help.
Write the person, task and obstacle before requesting ideas. Do not expand one incident into “everyone struggles every week.” The exercise is about accurate framing, not proof of demand.
Keep facts, interpretations and questions apart
A hypothesis is an idea you have not yet established. “The venue is at the bottom” is a supplied fact. “New members stop reading early” is an interpretation. “Where did you stop reading?” is a question that could investigate it.
Use separate columns and attach note IDs to facts. “Could not find the venue” is not “the venue was missing”: those statements suggest different fixes. Leave device, attendance history and delivery method unknown if the notes do not say.
Ask a colleague to trace the columns back to the source. A filled-in document is not necessarily a better document; an honest unknown can prevent an expensive wrong turn.
Write a user story around the outcome
A user story describes a person, a need and a goal. For this fictional case: “As a first-time attendee, I want to find the next venue so I can arrive at the right place.” Treat the proposed motivation as unverified.
Figure: Read the user story as person → task → destination. · AI Ping Read the second drawing as person → task → destination. A chatbot is not required in that chain. An outcome-focused story leaves room for a clearer announcement as well as a conversational interface.
Add an observable acceptance criterion: the announcement shows the next date and venue. “Users are satisfied” needs a separate method of investigation. Do not attach an impressive time or satisfaction target without explaining how it would be measured.
2 / 4
Step-by-step use
Learn what to prepare, how to request help and how to revise the result through examples and explanations.
Ask AI for a comparison, not a verdict
Give the assistant a bounded job: separate supported problems from unknowns using notes A–C. No recorded model answer is supplied here. For any generated sentence, identify its supporting note or label it an inference.
Compare moving venue information with answering questions automatically. Both may serve the same outcome, but the second proposal also needs a rule for choosing current information. That is a design responsibility, not a claim about any product’s price.
Ask who updates changed venues and who notices a wrong answer. A recommendation that ignores those responsibilities is incomplete. If missing information prevents a choice, record the missing evidence and the next action.
Example prompt Practice notes: A a new attendee asked for the venue again; B the venue is at the bottom; C the organiser wants automatic replies. Separate facts, hypotheses and questions. Attach A/B/C to facts. Leave unsupported causes unknown.
3 / 4
Check & explain
Think about what you would ask AI, then read the explanation. Written submissions and external AI use are optional.
This is a learning check, not a test you must pass. Use the explanations to understand the ideas.
Q1Rewrite “All members ignore announcements.”
Write your thoughts (optional)
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Read the answer and explanation
“The attendee in note A asked for the venue again.” Whether they read the announcement or others had the same difficulty remains unknown.
This is your own review, not an automatic score.
Q2Suggest an option to test without automatic replies.
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Read the answer and explanation
Move the date and venue to the top. If discoverability is the issue, this lets you investigate a simpler option before building a feature.
This is your own review, not an automatic score.
Q3An AI role-play says it loves the idea. Is demand validated?
Write your thoughts (optional)
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Read the answer and explanation
No. Role-play can help revise a question or mock-up, but it is not observed user behaviour. Investigate how actual participants find the venue.
This is your own review, not an automatic score.
Common mistakes
- Do not present fictional cases or AI guesses as customer evidence.
- Do not invent deadlines, results or commitments.
- Explain your decision before polishing its presentation.
Your learning record
Completion is optional. Mark this lesson when you feel ready, or move to the next lesson without marking it.
Completion is saved in this browser.
4 / 4
Apply to your work
Consider how new material changes the workflow and checking criteria. Trying an external AI tool is optional.
Try it: a one-page problem brief
Create a brief with five areas: problem, evidence, hypothesis, options and next question. Use the fictional notes throughout. Attach note IDs to evidence and mark untested explanations as hypotheses. Keep both announcement improvements and automatic replies in the comparison.
Ask a reader to trace each claim back to the notes. Explain why you prefer one option and what remains unknown. A single question cannot establish demand across the membership.
Highlight your strongest claim and your most uncertain claim. The first needs evidence; the second needs a next observation. A role-played customer response may help you revise your questions, but it cannot validate real demand.
Write a note (optional)
Use this only if you want to record a prompt or your understanding. This is a notebook, not a connected AI assistant.
Your writing is not sent anywhere. It disappears when you leave or reload this page, so copy anything you want to keep.
References
- Learning about users and their needs — GOV.UK
- Writing user stories — GOV.UK
