Validate a Jira Epic With Synthetic Users | Minds

An epic is a bet written in the team's own language. It passes refinement because everyone in the room already shares the context that makes it make sense — which is exactly the context the customer does not have. The requirement that reads as obvious on Tuesday becomes the support ticket in the release week.

Minds imports the epic directly from Jira and puts it in front of a synthetic audience built from the segment you are actually shipping to. You find the misread sentence while it is still a sentence.

When this is worth doing

Run it when the epic commits real engineering time and the team is relying on assumption rather than evidence:

• the epic introduces a new concept the user has to learn
• acceptance criteria describe behaviour nobody outside the team has reacted to
• two stakeholders disagree about what the user wants and neither has data
• the feature has a pricing, permission, or privacy implication
• you are about to write the copy that ships inside the feature

It is not worth doing for a refactor, a dependency bump, or an epic whose outcome is invisible to the person using the product.

What to import

Use the Jira button in the Minds composer. Either pick a recent issue from the picker or paste an issue link — both browse/ABC-123 URLs and board links with a selected issue resolve to the same import.

Minds flattens the issue into a readable document: the summary as the title, then project, type, status, priority, assignee, labels, and parent epic as context, then the full description with its headings, lists, tables, and panels preserved, then the comment thread. Discussion in comments is usually where the real requirement lives, which is why the thread comes across rather than the description alone.

The workflow

1. Connect Jira in Settings → Integrations. Approve the Atlassian consent screen for your site.
2. Import the epic into a new study.
3. Build the audience that this epic is for — not "users", but the role, context, and constraint that make the behaviour matter.
4. Ask the audience to explain the feature back to you in their own words before you ask whether they like it.
5. Ask what they would expect to happen next, and what would make them abandon it.
6. Rewrite the acceptance criteria against the answers, and note which disagreements are worth a real user session.

Step four does most of the work. A synthetic audience that cannot restate the feature is telling you the description is ambiguous, and that ambiguity is about to become a build.

What good output looks like

You are looking for three things, in this order.

A misread. Someone describes the feature doing something it does not do. That is a wording problem in the epic, and it is free to fix now.

An unplanned objection. A reason to hesitate that never came up in refinement — a privacy worry, an assumed cost, a fear of losing existing data.

A silent assumption. The audience expects a step the epic never mentions, which means the acceptance criteria have a hole.

A directional score is the least interesting output here. "Seven out of ten" tells you nothing you can put in a ticket; "three of them thought this would delete their existing report" tells you exactly what to change.

Sample prompt

Read this epic as the person it is written for. In your own words, what does this feature let you do? What do you expect to happen after you use it, what would make you hesitate, and what is missing that you would need before you trusted it?

Where this fits

This is the fast layer before real research, not a substitute for it. Use it to arrive at a sharper build and a shorter list of open questions, then spend live sessions and instrumented experiments on the questions that survived.

The same import works for stories and bugs, and the Linear connector behaves identically if your team tracks work there. If your requirements live in a document rather than a ticket, the general PRD validation workflow covers the same ground from the document side.