Why use an AI assistant for your user stories?
User stories are at the heart of agile development
User stories are at the heart of agile development
However, writing them can quickly become time-consuming, especially when requirements are complex or poorly defined. A well-guided AI assistant can help you:
Automate repetitive tasks (basic writing, formatting, generating acceptance criteria).
Standardize the structure for better understanding by the entire team.
Free up time to focus on business value and user experience.
But how can you ensure that the user stories generated are relevant, clear, and actionable? Here’s how.
1. Clarity & Precision: The foundation of an effective user story
A vague user story = risky development. To avoid misunderstandings, be explicit in your instructions.
How?
Use simple but precise natural language
“The user must be able to manage their profile.”
“As a logged-in user, I want to be able to change my email address and password from my personal space in order to keep my information up to date.”
Add detailed acceptance criteria
Acceptance criteria:
- The email field must be validated using a standard format (e.g., nom@domaine.com).
- A confirmation email is sent after modification.
- The password must contain at least 8 characters, including one uppercase letter and one number.
Illustrate with concrete examples
If the user enters “contact@example,” an error message will appear: “Invalid email format.”
Tip: The more detailed your prompt is, the less the AI will need to guess. Use templates to ensure consistency.
2. Contextualization: Give the AI the keys to understanding your project
AI does not know your product inside out. Provide it with the necessary context so that it can generate user stories aligned with your technical and business specifications.
What information should you share?
- Links to documents: Technical specifications, mockups (Figma, Adobe XD),configuration files (e.g., AGENTS.md), or even existing user stories.
- Business glossary: Define terms specific to your field (e.g., “AGENT” = user role with advanced permissions).
- Project history: Share user feedback or recurring bugs to guide suggestions.
Example of an enriched prompt: *”Write a user story for the password reset feature, taking into account the following constraints:
- The process must comply with GDPR (no storage of passwords in plain text).
- Use the available design system [link to Figma].
- Refer to the technical documentation on the authentication API [link to Confluence].”*
3. Strategic breakdown: Short, independent tickets
A user story that is too broad = a risk of blockage or partial delivery. Favor atomic tickets that are easy to prioritize and develop in sprints.
Best practices:
- 1 user story = 1 specific feature:
“Manage account settings.” (Too vague)
“Enable/disable email notifications.”
- Ticket independence: Each user story must be able to be developed separately.
- Ideal size: A user story should not exceed 1 to 2 days of development.
Advantage: AI sub-agents (or developers) can process multiple user stories in parallel, speeding up iterations.
4. Collaborative workflow People at the heart of the process
AI is an accelerator, not a replacement. Your role is crucial for:
- Validate business relevance: AI does not know your business challenges. It is up to you to verify that the user story adds value.
- Refine suggestions: Correct, complete, or rephrase the AI’s proposals.
- Use automated tests as a safety net: “Generate a user story for feature X and suggest related test scenarios.”
Result: A smoother development cycle with fewer setbacks.
The immediate benefits of AI-human collaboration
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Acceleration
40% reduction in writing time
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Traceability
Better documentation and history
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Reliability
Fewer errors thanks to automatic validations
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Innovation
More time for creativity and architecture
In practice: A complete example
Prompt given to AI: *”Write a user story for the ‘Team file sharing’ feature, with the following constraints:
- Only project members can access shared files.
- Incorporate a permissions system (read/edit).
- Use the storage API [link to documentation].
- Add 3 acceptance criteria and an example error scenario.
Generated user story: *”As a project team member, I want to share a file with my colleagues and define their permissions, in order to collaborate effectively while controlling access to data.
Acceptance criteria:
- Only users invited via their work email can access the file.
- Permissions (read/edit) can be modified by the file owner.
- An access history is available in the ‘Activity’ tab.
Example of an error scenario: If an unauthorized user attempts to open the file, a message is displayed: ‘You do not have permission to access this file.’”*
AI + Human = The winning equation
AI assistants transform the process of writing user stories into a faster, more structured, and less error-prone process. But their effectiveness depends on your guidance:
- Be clear and precise in your instructions.
- Provide context with documents and examples.
- Break down requirements into actionable tickets.
- Collaborate actively to validate and refine.
Want to know more?
FAQ – AI & User Stories
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What are the advantages of an AI assistant for user stories?
It speeds up writing, automates repetitive tasks, and allows you to focus on business value. Up to 40% time savings.
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How can AI be used effectively to generate user stories?
Provide context (objective, constraints, users) and be precise in your instructions and acceptance criteria.
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Can AI replace humans?
No. It assists but does not replace the professional perspective, functional validation, and human decision-making.
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How does DATASOLUTION support this type of use?
DATASOLUTION helps you integrate AI into your agile projects through its DATA & AI expertise and its technology partners.
