How to generate AI user stories like a pro using AI?
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Tired of spending too much time writing user stories? You’re not alone.
In fact, one of the product managers on Reddit said that they spend around 5 to 15 hours a week writing user stories and acceptance criteria. That’s a lot of time that could be used on other important work.
But what if you could turn the tables around?
By using the right AI tools, you can draft high-quality user stories within seconds or minutes, giving you more time to focus on building better products.
In this blog, we will cover what a user story is and how to generate user stories using generative AI tools.
What Is a User Story?
In product development, the main goal of the development teams should be to understand users’ needs and deliver a high-quality product that meets those needs. A user story is one type of requirement that describes the product features from the end user’s perspective.
User stories explain who wants a particular feature and why it should be implemented. A well-written user story helps development teams understand the end user’s goal clearly.
The general format of the user story:
- As a [type of user], I want [a goal] so that [a reason].
So, if we break down each part of the user story:
- “Type of user”: For whom are we building this feature? For instance, it can be an online customer, an offline customer, a system admin, a patient, etc.
- “A goal”: It should explain the user’s needs.
- “A reason”: It should explain why a user wants a particular feature.
What Are Acceptance Criteria in a User Story?
Acceptance criteria are predefined conditions that are used to check whether the user story works as expected. It works as a checklist for product development team members, including developers, testers, stakeholders, etc., and helps everyone to know what should be implemented to complete the user story.
Well-defined acceptance criteria are clear and easy to test. It removes guesswork by setting up clear expectations on how the features should behave.
Let’s understand user story and acceptance criteria with an example:
- User Story: As an inventory manager, I want to view current stock levels on the admin dashboard so that I can manage reordering efficiently.
Acceptance Criteria:
- Develop an admin dashboard that displays product names with SKU and available stock for each product.
- Only users having the “Inventory Manager” role should be able to access the inventory-related data.
- If the stock level for any product goes down, show the low-stock warning beside the stock count.
Why Should You Use AI to Write User Stories?
Creating a user story may be manageable at an individual level, but it becomes a tedious job when teams need to create dozens of them. However, an AI-powered user story generator can make this process much faster and more efficient.
With advanced generative AI tools, creating user stories can provide several benefits, such as:
- Maintains Quality: User stories created using AI tools are formatted in a consistent way, which guarantees uniformity across their structure.
- Offers Multiple Options: For any complex feature, if needed, you can ask AI to generate multiple options and pick the best one.
- Provides Suggestions: AI can also suggest new ideas that you might not have thought of, helping you to cover hidden features.
- Non-tech Team Members can also create user stories: With the help of AI tools, non-tech team members can also generate user stories.
- Saves Time: By using AI to generate user stories with acceptance criteria, teams can do hours of work in a few minutes.
Step-by-Step Guide: How to Generate User Stories With AI
AI can generate well-crafted user stories with a title, description, acceptance criteria, etc., but only if you know how to use AI tools effectively. Here, we have provided a step-by-step guide to generate user stories using AI like a pro.
Step 1: Choose the Right Tool
The first step to generating user stories with AI is selecting the right tool. Not every generative AI tool is built for writing user stories. For instance, free tools like ChatGPT, Claude, Gemini, etc., can write user stories, but you need to put a lot of effort into editing them.
To get the structured results, you can use specialized tools like Copilot4DevOps, an AI assistant within Azure DevOps. The “Elicit” feature of the Copilot4DevOps can generate user stories with test cases, acceptance criteria, pseudocode, etc., based on the parent work item’s content, including title, description, etc. This way, even if you don’t know how to write prompts, you can generate user stories.
Check how Copilot4DevOps AI can generate user stories:
Step 2: Define Your Objective and Write a Prompt
Even if you are using the best AI tool to write user stories, but can’t feed the best prompt to the tool, it won’t give you clear results. For writing clear and accurate prompts, mention details like user roles, edge cases, data rules, or conditions associated with the feature. This way, you can instruct an AI to generate usable and testable user stories with acceptance criteria.
Step 3: Review and Refine
Once you have generated user stories using AI, review them and select appropriate ones that follow Agile practices. If needed, manually edit some parts of AI-generated user stories and skip those that are unrelated to the project.
Related: Copilot4DevOps vs. TachyonGPT
Step 4: Add User Stories to the Backlog
After the final review, it’s time to add user stories to the backlog. If you are using tools like ChatGPT, you need to manually copy/paste each user story with its content into the project management tool. However, if you are using Azure Boards as a project management tool, you can generate user stories using Copilot4DevOps and add them to Azure Boards with a single click.
Real-World Use Cases of AI to Generate User Stories in Different Industries
EdTech: Breaking Course Requirements Into User Stories for Product Teams
- The problem: For developing the Edtech platform, teachers and subject matter experts can suggest course flow and content flow logic in slides. From these slides, business analysts or project manager needs to generate user stories that development teams can implement.
- How AI helps: Copilot4DevOps can analyze the slides or docs prepared by the academic teams and break down each feature into user stories. It can also generate acceptance criteria along with user stories.
Logistics & Supply Chain: Structuring Operational Changes Into Work Items
- The problem: The supply chain management team provides suggestions in plain text like “optimize route tracking”, “allow vehicle drivers to select a delivery slot”, etc. These suggestions are helpful, but hard to implement without converting them into well-structured user stories.
- How AI helps: AI can help in converting each suggestion or feature idea into structured and testable user stories. For example, it can break down “custom delivery slots” into smaller parts: time selection rules, customer restrictions, and error handling for unavailable windows.
Also Read: AI Test Case Generation: Tools, Techniques, and Case Study
Closing Thoughts: Let AI Do the Heavy Lifting for Your User Stories
With the use of AI, writing user stories should not feel like a slow, tiring task anymore.
AI is powerful, but it should not be a full replacement for human judgment. AI can speed up the user story creation process and maintain consistency across the structure of the user story. However, final approval of the user stories should be done by humans.
Furthermore, teams make the user story creation process more efficient by using AI tools like Copilot4DevOps, as it seamlessly integrates within your Azure workflow. It allows teams to generate user stories from various work items, including epics, features, etc.
Frequently Asked Questions (FAQs)
1. Can AI generate 100% accurate user stories without the help of humans?
AI tools can generate user stories, but not all AI tools are 100% accurate. As a human, your role should be to review and refine AI-generated user stories rather than writing them from scratch.
2. Which are the best AI tools to write user stories?
Copilot4DevOps is one of the best AI tools available in the market for writing user stories. However, teams can also use ChatGPT, Gemini, Claude, etc., tools.
3. Is it safe to use AI to write stories for projects with sensitive data?
If the tool is using the latest security protocols to protect its customers’ data, it’s safe for you to use the tool for projects with sensitive data. Otherwise, you should look for any other tools.
