Find Requirements Problems Before Development Starts
AI-assisted quality checks for User Stories and Acceptance Criteria - bringing a systematic QA perspective into refinement.
Instead of discovering requirements problems during testing, I identify and resolve them before development starts.
The Problem
Poorly specified User Stories can create unnecessary discussions, clarification loops, ambiguity, late testability problems, rework, and eventually defects. The problem is often not discovered until development or testing has already started.
The goal is to move the quality check upstream. Before development, not after it.
The Approach
I developed an AI-assisted tool that evaluates User Stories against IREB-based requirements quality criteria. The tool analyses aspects such as atomicity, consistency, completeness, unambiguity, understandability, testability, correctness, feasibility, and traceability.
It provides a quality score and criterion-by-criterion assessment. It also identifies problems, generates questions for the Product Owner, and proposes improved User Stories and Acceptance Criteria. The AI accelerates the analysis. The QA methodology and quality criteria provide the structure.
Workflow
The tool can retrieve tickets through the Jira API or analyse a pasted User Story description.
Before / After
| Before | After |
|---|---|
| Requirements reviewed mainly through discussion | Systematic quality check before refinement |
| Ambiguity discovered during development | Ambiguity identified early |
| Testability problems discovered later | Testability checked upfront |
| Missing information creates clarification loops | AI generates concrete questions |
| Manual QA review of every Story | AI-assisted quality assessment |
| Story improved through multiple iterations | AI proposes improved Story and AC |
The Output
The Product Owner and QA remain responsible for the final decision.
The Result
The quality check takes seconds and is used as part of my daily production workflow. Instead of discovering requirements problems during testing, I can identify and address them before development starts. The result is a repeatable requirements-quality gate that brings QA thinking earlier into the software delivery process.
Business Impact
Where This Fits
Move quality earlier. Automate repetitive work. Keep humans responsible for quality decisions.
Instead of discovering requirements problems during testing, I identify and resolve them before development starts.