Andrew Pallant

Software & Web Developer

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ChatGPT to Create Acceptance Criteria

Physical Link: ChatGPT to Create Acceptance Criteria

Today’s Learning

Today, I took a business requirement and put it into ChatGPT. I created a couple of simple prompts. The first prompt created acceptance criteria to make the software developer successful. The second prompt was to create test cases.

Surprisingly enough, it generated some pretty accurate results.

Could this be used in the future? YES

The answer yes has one caveat. You should still refine the results by adding more prompts. Once you have the refinement that is good for your business and platform, you still need a human to groom and clean up. The human needs to know the system, validations required and the regulatory requirements for your business. It would help if you also had a developer and QA review the test cases generated. After the review, you can add more criteria and prompts to perfect your output over time. You will never eliminate the need for a human, but you could certainly reduce the time spent.

  1. How does ChatGPT handle complex or domain-specific acceptance criteria? While ChatGPT excels at generating text, it may struggle with intricate or specialized requirements. For complex scenarios, human expertise remains essential. Leveraging ChatGPT as a starting point and refining its output collaboratively can strike a balance between automation and domain-specific nuances.
  2. What are the potential risks of relying solely on ChatGPT for acceptance criteria? Relying solely on AI-generated criteria poses risks:
    • Ambiguity: ChatGPT might produce vague or ambiguous statements.
    • Omissions: It could miss critical conditions or edge cases.
    • False Positives: Generated criteria may inadvertently approve incorrect behavior.
    • Lack of Context: ChatGPT lacks context awareness, leading to oversights.
  3. How can organizations effectively integrate ChatGPT-generated acceptance criteria into their existing development workflows? Integration involves:
    • Collaboration: Engage developers, testers, and domain experts. Discuss and refine criteria.
    • Validation: Test the generated criteria against real-world scenarios.
    • Feedback Loop: Continuously improve ChatGPT’s output based on practical usage.
    • Human Oversight: Ensure human review to catch any AI-generated gaps.

Remember, while ChatGPT offers valuable assistance, a thoughtful approach ensures successful adoption in software development processes.

Always be curious! Always try something new! Refine, measure and tweak.

If you do not succeed, innovate!

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