AI Wrote the Tests. Now What? A Developer’s Guide to Sanity-Checking AI Outputs

By Igor Goldshmidt, Testing & Quality Engineering Expert

TL;DR

If you’re a developer using GenAI tools to write your tests — don’t trust green test reports blindly. This article explains how the Psychology of Testing can help you critically review AI-generated tests, avoid false confidence, and stay in control of quality. It’s not about more tests. It’s about better thinking.

1. The Situation: Devs Are Testing on Their Own

In today’s Agile teams, especially in startups and cross-functional squads, developers are often responsible for testing their own code. GenAI tools like ChatGPT, Copilot, or Diffblue make it easy to generate test cases in seconds. But fast doesn’t always mean safe.

2. The Challenges We Meet

• Automation without validation: AI tends to focus on happy paths and misses edge cases.
• False sense of confidence: A green report doesn’t mean the app is safe to ship.
• Loss of critical thinking: Developers stop questioning when AI provides answers.
• Mental overload: Switching between coding and testing kills focus and quality.

3. One Powerful Tool: The Psychology of Testing

This is where the Psychology of Testing comes in — a human-focused discipline that helps you stay sharp, curious, and skeptical when using AI. It’s not about feelings. It’s about awareness.

4. How It Helps

• Teaches you why we overtrust confident-looking results
• Fights automation bias and confirmation bias
• Reframes testing from “running checks” to “challenging assumptions”
• Gives you tools to review AI output with a quality mindset

5. What Is the Psychology of Testing

It’s not some abstract academic field. It’s a practical set of skills:

• Spotting cognitive traps like anchoring or overconfidence
• Managing your cognitive load and energy
• Using emotions as signals (confusion = UX problem)
• Applying Bolton’s testing frames: Intention, Discipline, Testability, Realization
• Practicing empathy — with the user, with the system, and even with yourself

6. How to Implement It in a Dev Workflow

• Review for bias: Are your tests only covering the expected?
• Manually add edge cases AI might miss
• Treat each test as a hypothesis, not a fact
• Focus on coverage value, not just quantity
• Use emotion: if something feels wrong, it probably is
• Reduce cognitive overload: test in short, focused blocks
• Build an AI-test review checklist

7. 5 Practical Tips

1. Visualize your testing strategy — even a mind map helps expose gaps
2. Use double-loop thinking — not just “why did the test fail”, but “why are we testing this way?”
3. Apply STOP: Stop, Think, Observe, Plan — before running a full test suite
4. Switch roles: one dev writes, another reviews — independent review = better bugs
5. Prompt with testing frames: e.g., “Check as a user with accessibility challenges”

8. What’s Next?

If you’re already using GenAI for testing, your next step is to learn how to evaluate and improve what the AI gives you. Psychology of Testing gives you the mental model to do that. Don’t just consume AI output. Be its psychologist.

Next article coming soon: “How to Manage Cognitive Load While Testing as a Developer: A 20-Minute Practical Guide.”

At Skipper Soft, we help teams design scalable test strategies that align testing levels with business risk. Whether it’s an audit, a strategy session, or a hands-on workshop — we build systems that ship with confidence.