“The better we ask, the better we test.”
AI is changing how QA engineers work — not by replacing us, but by extending what we can do.
As a QA Lead working with automation teams, I’ve spent months experimenting with AI tools like ChatGPT and Claude for real QA workflows — from generating Cypress tests to debugging flaky suites.
What I learned is simple: prompt engineering is the new test design.
💡 What’s “Advanced Prompting” in QA?
Basic prompting is just asking a question and hoping for a good answer.
Advanced prompting is when you teach the AI to think like a QA engineer — by adding roles, context, examples, and constraints.
It’s like writing acceptance criteria for your AI.
⚙️ Real Scenarios Where AI Helps in Automation QA
Here’s how I now use AI in my daily QA work:
- Generate maintainable test scripts in Cypress or Playwright
- Diagnose flaky tests and suggest refactors
- Create synthetic test data with realistic edge cases
- Summarize regression results for weekly reports
- Refactor old automation code for readability
Let’s look at a few examples 👇
🧠 My Advanced Prompt Framework
Every prompt I use now follows the same pattern:
Role → Context → Constraints → Output Format
For example:
Act as a senior QA automation engineer.
Based on the acceptance criteria below, generate Cypress tests using the Page Object Model.
Include before/after hooks, positive + negative flows, and clear assertions.
Output: code blocks with file paths and brief comments.
Acceptance criteria:
User can log in using email and password. Invalid credentials should show an error message.
This small structure makes a huge difference in how AI interprets your intent.
🔁 Before vs After
Simple prompt:
“Write Cypress tests for login.”
🧩 Result: 1–2 generic tests, no structure, hardcoded selectors.
Advanced prompt:
“As a QA automation engineer testing a SaaS app with MFA login, write 5 Cypress tests using data-cy selectors and intercepts.
Include both valid and invalid flows, and verify API + UI responses.”
✅ Result:
Structured Page Object tests, reusable code, coverage for both UI and API layers.
🧩 Real Example — Diagnosing Flaky Tests
Prompt:
Here’s a failing Cypress test log.
Identify likely root causes (timing, async, selectors).
Propose fixes and refactor the test for reliability.
AI output:
- Found that waits were inconsistent (
cy.wait()instead ofcy.intercept()) - Suggested refactoring selectors to
data-cy - Recommended isolating login flow from other suites
We applied it — and flakiness dropped by 40% in the next sprint.
📘 My QA Prompt Library
To make this process repeatable, I built a public repo:
👉 QA Advanced Prompting
It includes:
- 10+ tested prompts for automation QA
- Examples for Cypress, Playwright, and API testing
- A few ready-to-copy JSONs for Postman
- Templates for AI-based code reviews
Feel free to fork it, test it, and contribute your own prompts.
🧩 Why It Matters
QA is evolving — and prompt engineering is part of that evolution.
It’s no longer just about finding bugs; it’s about designing intelligent test systems that learn, adapt, and assist.
“Prompting is not about tricking AI — it’s about teaching it to reason like a tester.”
If you’ve ever debugged flaky tests at 2 AM, you’ll appreciate having an AI co-tester.
💬 Key Takeaways
- Advanced prompting = structured thinking. Treat prompts like test cases.
- Give context. Framework, domain, and constraints matter.
- Iterate. Refine prompts the same way you refine tests.
- Reuse. Keep your best prompts in version control.
🚀 Ready to Try?
🧩 Explore the repo: QA Advanced Prompting on GitHub
🧠 Start building your own “AI QA Library” — it’ll become your best automation buddy.
Authored by Dasha Tsion — QA Lead, automation enthusiast, and believer that AI should work with us, not instead of us.
Top comments (1)
Dasha, this is an excellent guide for QA engineers! Turning AI into a testing partner is such a clever approach. Your examples of advanced prompting and practical workflows show how AI can enhance efficiency and accuracy. Thanks for sharing actionable insights that can truly transform testing practices!