Most testers won’t be replaced by AI.

But many will fall behind because they don’t evolve with it.

Episode #22 – How to Test as an Agentic Quality Engineer

Dragan Spiridonov, Founder of Quantum Quality Engineering, shares how AI is not replacing testers but elevating them into orchestrators of intelligent systems.

👉 Top 5 Advice to Become an Agentic QA Engineer:

✅ 1. Master the basics before the agentsStart with prompting → then context → then agents.

✅ 2. Invest in thinking, not just toolsCritical thinking, risk analysis, exploratory testing are differentiators.

✅ 3. Design systems, not just testsFrom executing test cases → to orchestrating agents doing testing

✅ 4. Build your own AI-powered QA projects
Small tools, experiments, or open-source projects to learn faster.

✅ 5. Verify everything (10% build / 90% validate)

Agentic QA is about designing strong validation loops.

Which of these levels are you currently at: AI Assistant, AI Augmented, or full Agentic QE?

Teams don't fail at AI adoption because of the technology. But because of how they evaluate and adopt it.

Geosley Andrades, Product Evangelist & Community Builder at ACCELQ, shares how Agentic AI is changing test automation.

And what QA teams need to know before jumping in.

👉 5 Mistakes Teams Make When Adopting AI Testing Tools:

⛔ Using AI at every place vs ✅ Know where AI actually solves a problem.

AI without the right context will hallucinate. Be skillful, not just enthusiastic.

⛔ Picking a tool before defining scope vs ✅ Define what you need to automate first.

Web? API? Mobile? Desktop? If the tool can't do it, you're wasting time evaluating it.

⛔ Going all-in at once vs ✅ Start with a proof of concept.

Give the tool your hardest test case. If it handles that, the basics are a given.

⛔ Using AI just to generate code vs ✅ Adopt a design-first approach.

AI-generated code without design principles creates tech debt, not solutions.

⛔ Ignoring where your data goes vs ✅ Check the architecture before you buy.

If your test data is going to a public LLM, you have a data breach waiting to happen.

Which of these mistakes have you seen on your team?

Connect with Goelsey or find out more:

• LinkedIn: https://www.linkedin.com/in/geosley/
• Personal Blog: https://geosley.blogspot.com/
• ACCELQ Website: https://www.accelq.com
• Blog (articles by Geosley): https://www.accelq.com/blog/autonomous-testing/

Today, Oleksandr Bolzhelarskyi, Director of QA & Release Management at Salesfloor, shares why successful releases are impossible without responsible testing and quality management, and how teams can stop firefighting production bugs and start shipping with confidence.

👉 5 Golden Rules for a Successful Release

⛔ Testing features individually → ✅ Testing the release as a package Features that work perfectly in isolation can break when merged together. Two developers changing the same component won't know about each other's work until it's combined. Always retest the full package.

⛔ Bug bashes → ✅ Combining structured testing with fresh eyes.

Involving non-testers brings valuable perspective, but it's not systematic. Bug bashes catch random issues, not targeted risks. Use them as a complement, never as your only release testing.

⛔ Testing everything → ✅ Testing based on risk / product knowledge You'll never have time to cover everything. Know your product architecture, understand what the new changes could break, and focus regression testing where the real risks are.

⛔ Release pressure → ✅ Communicating untested risks clearly

Pressure to ship means the feature matters. Instead of pushing back emotionally, tell your manager: here's what we tested, here's what we didn't, and here's what could go wrong. Let them make an informed decision.

⛔ Allowing "one last quick fix" → ✅ Enforcing a strict code freeze Last-minute changes during regression testing cause the biggest surprises. Say no. If it's urgent, ship it as a hot fix after the current release is done.

Connect on LinkedIn: https://www.linkedin.com/in/oleksandr-bolzhelarskyi/