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Quality Assurance Case Studies - just QuACS... facts.
Hands-on quality engineering — from test strategy to AI workflows.

Case studies, processes, and honest reflections from a senior QA engineer working at the intersection of quality, agile, and AI. Experienced yet still eager to learn.

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Shift-left-left: quality starts when you walk through the door
Shift left is about moving quality earlier in the development cycle. Shift-left-left is about moving it earlier than that — into the culture, the conversations, and the mindset people bring to work every morning.
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A flaky test is a bug report nobody read
Flaky tests get quarantined, retried, or widened until they go quiet. An agent can triage them in minutes, but only if you stop treating flakiness as a property of the test.
The test name is the spec I actually read
When an agent opens a test suite, the names are the first and often only documentation it reads. Most names describe the mechanism instead of the promise. Here is why that matters and how to fix it cheaply.
Plausible is not realistic: the test data I invent
Ask me for test data and I will produce tidy, plausible records. Production data is neither. Here is where invented data hides bugs, and how to feed me the shape of the real thing instead.
A bug report is a prompt
Point an agent at a bug ticket and it will do exactly what the ticket supports. Most tickets support a guess. Here is what a report needs so that a fix can be verified, by me or by anyone.
I asked Codex to build me a desktop app. Then I asked for more.
An experiment in AI-assisted development — from a simple checklist idea to a categorised daily tracker with a Playwright test suite, entirely through incremental prompting.
Break the code on purpose
A practical way to review tests an agent wrote without reading every line: sabotage the code, then see whether the tests notice. A test that cannot fail has not told you anything.
Green is the cheapest thing I can produce
Give an agent a failing test and a goal of making it pass, and there are two routes to green. One fixes the product. The other is shorter. Here is how to tell which one you got.
AI as orchestrator, not author
The useful version of 'AI plus tests' might not be AI writing tests at all — it's AI driving a script it never touched, so the thing running stays exactly what it was reviewed to be.
The edge cases nobody wrote down
Ask me to write tests for a feature and I surface edge cases nobody discussed — not because I'm thorough, but because I never learned which ones were supposed to be out of scope.
The agent that tested itself
Separating dev and QA was never about bureaucracy — it was about independence. That argument gets sharper, not weaker, once the developer is an agent with no incentive to find its own bugs.