So the cat's out of the bag: after some initial skepticism, we're all coding with AI now, and wow, it's good. Scary good. Maybe you're using it for boilerplate, or maybe you've morphed into a vibe-coding wizard. Either way, you're shipping features faster than ever.
But there's that nagging question: Is my code actually any good?
The gap between "this looks fine" and "this is bulletproof" is where stress creeps in. No one likes the risk of shipping bugs that make your next release memorable, for all the wrong reasons.
QA.tech is the AI tool with QA expertise that helps you bridge the gap from vibe code to reliable code, one test at a time. So you can ship with speed and confidence.
Building Quality Code with QA.tech
In a world where development is being fast-tracked with AI tools like Cursor and Zed, it’s easy to lose oversight of your code’s quality.
You could wrestle Selenium, Cypress, or Playwright, investing hours in brittle setups, or you skip E2E testing altogether. Neither option gives you full confidence in your code.
This is where QA.tech comes in, it bridges the gap between "this seems fine" and "we're ready to ship". There's no learning curve or brittle tests, just high quality insights instead instead of "FAIL” and “PASS”.
To prove I'm not just hand-waving, I'm going to put QA.tech to work on my hobby project: A ticketing app. It has unit tests but zero E2E testing, making it the perfect test subject for some QA.tech wizardry.
Why We Need End-To-End Testing
When done right, E2E testing is one of the best front-line defenses for code quality. In today’s fast-moving world of competing products, even a little friction can trigger churn, so catching issues before they hit production matters more than ever before.
A solid E2E setup should:
- Cover your app’s critical user journeys.
- Help you find and fix issues before they’re deployed.
- Keep tests reliable, so you can quickly see if code or UI changes are causing issues.
For the latter point QA.tech outshines traditional frameworks thanks to its ability to adapt automatically. This saves teams hours of work and helps them ship new features smoothly.
Getting Started With QA.tech
Now that we’ve covered why QA.tech belongs in our development flow, it's time to create our first test. The good news is QA.tech's docs and onboarding cover the whole process, so we're not flying blind.
Creating A Test Case
Okay, it's time to see if our ticketing app really lets people buy tickets.
Once you're signed up, head to "Test cases" and click "Add Test Case". QA.tech can scan your app and suggest tests automatically, which is handy when getting started, but since we know exactly what we want to test, let's create our own.
A test case has a few key fields:
- Name: What we're calling this test.
- Goal: What we expect the user to be able to do.
- Expected Result: What success looks like.
- Run After: Dependencies on other tests.
There are also advanced options, like picking which agent to run the test with (Claude, for example).
For our first test, we'll keep it simple:
- Name: Buy a ticket
- Goal: "As a user I should be able to buy a ticket."
- Expected Result: "The user can successfully purchase a ticket and view their purchase info."
And that's it, we just need to hit Generate Test, and we're off!
Reviewing Our Test
Once we’ve submitted the Add Test Case form, it only takes QA.tech takes few moments to generate an E2E test.
You can watch your test generation in real time as QA.tech analyzes your app, and starts creating the steps needed to achieve the test’s Expected Result:
When the test is finished generating, QA.tech outlines each step it took, and we can edit, remove, or add to those steps if needed. But things took an interesting turn while generating the test case: our first run failed 😱!
This failure isn't a dead end, though. QA.tech identified a huge bug in our booking flow. It showed exactly why the test failed, let us click through each action it took, and even gave us console and network data to debug.
Running the test again confirmed this was not a one-off failure. We'd added authentication to the booking form, which blocked the "buy a ticket" user journey.
So let’s give the details to Cursor, and ship a fix before asking QA.tech to run the test again.
When re-running our test, we don’t even have to worry about manually modifying our test steps because QA.tech will modify them for us as it tries to make a successful booking:
Et voilà, the test passed! What would've been a nasty oversight was caught and fixed in minutes, with zero manual test writing. Honestly, this really impressed me (and I'm not easily impressed).
We can now review our test’s steps and, if everything looks good, activate it.
Managing QA.tech Tests
Once you've got a few active tests up and running in QA.tech, you can start sorting them into Scenario Groups. These are related tests that align with real user flows, such as "buy a ticket" or "update profile".
Instead of running everything individually, or with no particular order, you can run a whole group as a Test Plan, which makes it easier to understand user journey behavior from start to finish.
QA.tech’s Test Plans help you scale as your suite grows and ensure you are testing the product the same way people use it.
Keep Tests Smart With Project Context
You can provide project knowledge to help QA.tech provide smarter test scenario suggestions and build better tests.
This can include, for example, the kinds of data you want QA.tech tests to input into your application, actions you don't want QA.tech to take (don't press the red button!), links to documentation, and which subdomains QA.tech can scan.
QA.tech uses this context when generating and running tests, so they stay relevant to your app as it evolves, meaning your tests can adapt to changes automatically without the maintenance that traditional E2E frameworks require
QA Is Essential For Stable, Scalable Apps
And that’s the end of our whistle-stop tour of QA.tech. You've seen how easy it is to leapfrog legacy E2E frameworks and move to a smarter, more adaptable approach to QA, and one that gives you reliable, maintainable, and resilient testing without the pain.
QA.tech keeps the focus on what matters: your users, not brittle frameworks or endless refactors. QA.tech helps turn "vibe code" into production-ready code, regardless of how much AI was involved along the way.
Proper E2E testing is the backbone of stable, scalable applications. QA.tech makes it easier to achieve this, giving you confidence, control, and a little peace of mind every time you hit deploy.
From Vibes to Verified: Adding QA to Your Flow
I've shown you how I've used QA.tech on a simple ticketing app, but that's just scratching the surface of what it's capable of. If you're curious about more complex real-world use cases, QA.tech has some great case studies you can read through.
In my opinion, though, the best way to understand QA.tech is to try it yourself. The setup is so minimal that it'll only take several minutes for you to get an idea of its value.
Top comments (5)
oh nice, I am Solutions Engineer at QA.tech and I am usually the first person our users go to when they have feedback about the product or want help with adoption. I guess, you can ask me anything :)
Great insights 🔥.
This is brilliant! 👏
I can now finally finish up my app idea! I was always struggling with testing user flows, as inevitably Cursor creates bugs even on simple projects.
Awesome post, thanks for sharing
Love this! AI + QA synergy is something I’m deeply passionate about too. It’s amazing to see real examples like this showing how smart testing tools can actually reduce release anxiety 😅👏