QA.tech runs dynamic regression and exploratory testing on every PR preview – automatically. AI agents validate your changes against real user flows in a real browser, posting results back to the PR before anyone reviews or merges. Every failure comes with screenshots, logs, and network activity so your team debugs fast. Push a new commit and it re-runs. Merge only when tests pass.
running AI regression + exploratory tests on every preview deploy is such a good use of agent time — way more valuable than yet another chat ui. how flaky are the runs in practice? curious if you've had to build in any self-healing or retry logic for transient UI stuff.
Congrats on the launch! This is a compelling take on QA automation. I'm curious about how QA.tech handles the nuances of testing products with complex user flows or those requiring specific business logic validation. Do your agents learn from existing test cases, or do they generate test scenarios from scratch by exploring the product?
how do you handle flaky tests eating the pr signal?
every team i've seen roll out automated pr checks ends up with devs reflexively re-running until green, at which point the whole system is just theater. wondering whats the stance is
Ahh that sounds cool. so is it like: 1. Login commit change. 2. AI writes tests to focus on login UX 3. Runs tests in headless CI browser. 4. Shhows result in pr?
PR review is the bottleneck every team complains about but no one fixes. Curious what the false-positive rate looks like in practice — does the agent flag cosmetic changes (whitespace, renames) as issues, or only real regressions? Congrats on launch 🚀
"That's weird. It works on my machine." If I had a cent for every time I've heard that, I wouldn't need to work anymore.
We're fixing one of the most painful parts of development: testing new things while they're still being built.
From the developer side, you want fast feedback, clear repro steps, and all of it while you're still in the zone. From the quality side, we bring your requirements into one place and help make sure every PR meets the bar, whether it was written by a human or generated by AI.
Built on Vercel (vercel functions, ai-sdk, nextjs hosted on vercel) and works out of the box with Environments and Preview Deployments.
Give it a try and let me know what you think!
About Visual PR Testing with AI on Product Hunt
“Validate every PR with AI that runs tests for you”
Visual PR Testing with AI launched on Product Hunt on April 17th, 2026 and earned 133 upvotes and 14 comments, placing #11 on the daily leaderboard. QA.tech runs dynamic regression and exploratory testing on every PR preview – automatically. AI agents validate your changes against real user flows in a real browser, posting results back to the PR before anyone reviews or merges. Every failure comes with screenshots, logs, and network activity so your team debugs fast. Push a new commit and it re-runs. Merge only when tests pass.
Visual PR Testing with AI was featured in Developer Tools (511.1k followers), Artificial Intelligence (466.3k followers) and Vercel Day (4 followers) on Product Hunt. Together, these topics include over 153.1k products, making this a competitive space to launch in.
Who hunted Visual PR Testing with AI?
Visual PR Testing with AI was hunted by fmerian. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Reviews
Visual PR Testing with AI has received 7 reviews on Product Hunt with an average rating of 4.29/5. Read all reviews on Product Hunt.
Want to see how Visual PR Testing with AI stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
fmerian
running AI regression + exploratory tests on every preview deploy is such a good use of agent time — way more valuable than yet another chat ui. how flaky are the runs in practice? curious if you've had to build in any self-healing or retry logic for transient UI stuff.