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AutoSmoke
Catch broken flows before your users do
Stop shipping broken flows. AutoSmoke is AI-powered smoke testing that actually uses your app like a real user. An LLM agent drives a real browser to verify your critical userflows(login, checkout, onboarding) after every deploy. No brittle selectors. No test scripts to maintain. Just describe what to test in plain English, and AutoSmoke clicks, types, and verifies it works. Can be scheduled but it integrates with your CI/CD too. Set up in minutes, catch regressions before users do.
Hey everyone! I'm Laszlo, the maker of AutoSmoke.
I built this because I kept living the same nightmare. Someone ships a "small change" and then Slack blows up because login is broken or checkout silently stopped working. We had E2E tests, but they were so brittle that maintaining them felt like a second job. Half the time we'd just skip them.
The other thing I kept seeing is teams moving incredibly fast with AI coding tools, shipping multiple times a day, but nobody is actually checking if the core flows still work. I talked to a founder whose signup was broken for three days before a user emailed them about it. No tests, no monitoring, just vibes.
Both problems pointed to the same question: what if the test could just *use* the app like a human does?
That's AutoSmoke. You describe your flow in plain English and an AI agent opens a real browser and actually does it. Clicks buttons, fills in forms, verifies things work. When something breaks, you get a video of exactly what went wrong. It plugs into your CI/CD with a GitHub Action so it runs on every deploy.
What flows would you test first?
About AutoSmoke on Product Hunt
“Catch broken flows before your users do”
AutoSmoke was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #162 on the daily leaderboard. Stop shipping broken flows. AutoSmoke is AI-powered smoke testing that actually uses your app like a real user. An LLM agent drives a real browser to verify your critical userflows(login, checkout, onboarding) after every deploy. No brittle selectors. No test scripts to maintain. Just describe what to test in plain English, and AutoSmoke clicks, types, and verifies it works. Can be scheduled but it integrates with your CI/CD too. Set up in minutes, catch regressions before users do.
On the analytics side, AutoSmoke competes within Developer Tools, Artificial Intelligence and Vibe coding — topics that collectively have 977.8k followers on Product Hunt. The dashboard above tracks how AutoSmoke performed against the three products that launched closest to it on the same day.
Who hunted AutoSmoke?
AutoSmoke was hunted by László Kiss. 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.
For a complete overview of AutoSmoke including community comment highlights and product details, visit the product overview.
László Kiss