CodeCanary watches your session replays and conversion funnels to look for: 1. bugs, 2. UX friction, and 3. conversion optimization ideas. Once it finds an opportunity, it creates a pull request in the style of your existing pull requests.
Hi Product Hunt 👋
Your session replays are full of information on how to improve your product—where users get stuck, where they get lost, what bugs they encounter.
But, there aren't enough hours in the day to watch every replay. And, even if you could watch all the session replays, the list of things to work on would be so long that you would never be able to get to them all.
So, we built CodeCanary to both identify what to work on and do the work for you.
We spent a few years building map software where bugs and UX improvements stopped us from working on more ambitious projects. We wanted something which would free up our attention without sacrificing product improvements—so we built it!
With CodeCanary, you can always be A/B testing your conversion and keep bugs out of your product, all on autopilot.
If you want to try CodeCanary, we'd love to chat.
Thank you so much for checking out CodeCanary!
The problem you are describing is real and I felt it building DocMetrics. You collect all this user behaviour data — session replays, clicks, drop-offs — and then it just sits there because actually watching hours of recordings and turning them into actionable fixes is a full time job on its own. The gap between having the data and doing something with it is where most small teams lose. The A/B testing on autopilot angle is what catches my attention most because running proper experiments usually requires dedicated engineering time that solo founders and small teams simply do not have. Congrats on shipping this — curious what kind of bugs you find most commonly in session replays that developers would never catch through normal testing.
About CodeCanary on Product Hunt
“Turn session replays into revenue”
CodeCanary launched on Product Hunt on April 24th, 2026 and earned 59 upvotes and 2 comments, placing #25 on the daily leaderboard. CodeCanary watches your session replays and conversion funnels to look for: 1. bugs, 2. UX friction, and 3. conversion optimization ideas. Once it finds an opportunity, it creates a pull request in the style of your existing pull requests.
CodeCanary was featured in User Experience (364.9k followers), Analytics (171.5k followers) and Software Engineering (42.4k followers) on Product Hunt. Together, these topics include over 50.3k products, making this a competitive space to launch in.
Who hunted CodeCanary?
CodeCanary was hunted by Michael Egan and Garry Tan. 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.
Want to see how CodeCanary stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Michael Egan,
Garry Tan