An agentic quality verifier for developers and AI coding agents. Describe a test in natural language, and Kane CLI runs it in a real Chrome browser and returns pass or fail with shareable proof. No selectors to write. Local-first, free to start.
Every technology wave has the same shape. Capability jumps first. Trust catches up later. We saw it with cloud, and we are watching it again with AI.
The gap we kept seeing
⚡ AI writes the code in minutes now
🖱️ But someone still has to open the app and confirm it actually works
⏳ The building got fast. The assurance never did
That gap is the defining problem of this era of software, and it is why we built Kane CLI.
How it closes the loop
📥 Ingests your source or PRD
🧩 Designs the use cases and test scenarios
🌐 Runs them in a real Chrome browser, or on Android emulators and iOS simulators
📸 Returns an evidence pack, AC coverage, and a verdict
Not just "did it run". Did it work, and can you prove it. ✅
We believe the next generation of software teams will not be measured by how fast they build. Everyone will build fast. They will be measured by how fast they can trust what they built. 🚀
Would love to hear how your team is dealing with this gap.
The build-fast, trust-slow gap is very real. I like how Kane CLI focuses not just on running tests, but on producing evidence teams can actually trust and share.
How do you see Kane CLI fitting into an AI coding workflow,should testing happen automatically after every code change?
I really love KaneAI’s conversational approach to generating critical test scenarios from the provided documentation. It frees up my local machine’s resources while helping me explore and work with different aspects of the platform more efficiently. Overall, KaneAI has made the testing process smoother, faster, and more collaborative.
the machine-readable verdict for agent loops is the right instinct, that's the same gap I hit running voice model evals: a pass/fail with no provenance just means trusting the model again. does the evidence pack capture intermediate state, or just the final screenshot, when a flaky animation causes a false fail?
Congrats, team! How does Kane decide whether a natural-language test has actually passed when the page behavior is slightly different than expected?
the ask-tool pause on OTP/CAPTCHA instead of guessing is the right call. since the exported case replays deterministically, what happens when the site's UI shifts a little, a moved button or new copy, does it re-derive from the original NL description or does someone have to re-record?
AI coding agents desperately need something like this. Writing code is becoming easy; reliably verifying the result is becoming the bottleneck.
What happens when a test encounters a CAPTCHA, unexpected modal, or authentication challenge halfway through execution?
Launch day energy is real today 🎉
I have told the Kane story on stages and in campaigns for months, and the reaction is the same every time. People assume they will need to write code or learn a framework. Then they watch someone type a sentence in natural language, a real browser opens, and it comes back with an evidence pack and a verdict.
That moment when the room goes "wait, that's it?" never gets old.
And today the story got a new chapter: the same commands now run on Android emulators and iOS simulators too.
Even outside engineering, I use Kane CLI for my own repetitive browser work. That is the part I love most, it is not just for engineers. The Starter plan is free, so go break it and tell us what you think. The team is here in the comments all day.
Agentic mobile test was the missing piece of the puzzle. Kane CLI seems to be solving that perfectly well!
Does Kane handle logged-in flows automatically, or do we need to set up auth ourselves?
Hi everyone, I'm one of the engineers building Kane CLI. Good to finally have this out in the world.
The part I'm personally most proud of: we built it agent-native from day one. I've spent 2+ years shipping frontend at TestMu AI, and if that taught me anything, it's that writing UI was never the slow part, proving it still works after every change is. AI has made the writing nearly instant, which makes verification the real bottleneck. So we designed for it: every command can emit machine readable output, meaning it's not just humans in a terminal, your coding agent (Claude Code, Cursor, whatever you use) can invoke kane-cli, stream the run, read the verdict, and act on it inside its own loop. AI writes the code, Kane CLI verifies it in a real browser (or on mobile), and the agent gets machine-readable proof back. Closing that loop is what makes autonomous dev workflows actually trustworthy.
The other thing we obsessed over: a pass has to actually mean something. Every verdict ships with an evidence pack; screenshots, console logs, network responses; so a green check is never "the model felt good about it." You can see exactly what was verified, and when something fails you're not guessing.
It's local-first and free to start. Happy to answer any questions in the comments.
Big day for us at TestMu AI
I have watched Kane CLI come together from the inside, and the part that still gets me is watching it in action. You type what you want verified in natural language, a real Chrome window opens, it works through the flow, and comes back with an evidence pack and a verdict. No selectors written. No framework set up.
And the timing of this launch could not be better. As of today it does the same thing on Android emulators and iOS simulators. Same commands, same evidence, now on mobile.
The team has poured months into getting the details right, determinism, Autoheal, agent-native output, and it shows.
Proud of this one. If you ship with AI agents, or you are just tired of clicking through your app before every release, give it a run. First verdict lands in minutes.
Hi, I'm Mayank Bhola, Co-Founder and Head of Products @TestMu AI
It started with a pattern that would not go away. Agent ships the code. PR merges. Tests pass. Three days later someone opens the app and the button does not work.
Everyone kept asking how to make agents write better code. Wrong question. Agents could already open browsers and check their work. The output was the problem. Different result every run. No verdict you could trust. Loop it enough times to be sure and you have burned real money for a maybe.
So we set one non-negotiable bar: determinism
Same flow, same result, every time. A pass is granted only when the expected state is verified through explicit evidence:
DOM state and URL changes
Network responses
Screenshots and console logs
AC coverage behind every verdict
And as of today, that bar holds on mobile too
v0.8.1 brings the same verification contract to Android emulators and iOS simulators. Same evidence, same replay, same verdict you can defend.
This is the layer I wished existed every time a merged PR broke in production. Now it does, on web and mobile.
Testing across browsers and real devices already creates plenty of complexity. Adding agentic reasoning could make that easier to manage.
How much context can Kane understand from a PRD before generating the actual browser scenarios?
Could developers trigger Kane directly from CI/CD and block deployments automatically when critical browser workflows fail?
About Kane CLI on Product Hunt
“Natural language browser & mobile app tests from terminal”
Kane CLI launched on Product Hunt on August 13th, 2026 and earned 327 upvotes and 38 comments, earning #1 Product of the Day. An agentic quality verifier for developers and AI coding agents. Describe a test in natural language, and Kane CLI runs it in a real Chrome browser and returns pass or fail with shareable proof. No selectors to write. Local-first, free to start.
Kane CLI was featured in SaaS (43.6k followers), Developer Tools (517.5k followers) and Artificial Intelligence (475.9k followers) on Product Hunt. Together, these topics include over 245.4k products, making this a competitive space to launch in.
Who hunted Kane CLI?
Kane CLI was hunted by Rohan Chaubey. 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 Kane CLI stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Hi, I'm Jay Singh, Co-Founder of TestMu AI.
Every technology wave has the same shape. Capability jumps first. Trust catches up later. We saw it with cloud, and we are watching it again with AI.
The gap we kept seeing
⚡ AI writes the code in minutes now
🖱️ But someone still has to open the app and confirm it actually works
⏳ The building got fast. The assurance never did
That gap is the defining problem of this era of software, and it is why we built Kane CLI.
How it closes the loop
📥 Ingests your source or PRD
🧩 Designs the use cases and test scenarios
🌐 Runs them in a real Chrome browser, or on Android emulators and iOS simulators
📸 Returns an evidence pack, AC coverage, and a verdict
Not just "did it run". Did it work, and can you prove it. ✅
We believe the next generation of software teams will not be measured by how fast they build. Everyone will build fast. They will be measured by how fast they can trust what they built. 🚀
Would love to hear how your team is dealing with this gap.
Learn more: https://www.testmuai.com/kane-cli-ph/