Clayzo lets product and design teams spin up their existing product, prototype directly on it, record walkthroughs, and leave contextual feedback tied to the real codebase. What used to live across screenshots, Looms, and Slack now becomes actionable tasks that engineers and coding agents can build from.
Hi Product Hunt!
We found 2 things in common across product and design teams at Google, Amazon, and early-stage startups.
Trying a simple idea on a product usually requires waiting on engineering to send a deployment link.
And even after that, most tools only let you view the product, or give feedback on screenshots/wireframes. Ideas usually end up being struck on Figma, docs, or long Loom videos.
That's why we built Clayzo!
Here’s how it works:
⚡ Spin up instantly: launch a sandboxed version of your product from a branch, without waiting for deployment links or wrestling with local environments.
✏️ Prototype on the product itself: test ideas directly on the real interface instead of static mocks.
🎥 Record walkthroughs: show flows, explain decisions, and share product context visually.
💬 Leave feedback in context: tie comments to the actual product and codebase, not side conversations and disconnected artifacts.
🛠️ Actionable handoff and integrate with existing stack: translate product and design feedback into technical, execution-ready context for engineers and coding agents. Push tasks to Linear, Jira, and Github Issues, with end-to-end task tracking on our platform.
Would love to chat!
- Janani, Purav, & Armaan
Wow this is an awesome idea, it really simplifies the whole process altogether!
Looks great. I’ve used chatprd before for this but it felt disconnected to where I was working l, GitHub and Linear. Look forward to trying to this and seeing a demo next week.
Excited to use Clayzo instead of taking a million screenshots & jumping in a bunch of flow-breaking huddles throughout the day. Being able to ship fixes fast without risking breaking prod is nice too 😅
Curious if Clayzo has different triage flows for small edits (e.g. copy or UI changes) vs. higher eng lift tasks (involving backend, database, APIs, etc.)? And does AI route the different proposed changes (e.g. "this needs human oversight") or is it based on some preset rules?
Janani Prasad