{"id":1833,"date":"2026-09-21T10:30:00","date_gmt":"2026-09-21T10:30:00","guid":{"rendered":"https:\/\/bugsmash.io\/blog\/?p=1833"},"modified":"2026-09-13T14:53:39","modified_gmt":"2026-09-13T14:53:39","slug":"ai-prototype-feedback-client-review","status":"publish","type":"post","link":"https:\/\/bugsmash.io\/blog\/ai-prototype-feedback-client-review\/","title":{"rendered":"How to Get AI Prototype Feedback From Clients Before You Write a Single Line of Code"},"content":{"rendered":"\n

The workflow just flipped. A year ago, “prototype” meant a static Figma file with a few clickable hotspots. Today, you can describe a product to Claude, Lovable, v0, or Bolt and watch a working version load in your browser three minutes later. That’s a real shift \u2014 but it leaves one gap most teams haven’t figured out yet: how do you get useful AI prototype feedback<\/strong> from a client before you turn any of that into production code?<\/p>\n\n\n\n

This post walks through why that gap exists, what “good feedback” on an AI-built prototype actually looks like, and a practical workflow you can steal for your next project. The short version: build fast, share faster, collect feedback<\/a> exactly where the reviewer is looking, and only start writing real code once the client has pointed at the button they want moved.<\/p>\n\n\n\n

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