Collaborative review for AI-generated apps
AI tools generate working apps, websites and prototypes in minutes. What they don't generate is agreement: the review step where teammates, stakeholders and clients look at the result, give feedback, and decide what ships. This page explains the collaborative review workflow for AI-generated software, why the usual tools fail at it, and how Capsule runs the whole loop on one link.
Why reviewing AI-generated apps is different
Traditional review tooling assumes one of two things: the artefact is source code (code review), or it is a deployed product (staging environments, QA). AI-generated apps fit neither. They are produced in seconds, change with every prompt, and the people who need to review them — a product manager, a client, a founder — care about the rendered page, not the diff.
So teams fall back to improvised workflows: screenshots pasted into Slack, Loom walkthroughs, screen-shares, zip files. Feedback arrives detached from the thing it describes. By the time it's actioned, the AI has generated three newer versions and nobody is sure which one was reviewed.
Reviewing AI-generated HTML well needs three properties the improvised stack can't provide:
- The review surface is the live page — feedback attaches to the element it's about, in the state the reviewer saw it.
- Iteration is part of the loop — feedback flows back to the AI agent that generated the app, and the fixed version lands where reviewers already are.
- Publication is a decision — a human approves a specific version; that approval is recorded.
The collaborative review workflow
Capsule structures review around five steps. The same loop works for a one-page prototype and a client-facing dashboard.
Generate
Build with AI tools like Claude, Cursor, Lovable or v0.
Share
Publish to one private browser link — no zip files, no hosting setup.
Review
Reviewers click and comment directly on the live page.
Iterate
Your AI agent reads the feedback and proposes fixes; you decide what ships.
Publish
Approve the version and the same link updates for everyone.
1 · Generate
Build with whatever produces the artefact: Claude Code or Claude artifacts, Cursor, Lovable, v0, Windsurf, or plain prompting. Capsule doesn't generate anything and doesn't care what did — it takes HTML or Markdown as-is.
2 · Share
Your agent publishes the artefact with one tool call (over MCP or the REST API). The result is a live, browser-based share link — optionally password-protected or time-limited. No hosting, no build pipeline, no "can you send me the file again".
3 · Review
Reviewers open the link and comment directly on the page — on the button that's mislabeled, the chart that's wrong, the section that reads badly. Comments carry their context with them, so feedback stops being an archaeology exercise.
4 · Iterate
The feedback is readable by your AI agent. It collects open comments, proposes a fix for each, and you — the builder — decide which to apply. The approved changes are pushed as a new version on the same link, and each addressed comment is marked for the reviewer to accept or iterate on.
5 · Publish
When reviewers accept and the builder approves, that version is the published one. Version history shows exactly what changed between review rounds, and the audit trail shows who approved it.
What makes a good AI app feedback workflow
Whether or not you use Capsule, a collaborative review workflow for AI-generated apps should pass these tests:
- Zero-setup sharing. If sharing a prototype takes more than a minute, review happens too late to matter.
- Feedback in context. A comment should point at the element it concerns, not describe it from memory.
- One canonical link. Reviewers should never wonder whether they're looking at the current version.
- Agent-readable feedback. If your AI can't read the review comments, a human re-types them into the prompt — that's the broken loop again with extra steps.
- Human approval. AI proposes; a person decides. The publish step is where accountability lives.
Capsule was built to pass all five. It is not an AI tool and not a website builder — it is the collaborative layer between the tools that generate software and the people who decide it's ready.
Review workflows by ecosystem
The loop is the same everywhere; the generate step differs. Pick your tool:
Frequently asked questions
What is collaborative review for AI-generated apps?
It is the workflow of putting an AI-generated app, website or prototype in front of the people who need to evaluate it — teammates, stakeholders, clients — so they can give feedback in context, see iterations, and approve a final version. Capsule runs this loop on a single live share link instead of screenshots, video walkthroughs and chat threads.
How do I review an AI-generated app without deploying it?
Publish the generated HTML to Capsule from your AI agent. It becomes a live, browser-based page on a private share link immediately — no hosting, build pipeline or zip files. Reviewers open the link and comment directly on the page.
Does Capsule work with Claude, Cursor, Lovable and other AI tools?
Yes. Capsule is tool-agnostic: anything that produces HTML or Markdown can be published. Agents connect over MCP (Claude Code, Cursor, VS Code, Windsurf, Cline, Zed and others) or the REST API, so the iterate step flows feedback straight back to whichever tool generated the app.
How is this different from a staging environment or a code review tool?
Code review evaluates source; staging environments require deployment infrastructure and still leave feedback in another tool. Collaborative review evaluates the rendered result — what stakeholders actually experience — with comments attached to the page itself and an approval step before the version ships.
Who approves what ships?
A human. Your AI agent proposes fixes based on reviewer feedback, but nothing is published until the builder approves it. Every version is kept, so you can always see what changed between review rounds.