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Arrange the terminal, editor, and live preview side by side. Start from a dedicated prototype directory so you can read the plan, inspect changes, and see the result without losing context.
Turn a spoken product idea into a working prototype by pairing plan mode with repository context, a live preview, and browser checks the agent can run without handing every validation step back to you.


Source episode · 10:52
How Notion Designs with AI: Brian Lovin's Prototype Playground and Claude Code Workflowswith Claire Vo
Brian creates a podcast player prototype with Monologue and Claude Code, reads the plan, relies on shared and local Claude context, and teaches the agent to lint and test the browser interaction itself.
A working podcast detail prototype with video, audio, episode metadata, and a confetti interaction on play.
Anthropic AI assistant
AI-first code editor
Step by step
Follow the sequence once, then adapt the prompts, checks, and handoffs to your own setup.
5 steps
Arrange the terminal, editor, and live preview side by side. Start from a dedicated prototype directory so you can read the plan, inspect changes, and see the result without losing context.
Speak or type the product idea in concrete UI and behavior terms. Name the page, required content, interactions, and one memorable detail rather than dictating the implementation.
Dictation is useful when the idea is easier to describe aloud, but the value comes from concrete behavior and context.
Switch Claude Code to plan mode. Read the proposed files, dependencies, component structure, and validation approach before allowing edits. Correct anything that conflicts with the repository or expands the scope.
Plan a podcast episode detail prototype in this repository. Include a video player, audio player, title, description, and confetti when either player starts. First inspect the repository instructions and existing patterns. List the files to create or change, dependencies, component structure, interaction state, and browser checks. Do not write code yet.
Reading the plan is a critical step. With a little development knowledge, you can catch logical errors early and save significant debugging time.
After the plan is sound, give the full request and let the agent implement it inside the assigned directory. Keep shared repository rules in CLAUDE.md and user specific paths or boundaries in an uncommitted local file.
Build a prototype in the How I AI directory for a podcast episode detail page. Include a video player, audio player, episode title, description, and confetti when play begins. Follow the approved plan and the repository instructions.
Have the agent run lint and type checks, launch the prototype, open it with browser tooling, click play, inspect console errors, and confirm the media controls and confetti. Review the working result and code together.
Turn an idea into a PRD, user stories, and a plan.
After the steps
How to recover when the loop fails and where human judgment helps.
Recover
Keep building

Use a hybrid AI workflow to bridge design and development. Generate high-level design concepts and tokens with Claude, then use Codex for robust implementation of the technical components in your codebase.

Implement a QA loop for AI-generated code using Devin. This playbook combines automated code reviews with an agent-recorded video walkthrough for visual verification, ensuring high-quality merges at scale.

Build a reusable 'Watchdog' playbook in Devin to automatically monitor customer accounts. The agent proactively checks for errors, synthesizes a prioritized list of critical issues, and saves you time.
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