Use an AI model like GLM 5.2 to analyze an entire codebase, summarize its architecture and recent changes, and then generate a visual HTML report to share with your team.
Ensure your AI model (e.g., GLM 5.2) is configured in your editor (like Cursor) and has access to your project's full codebase.
Use a prompt to ask the AI to explore the codebase and provide a summary of its architecture and recent development activity.
This is the chat, PRD code base. Please explore it and tell me a little bit about its architecture and the most recent things we have been shipping on this code base.Read the AI's initial analysis to verify its understanding of the stack, architecture, and recent work.
Ask the AI to convert its analysis into a visual HTML page that communicates the app's architecture and product strategy.
Turn this into an HTML page that can communicate the overall architecture of the app and give a sense of the upcoming roadmap. You can use whatever components you want to make this look good and communicate to me the end developer, the major pieces of the architecture and product strategy. Give me a page to pull up when it's ready to review.Open the generated HTML page to assess its design, structure, and content. The model may even correctly infer brand colors and roadmap themes.
Leverage an AI coding assistant like Claude Code to implement a Test-Driven Development (TDD) process. This workflow allows you to reproduce, fix, and verify bug fixes with incredible speed and accuracy.
Learn Gusto's radical approach to building a new product line in 10 weeks by ditching traditional tools like Jira and Figma, and relying on a perma-Zoom room and an AI coding assistant for rapid development.
Set up a long-running AI task in Cursor to autonomously pull error logs from Sentry and Vercel, analyze them, and generate a prioritized bug-fixing plan, including surfacing critical P0 bugs.
Join 100,000+ product managers who use ChatPRD to write better docs, align teams faster, and build products users love.