Trae+Claude Code Product Manager Practical Combat: AI automatically organizes requirements, writes PRDs, generates interactive prototypes, syncs with TAPD, and improves work efficiency

I. Course content overview

A practical course for product managers, AI product developers, and enterprise digital teams, through65 systematic lessons, using a points redemption mall as a complete case study, taking you from zero to mastering the entire process of AI-assisted product design, requirements analysis, document writing, prototype creation, project collaboration, and product delivery. The course first explainsthe core capabilities of an AI product manager, the SIDE four-step closed-loop methodology, and the installation, configuration, and use of tools such as Trae, Claude Code, Gitee, Pencil MCP, and TAPD MCP; then, starting from real business requirements, you will learn how to use AI to complete requirements collection, pain point analysis, MRD reading, PRD product requirements document writing, and 14-dimensional quality review, reducing missed requirements. It then explains in depthpage specification documents, AI-generated HTML interactive prototypes, HTML-to-Pencil design file conversion, sitemap creation, and design review, enabling product solutions to quickly become presentable and discussable design results. The course also teaches you to use AI to write user stories and, through TAPD, achieve requirements synchronization, task management, and team collaboration, while establishingproject discussion records, decision sedimentation, a product knowledge base, and an iteration roadmap. Finally, through a complete project review and an AI product graduation project, it helps learners masterfrom a one-sentence requirement to product solution, prototype design, development collaboration, and project deliverya systematic method, enhancing product design and project advancement capabilities in the AI era.

II. Suitable audience

1. Professionals who want to transition into AI product managers.
2. Product managers who want to use AI to improve work efficiency.
3. Beginners learning product design and development collaboration from zero.
4. Entrepreneurs who need to quickly create product prototypes.
5. Enterprise teams that want to master the AI product implementation process.

III. What you gain after learning

1. Master the use of Trae, Claude Code, and MCP tools.
2. Learn AI requirements analysis, PRD writing, and quality review.
3. Master AI prototype creation, page design, and review processes.
4. Learn user story writing and TAPD project collaboration.
5. Master the complete AI product process from requirements to delivery.

IV. Course Catalog

1. Introduction to the AI Product Enterprise-Level Application Practical Combat Course
2. Why AI Product Managers Are the Future
3. Understanding the Course Case
4. SIDE Methodology: The Four-Step Closed Loop from a Product Manager's Perspective
5. One-Sentence Introduction to Course Tools
6. AI Software Installation
7. Configuring Claude Code
8. Configuring Gitee
9. Pencil MCP Configuration
10, TAPD MCP configuration
11, TRAE workspace and extension plugins
12, Common pitfalls and solutions
13, Using Claude Code for the first time
14, Experience the three core capabilities
15, Hands-on: Use AI to read the MRD and complete three tasks
16, Where product managers' requirements come from
17, Case breakdown: The 6 core pain points of the points mall
18, Three-step information collection method
19, Hands-on: From one sentence to a requirements list
20, What is a PRD: A product blueprint, not a reporting document
21, Use AI to write PRD documents
22, PRD key product manager standards
23, Hands-on: Use AI to generate a points mall PRD
24, 5 common PRD pitfalls
25, Use AI for a 14-dimension PRD scan
26, Hands-on: Use AI to audit the points mall PRD
27, What is a page specification document
28, Standard page specification document template
29, Case breakdown and template selection
30, Hands-on: Use AI to write a page specification document
31, What pages most easily miss: 6-dimension page specification document scan
32, Hands-on: Use AI to audit the page specification document
33, Why product managers should know how to make prototypes
34, Prototype creation principles
35, Quick start: Use Claude Code to generate a prototype
36, Points mall prototype breakdown
37, Hands-on: Use AI to create a points redemption mall homepage prototype
38, Why convert HTML to Pencil
39, Detailed HTML to Pencil process
40, Hands-on: Use AI to convert the points mall HTML prototype into a .pen file
41, What is a sitemap
42, Use AI to generate a sitemap
43, Use AI to generate a design review HTML page
44, Hands-on: Use AI to generate a sitemap + review page + simulated 5-minute demo
45, Why development needs user stories
46, Standard user story template
47, Full overview of points mall user stories
48, Use AI to generate user stories in one click
49, Hands-on: Write a set of user stories for the redemption + verification process
50, TAPD sync full workflow
51, How to configure tapd-config.json
52, What a TAPD Story looks like
53, Hands-on: use AI to sync user stories to TAPD
54, User story sync verification checklist
55, Why product managers should write good discussion records
56, Use AI to capture decisions
57, Knowledge base maintenance
58, Common pitfalls guide for knowledge management
59, Hands-on: use AI to capture a discussion
60, Project overview review
61, SIDE deliverables at each stage
62, Product manager pitfall experience summary
63, Product iteration evolution roadmap
64, 8 experience tips for product managers
65, AI product graduation project