Workflow and collaboration mechanisms
Build an efficient AI-assisted development process, design collaboration mechanisms, enable cross-department collaboration, and ensure the team operates efficiently.
AI-assisted development workflow
Deeply integrate AI tools into every stage of the development process, optimizing the full workflow from requirements to delivery.
Requirements phase
Use AI tools to conduct requirement interviews and quickly identify ambiguities and contradictions in the requirements.
Based on the requirements clarification results, use AI to generate initial drafts of the PRD and Spec documents, then review and refine them manually.
Break the Spec down into executable tasks, with AI assisting in generating the WBS (Work Breakdown Structure).
Development phase
Based on the Spec and WBS, use AI tools to generate code, then manually review and optimize it.
Use Cursor Agent Review mode for code reviews to check conventions, security, and performance.
Based on code logic, AI generates unit test cases to improve test coverage.
Delivery phase
Use Fabric Patterns to automatically generate changelogs and API documentation, ensuring documentation stays in sync with code.
Integrate AI tools into the CI/CD process to automatically perform code reviews, test generation, and documentation updates.
Use AI tools to analyze production environment issues, quickly identify and resolve them.
Collaboration mechanisms
Build effective collaboration mechanisms to promote knowledge sharing and problem solving.
Code review process
- • Use Cursor Agent Review mode
- • Review checklist (specification check, security check, performance check)
- • Review feedback template
- • AI assistance + human review
Knowledge sharing mechanism
- • Weekly tech sharing (new tools, new techniques, case studies)
- • Skill/Pattern contribution rewards
- • Best practice documentation
- • Internal Wiki setup
Problem-solving process
- • AI tool usage issues → internal Wiki
- • Technical challenges → AI-assisted analysis + team discussion
- • Tool bugs → unified feedback channel
- • Issue tracking and resolution records
Cross-department collaboration process
How departments such as HR, finance, and legal collaborate with AI tools to improve work efficiency.
HR department collaboration
- • Use Fabric to generate job descriptions and interview questions
- • Use AI tools to generate evaluation criteria
- • Use Cursor to create training materials
- • Use AI to generate training content
- • Use AI tools to analyze employee data (pay attention to privacy protection)
- • Use a local model to process sensitive information
- • Fabric Patterns (HR only)
- • Cursor (document writing)
Collaboration with the finance department
- • Use AI tools to analyze cost data
- • Use local models to generate reports
- • Use Fabric to generate budget templates
- • Use AI to generate analysis reports
- • Use Cursor to write financial documents
- • Use AI to generate reports (without sensitive data)
Financial data uses only local models (Ollama) and is not uploaded to the cloud
Collaboration with the legal department
- • Use AI tools to assist review (local processing)
- • Sensitive contracts are not uploaded to the cloud
- • Use AI tools to check compliance
- • Generate compliance reports
- • Use Fabric to generate legal document templates
- • Use Cursor to write legal documents
Use local models for sensitive legal documents
Cross-department collaboration guidelines
- •Data classification: Clarify which data can be used with AI tools
- •Tool selection: choose tools based on data sensitivity (cloud/local)
- •Approval workflow：Using AI tools with sensitive data requires approval
- •Audit records: Record usage of all AI tools
Version control and branching strategy
Establish a standardized version control process to ensure the quality and traceability of AI-generated code.
Git workflow
- • Feature branch: use AI tools to develop new features
- • Code Review: AI assistance + human review
- • Merge strategy: ensure the quality of AI-generated code
- • Commit message conventions: clearly describe the changes
Document version control
- • Spec document version management
- • Skill/Pattern version management
- • Best practice document version management
- • Change log entries
Hands-on practice
Practice suggestion:
- 1Design an AI-assisted development workflow (the complete process from requirements → development → delivery)
- 2Establish a code review mechanism (review checklist, feedback template, review process)
- 3Create a knowledge-sharing platform (internal Wiki, technical sharing sessions, case library)
- 4Design cross-department collaboration processes (AI use cases and guidelines for HR/finance/legal departments)
Learning outcomes
After completing this chapter, you will:
- 1Master the AI-assisted development process (requirements phase, development phase, delivery phase)
- 2Able to build effective collaboration mechanisms (code review, knowledge sharing, problem solving)
- 3Understand the importance of version control (Git workflows, document version control)
- 4Master cross-department AI collaboration methods (coordination processes and standards for HR, finance, and legal departments)