Initial Document Generation Guide
Table of Contents
- Introduction
- Choosing the Right Flow
- Questionnaire Flow
- AI Wizard Flow
- Comparison Table
- Tips for Best Results
- Common Mistakes to Avoid
- FAQ
Introduction
ProjectDocsEngine offers two distinct flows for generating initial project documentation:
- Questionnaire Flow - A structured, form-based approach with predefined questions
- AI Wizard Flow - A conversational, flexible approach with AI-guided questions
Both flows generate the same 6 core documents:
- Product Requirements Document (PRD)
- Technical Stack
- User Flow Diagrams
- Database Schema
- UI/UX Design Guidelines
- Development Task List
Choosing the Right Flow
Use Questionnaire Flow When:
- You have clear, well-defined project requirements
- You prefer structured input forms
- You want predictable questions every time
- You're documenting a traditional web/mobile application
- You want to complete the process quickly (5-10 minutes)
- You're less comfortable with conversational interfaces
Use AI Wizard Flow When:
- Your project has unique or complex requirements
- You want to explore ideas through conversation
- You need flexibility in how you describe your project
- You're building something innovative or non-standard
- You prefer natural language over forms
- You want the AI to ask relevant follow-up questions
Questionnaire Flow
Step-by-Step Guide
Step 1: Basic Project Information
What you'll be asked:
- Project name
- Brief description (2-3 sentences)
- Target audience
- Main problem it solves
Example Input:
Name: TaskFlow Pro
Description: A project management tool that uses AI to automatically prioritize tasks and suggest optimal work schedules based on team capacity and deadlines.
Target Audience: Small to medium software development teams (5-50 people)
Problem: Teams struggle with task prioritization and often miss deadlines due to poor workload distribution
Step 2: Features and Functionality
What you'll be asked:
- Core features (list 5-10)
- User types/roles
- Key user actions
Best Practices:
- Be specific about features (not just "user management" but "role-based user management with admin, manager, and team member roles")
- Prioritize features by importance
- Think about the complete user journey
Example Input:
Core Features:
1. AI-powered task prioritization based on dependencies and deadlines
2. Real-time team capacity visualization
3. Automated sprint planning with workload balancing
4. Integration with GitHub, Jira, and Slack
5. Burndown charts and velocity tracking
6. Smart notifications for at-risk tasks
7. Time tracking with automatic suggestions
User Roles:
- Admin: Full system control, team management
- Project Manager: Create projects, assign tasks, view reports
- Developer: Update tasks, log time, view assignments
- Viewer: Read-only access to dashboards
Step 3: Technical Preferences
What you'll be asked:
- Preferred technology stack
- Database preference
- Deployment target
- Third-party integrations
Example Input:
Frontend: React with TypeScript, Tailwind CSS
Backend: Node.js with Express
Database: PostgreSQL with Redis for caching
Deployment: AWS (ECS for backend, S3/CloudFront for frontend)
Integrations: Stripe for payments, SendGrid for emails, Auth0 for authentication
Step 4: Design and UX
What you'll be asked:
- Design style preference
- Key UI elements
- Mobile responsiveness needs
- Accessibility requirements
Example Input:
Style: Modern, minimal with focus on data visualization
UI Elements: Kanban boards, Gantt charts, real-time dashboards
Mobile: Fully responsive with dedicated mobile app planned
Accessibility: WCAG 2.1 AA compliance required
Questionnaire Flow Tips
-
Prepare Before Starting
- List your features beforehand
- Know your target audience precisely
- Have technical preferences decided
-
Be Comprehensive
- Include all major features in the first pass
- Don't leave sections blank
- Add context where helpful
-
Think About Edge Cases
- Include error handling requirements
- Mention scalability needs
- Consider security requirements
AI Wizard Flow
How to Get the Best Results
Starting the Conversation
Good Opening:
I want to build a project management tool called TaskFlow Pro that helps software development teams manage their work more efficiently. The main innovation is using AI to automatically prioritize tasks and balance workload across team members.
Why it works:
- Clear project type
- Specific name
- Unique value proposition stated upfront
Guiding the AI's Questions
The AI Wizard will adapt its questions based on your responses. Here's how to guide it effectively:
-
Provide Context in Your Answers
AI: "What features are most important for your project management tool?"
Good Response:
The core feature is AI-powered task prioritization that considers:
- Task dependencies and blockers
- Team member skills and availability
- Historical velocity data
- Business priority scores
We also need sprint planning automation, real-time dashboards, and integrations with developer tools like GitHub and Jira. -
Ask for Clarification When Needed
Example:
You: "Should I include details about our microservices architecture plan, or focus more on user-facing features?"
AI: "Please include both! Start with the user-facing features, then explain how the microservices architecture supports them." -
Use Technical Terms When Appropriate
Good: "We'll use event sourcing for the task history and CQRS for separating read/write operations"
Why: The AI recognizes technical patterns and will ask more sophisticated follow-up questions
AI Wizard Conversation Strategies
Strategy 1: Start Broad, Then Narrow
You: "It's a B2B SaaS platform for project management"
AI: "What makes your platform different from existing tools?"
You: "We use machine learning to predict task completion times and automatically rebalance workloads"
AI: "How will the ML model be trained?"
You: "Using historical data from teams, considering factors like task complexity, developer experience, and past performance"
Strategy 2: Use Comparisons
"It's like Jira meets Clockify with AI capabilities similar to GitHub Copilot's predictive features"
Strategy 3: Describe User Scenarios
"A project manager opens the dashboard Monday morning and sees that based on the weekend's commits, three tasks are now at risk. The AI suggests reassigning two tasks and pushing one sprint deadline by 2 days."
AI Wizard Advanced Techniques
-
Iterative Refinement
- Start with a basic description
- Let the AI ask questions
- Refine your answers based on what aspects the AI explores
-
Domain-Specific Language
- Use industry terms relevant to your project
- This helps the AI ask more targeted questions
-
Provide Examples
"For example, when a developer marks a task as blocked, the AI should automatically notify relevant team members and suggest alternative tasks from the backlog" -
Discuss Non-Functional Requirements
- Mention performance needs: "Must handle 10,000 concurrent users"
- Include security requirements: "Needs SOC 2 compliance"
- Specify scalability: "Should support teams from 5 to 500 members"
Comparison Table
| Aspect | Questionnaire Flow | AI Wizard Flow |
|---|---|---|
| Time Required | 5-10 minutes | 10-20 minutes |
| Structure | Fixed form fields | Dynamic conversation |
| Best For | Standard projects | Unique/complex projects |
| Flexibility | Limited | High |
| Question Depth | Consistent | Adaptive |
| User Experience | Form-filling | Conversational |
| Revision Process | Edit form fields | Continue conversation |
| Learning Curve | Minimal | Moderate |
| Output Consistency | High | Varies with input quality |
Tips for Best Results
For Both Flows
-
Know Your Audience
- Be specific: "B2B SaaS for 10-50 person software teams" not just "businesses"
- Include geographic considerations if relevant
- Mention technical sophistication level
-
Define Success Metrics
- Include how you'll measure success
- Mention KPIs important to your users
- This helps generate better PRD sections
-
Include Technical Constraints
- Budget limitations
- Timeline requirements
- Compliance needs (GDPR, HIPAA, etc.)
- Performance requirements
-
Think About the Full Lifecycle
- Not just features, but onboarding
- Maintenance and updates
- User support needs
- Growth considerations
Questionnaire-Specific Tips
-
Use the Description Fields Fully
Bad: "User management"
Good: "Multi-tenant user management with SSO support, role-based permissions, and audit logging" -
Prioritize in Your Lists
- Put must-have features first
- Indicate MVP vs. future features
- Group related features together
-
Be Consistent with Terminology
- If you say "workspace" in one answer, don't switch to "project" later
- Define terms if they're domain-specific
AI Wizard-Specific Tips
-
Prime the AI with Context
"I'm building this for my current company, a 50-person fintech startup. We need to replace our current Jira+Excel workflow with something more automated." -
Answer the 'Why' Not Just the 'What'
"We need real-time notifications because our team works across 3 time zones and async communication is critical for our workflow" -
Use Follow-Up Capabilities
You: "Should I explain our current pain points?"
AI: "Yes, please! That will help me understand what problems your solution needs to solve"
Common Mistakes to Avoid
In Questionnaire Flow
-
Being Too Vague
- ❌ "Good UX"
- ✅ "Clean, minimal interface with focus on data visualization, similar to Linear.app"
-
Listing Too Many Features
- Focus on 7-10 core features
- Save nice-to-haves for later updates
- Avoid feature creep in initial generation
-
Ignoring Technical Realities
- Don't select conflicting technologies
- Consider your team's expertise
- Be realistic about complexity
In AI Wizard Flow
-
Being Too Brief
- ❌ "It's a project management app"
- ✅ "It's a project management app that uses AI to predict task completion times and automatically balance workload across team members"
-
Not Following Up on AI Questions
AI: "How will the AI learn from team behavior?"
❌ "Machine learning"
✅ "By analyzing historical task completion times, comparing estimated vs. actual hours, and identifying patterns in task types and developer expertise" -
Switching Context Mid-Conversation
- Stick to one project vision
- Don't introduce major pivots midway
- Save alternative ideas for command mode updates
FAQ
Q: Can I switch between flows?
A: No, once you start with one flow, you need to complete it. However, you can always use Command Mode to update the generated documents later.
Q: What if I realize I forgot something important?
A: Complete the initial generation, then use Command Mode to add missing elements. For example: "Add real-time collaboration features to allow multiple users to edit tasks simultaneously"
Q: Which flow typically produces better documentation?
A: Both can produce excellent documentation. Questionnaire is more consistent, while AI Wizard can capture nuanced requirements better for complex projects.
Q: Can I use AI Wizard for a simple CRUD app?
A: Yes, but Questionnaire might be more efficient for straightforward projects. AI Wizard shines with innovative or complex requirements.
Q: How do I handle technical requirements I'm unsure about?
A:
- In Questionnaire: Choose the most likely option and update later via Command Mode
- In AI Wizard: Tell the AI you're unsure and ask for recommendations
Q: What detail level should I choose?
A:
- Basic: MVP, simple projects, or when you need quick documentation
- Standard: Most commercial projects with moderate complexity
- Enterprise: Complex systems, multiple integrations, high scalability needs
Q: Can I re-generate if I'm not happy with the output?
A: Yes, but you'll start fresh. It's often better to use Command Mode to refine specific documents.
Summary
Both flows are powerful tools for generating comprehensive project documentation:
- Questionnaire Flow: Best for standard projects where you have clear requirements and prefer structured input
- AI Wizard Flow: Best for innovative projects where you want to explore ideas and need flexible, adaptive questioning
The key to success with either flow is being specific, comprehensive, and thinking about your project from multiple angles (user needs, technical requirements, business goals).
Remember: Initial generation is just the start. Use Command Mode to continuously refine and update your documentation as your project evolves.