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Task Implementation Methodology
Task Implementation Methodology
Why Have a Methodology?
When you're collaborating with AI on complex tasks, a methodology:
- Prevents you from missing critical steps
- Improves code quality
- Reduces rework
- Makes outcomes predictable
Process
1. Think Through Strategy
Before writing any code, get clear on:
- Understand the complete requirement
- Identify key components needed
- Consider dependencies and constraints
- Plan the implementation approach
2. Evaluate Approaches
List possible approaches and compare:
- List possible implementation strategies
- Compare pros and cons of each
- Consider:
- Performance implications
- Maintainability
- Scalability
- Code reusability
- Testing complexity
3. Consider Tradeoffs
Every decision has tradeoffs:
- Short-term vs long-term benefits
- Complexity vs simplicity
- Performance vs readability
- Flexibility vs focused solution
- Time to implement vs perfect solution
4. Implementation Steps
Follow this order during execution:
- Break down into subtasks
- Start with core functionality
- Implement incrementally
- Test each component
- Integrate components
- Add error handling
- Optimize if needed
- Document decisions
5. Best Practices
- Write tests first (TDD approach)
- Keep functions small and focused
- Use meaningful names
- Comment complex logic
- Handle edge cases
- Consider future maintenance
Checklist
Before calling a task done, verify:
- Requirements fully understood
- Approach documented
- Tests written
- Code implemented
- Edge cases handled
- Documentation updated
- Code reviewed
- Performance acceptable
Working with AI in Practice
Tell AI Your Methodology
I need to implement user authentication. Follow these steps:
1. Analyze requirements, list key components
2. Evaluate JWT vs Session approaches
3. After picking an approach, implement step by step
4. Test after each step
5. Integrate and add error handling last
Have AI Generate a Task List
Analyze this feature requirement and generate an implementation checklist,
including subtasks, dependencies, and test points.
Incremental Implementation
Implement core functionality first: user login.
Don't worry about password reset, OAuth, etc.
We'll add those later.
Example: Implementing Search
1. Understand Requirements
Need to implement:
- Keyword search
- Pagination support
- Result highlighting
- Search suggestions
2. Analyze Approaches
Approach A: Database LIKE queries
+ Simple
- Poor performance
- Can't highlight
Approach B: Elasticsearch
+ Great performance
+ Full feature set
- Extra dependency
3. Implement Step by Step
Step 1: Build basic search API
Step 2: Add pagination
Step 3: Integrate Elasticsearch
Step 4: Implement highlighting
Step 5: Add search suggestions
Task Template
## Task: [Task Name]
### 1. Requirements
- [ ] [Requirement 1]
- [ ] [Requirement 2]
### 2. Approach
Chosen approach: [approach name]
Reason: [rationale]
### 3. Subtasks
- [ ] [Subtask 1]
- [ ] [Subtask 2]
- [ ] [Subtask 3]
### 4. Testing
- [ ] Unit tests
- [ ] Integration tests
- [ ] Edge cases
### 5. Documentation
- [ ] Code comments
- [ ] API docs
- [ ] README update
Summary
A methodology isn't about limiting creativity -- it's about ensuring quality. When you work with AI, a clear methodology helps AI understand your expectations and produce higher-quality code.