Getting Started with AI Development Patterns

A structured learning path for developers new to AI-assisted development.

Prerequisites

  • Basic programming knowledge
  • Familiarity with version control (Git)
  • Access to an AI coding assistant (Claude Code, GitHub Copilot, etc.)

Learning Path Overview

graph LR
    A[Foundations] --> B[First Patterns]
    B --> C[Tool Integration]
    C --> D[Team Adoption]
    D --> E[Advanced Patterns]

Week 1: Foundations

Day 1-2: Philosophy and Mindset

📖 Read: Philosophy and Mindset

  • Understand AI as a collaborator, not replacement
  • Learn about context management
  • Grasp the importance of clear communication

Exercise: Write 5 different prompts for the same task, observe differences

Day 3-4: Core Concepts

📖 Read: Introduction

  • Understand the three-tier knowledge system
  • Learn risk profiles (Green/Yellow/Red)
  • Review the taxonomy structure

Exercise: Categorize 3 recent coding tasks by risk level

Day 5: First Implementation

📖 Read: System Prompts and Model Settings

  • Configure your first system prompt
  • Understand model parameters
  • Set up development environment

Exercise: Create a custom prompt for your specific domain

Week 2: First Patterns

Day 1-2: Basic Execution Flow

📖 Read: Execution Flow in Detail

  • Understand request-response cycles
  • Learn about streaming responses
  • Handle errors gracefully

Exercise: Implement a simple tool that uses AI for code review

Day 3-4: Framework Selection

📖 Read: Framework Selection Guide

  • Evaluate different AI frameworks
  • Understand trade-offs
  • Make informed choices

Exercise: Compare 2 frameworks for your use case

Day 5: Practical Examples

📖 Read: Real World Examples

  • Study successful implementations
  • Learn from common mistakes
  • Identify patterns relevant to your work

Exercise: Adapt one example to your project

Week 3: Tool Integration

Day 1-2: Architecture Basics

📖 Read: Core Architecture

  • Understand the three-layer architecture
  • Learn about plugin systems
  • Grasp reactive patterns

Exercise: Diagram your current architecture and identify AI integration points

Day 3-4: Tool Systems

  • Learn tool interface patterns
  • Understand permission models
  • Implement custom tools

Exercise: Create a custom tool for your workflow

Day 5: Parallel Execution

📖 Read: Parallel Tool Execution

  • Optimize for performance
  • Handle concurrent operations
  • Manage resource usage

Exercise: Convert sequential operations to parallel

Week 4: Team Adoption

Day 1-2: Collaboration Patterns

  • Set up team workflows
  • Establish conventions
  • Share knowledge effectively

Exercise: Document and share one successful pattern with your team

Day 3-4: Security Considerations

📖 Read: The Permission System

  • Implement access controls
  • Understand security risks
  • Set up audit logging

Exercise: Add permission checks to your tools

Day 5: Lessons Learned

📖 Read: Lessons Learned

  • Learn from others' experiences
  • Avoid common pitfalls
  • Plan for challenges

Exercise: Create a risk mitigation plan

Milestone Checklist

Foundation Complete ✅

  • Configured AI assistant with custom prompts
  • Implemented at least one pattern successfully
  • Measured productivity improvement
  • Documented learnings

Integration Complete ✅

  • Integrated AI into existing workflow
  • Created custom tools
  • Optimized for performance
  • Established security measures

Team Ready ✅

  • Shared patterns with team
  • Established team conventions
  • Set up collaborative workflows
  • Created documentation

Next Steps

For Individuals

→ Explore Advanced Patterns → Experiment with High-Risk Patterns in safe environments

For Teams

→ Follow Enterprise Adoption Journey → Implement Team Workflows

For Agencies

→ Study Agency Playbook → Focus on Client Communication

Quick Reference Card

Daily Practices

  1. Start with low-risk patterns (Green)
  2. Document what works and what doesn't
  3. Measure impact with simple metrics
  4. Share learnings with peers
  5. Iterate quickly based on feedback

Warning Signs

  • 🚫 Implementing high-risk patterns without experience
  • 🚫 Skipping security considerations
  • 🚫 Not measuring impact
  • 🚫 Working in isolation
  • 🚫 Ignoring failure modes

Success Indicators

  • ✅ Consistent productivity gains
  • ✅ Reduced bug rates
  • ✅ Team adoption growing
  • ✅ Clear documentation
  • ✅ Positive feedback loops

Resources

Essential Tools

Community

  • Share your patterns with the QED community
  • Learn from others' implementations
  • Contribute improvements back

Remember: Start small, prove value, scale gradually