AI-Driven
Development

Master the art of building software with AI assistants. Learn the AIDD methodology to write better code faster while maintaining quality and avoiding common pitfalls.

10
Lectures
7
Practicals
AIDD
Framework
Commencer
Défiler

Module 1: Foundations of AI-Driven Development

Understand AI-assisted development and the AIDD framework

Lecture 1

Introduction to Vibe Coding

Understand AI-assisted development, the promise and perils of "vibe coding", and why methodology matters

 Lecture 2

The AIDD Framework

Deep dive into AI-Driven Development: Discover, Plan, Review, Execute, Commit, Test workflow

Module 2: Prompt Engineering for Developers

Learn to craft effective prompts and specifications

Lecture 3

Effective Prompt Engineering

Learn to craft effective prompts: structure, context, constraints, and iterative refinement techniques

 Lecture 4

Specifications & Vision Documents

Create effective vision.md files, specifications, and context documentation for AI collaboration

Module 3: Quality Assurance with AI

Implement TDD workflows and understand AI limitations

Lecture 5

Test-Driven Development with AI

Implement TDD workflows with AI: write tests first, verify AI output, and maintain code quality

 Lecture 6

AI Limitations & When Not to Use AI

Understand AI boundaries, hallucinations, and scenarios where AI assistance falls short

Module 4: Real-World Applications

Case studies and comparison of AI development tools

Lecture 7

Case Studies

Real-world examples of AI-assisted development: API development, library integration, documentation

 Lecture 8

AI Tools Comparison

Compare Copilot, Claude, ChatGPT, Cursor, and other AI development tools with practical examples

Module 5: Advanced Topics

Building AI agents and best practices for the future

Lecture 9

Building AI Agents

Create autonomous AI agents using LangChain and other frameworks for automated development workflows

 Lecture 10

Best Practices & Future Trends

Industry best practices, emerging patterns, and the future of AI-driven software development

Hands-On Exercises

Apply AIDD methodology through practical coding exercises

Practical 1

Environment Setup

Set up your AI development environment: IDE configuration, AI assistants, and project structure

 Practical 2

Your First AIDD Project

Build a complete feature using the AIDD workflow from vision document to deployment

 Practical 3

Complex Feature Implementation

Tackle a complex feature with multiple components, edge cases, and proper testing

 Practical 4

Debugging with AI

Use AI to analyze stack traces, identify root causes, and fix bugs systematically

 Practical 5

AI-Assisted Code Review

Conduct thorough code reviews for security, performance, and code smells with AI

 Practical 6

Refactoring Legacy Code

Safely modernize legacy code using characterization tests and design patterns

 Practical 7

API Integration with AI

Generate type-safe API clients with proper error handling and integration tests