2.0 AI-Driven Development Foundations
Overview
This module lays the groundwork for AI-native coding. You'll learn how to translate ideas into specs and use AI to generate quality code. The focus is on frictionless onboarding into AI-driven work — setting up tools, learning how to "think in prompts," and embracing new workflows.
Core Themes:
- Introduction to AI pair-programming and prompt engineering
- Liatrio's Spec-Driven Development process
- Getting reps with an AI-native codebase
What You'll Do
You'll work through all the open issues in the Emerald Grove Pet Clinic repository. These issues are your "reps" — structured exercises to build muscle memory with AI-assisted development.
Use the fork of the Emerald Grove Pet Clinic repository you created in 1.5 Fork the Example Repository. That fork is your personal workspace for all the exercises in this module.
You should already have:
- Your own fork of the Pet Clinic repository
- The issue set created in your repository
- Pre-commit hooks installed and verified
- AI code review configured on your PRs
Primary Capabilities You'll Develop
Spec-Driven Development Proficiency
Learn to use the 4-step SDD prompt sequence:
- Specification — Transform a feature idea into a detailed spec
- Task Breakdown — Break the spec into actionable tasks with proof artifacts
- Implementation — Execute tasks with AI doing the coding
- Validation — Verify implementation matches the specification
You'll practice writing clear, machine-readable specifications and letting the AI handle implementation details.
Prompt Engineering & AI Collaboration
Develop skill in crafting effective prompts and instructions for coding agents. Learn strategies to:
- Iteratively refine AI outputs
- Fix errors and course-correct
- Verify the AI's work
- Manage context effectively
Essentially, you become an "AI project manager" — directing the model and keeping it on track.
Version Control & Quality Checks
Even though AI writes the code, you remain responsible for quality:
- Use Git effectively with AI-generated commit messages
- Review AI contributions critically
- Use automated testing and validation from the SDD workflow
- Respond to AI code review feedback on your PRs
Exercises
Fix All Open Issues
The Pet Clinic repository has open issues waiting to be fixed. Your job:
- Pick up an issue
- Write a spec for the fix (SDD Step 1)
- Generate a task breakdown (SDD Step 2)
- Have AI implement the fix (SDD Step 3)
- Validate and get AI code review (SDD Step 4)
- Merge the PR
Repeat for all issues. This is where you build your reps.
Record Your Demo
As you work through the issues, record a demo (5-10 minutes) that shows:
- The issues you fixed
- How you used AI to solve them
- Your approach and any techniques that worked well
Deliverables
By the end of the Foundations Module, you must produce:
| Artifact | Description |
|---|---|
| Spec docs | Markdown specifications for each issue |
| Task breakdowns | How you decomposed each fix |
| PR links | All merged PRs with AI code review |
| Test output | Proof that all acceptance criteria passed |
| Demo recording | 5-10 minute walkthrough of your approach |
Exit Criteria
You can move to the Features & Systems Module when you have:
Fixed all the open issues in the Pet Clinic with 99% AI-written code.
Your PRs should show AI code review feedback addressed, tests passing, and a demo recording explaining your approach.
If this is taking longer than ~10 hours, reach out for help.
Reflect on Your Workflow
Before moving on, run the /insights command in Claude Code. After working through all the issues in this module, you have real conversation history for it to analyze.
/insights reviews your recent sessions and surfaces actionable suggestions — things like prompting habits you could improve, features you're underusing, or workflow patterns that could be more efficient.
Take a few minutes to review the suggestions. Pick one or two to intentionally practice in the next module. This is one of the fastest ways to level up your AI collaboration skills.
What You'll Learn
By completing this module, you'll have experienced:
- Delivering features in minutes or hours instead of days
- The discipline of spec-driven development
- How to direct AI effectively (and when to start fresh)
- The feedback loop of AI code review
This establishes your baseline for accelerated flow.