A practical AI coding workflow course teaching developers how to use Claude Code on real production codebases without creating technical debt.
Getting your AI coding workflow right is the difference between shipping clean production code and drowning in spaghetti you don't understand.
This course shows you how to use Claude Code as a professional tool, not a crutch.
It covers the fundamentals of how large language models work, why context windows matter, and how to manage them without losing your grip on a codebase.
All lessons are async, dropping on Mondays. Live office hours are offered at multiple time zones. You keep all materials after the cohort ends.
What you will learn:
How to use the Plan/Execute/Clear loop to keep Claude Code in its best-performing state.
How to write AGENTS.md files and custom skills that steer output without wasting tokens.
How to plan and execute features larger than any single agent session using multi-phase plans and tracer bullets.
How to set up automated feedback loops. Tests, pre-commit hooks, and red-green-refactor that catch problems before they compound.
How to run Claude Code autonomously against a GitHub Issues backlog using the Ralph loop.
Ideal for: Working developers who want a structured, production-safe AI coding workflow they can actually trust.