Real Programmers Use AI
AI is a coding tool. Used well, it helps you plan, debug, refactor, test, and document faster while you stay accountable for every line that ships.
What you will get
Practical workflows and prompt patterns that produce reliable work without turning your repo into guesswork.
- Spec-first prompts that force clarity before you code
- Debugging prompts built around minimal repros and logs
- Refactor prompts that respect tests and small commits
- Documentation prompts that match what the code actually does
What you will not get
No hype. No magic. No pretending the AI is a senior engineer.
- No "copy this prompt and it will build your app" nonsense
- No hallucinated APIs passed off as facts
- No shortcuts that hide accountability
- No shaming, and no purity tests
The workflow loop (the core of the series)
This is the repeatable loop that keeps you in control, whether you are working in a modern stack or maintaining a mature codebase.
- Frame: Define the goal, constraints, inputs, and acceptance checks.
- Draft: Generate options, not a single answer. Prefer small steps.
- Verify: Run tests, check docs, validate assumptions, and review diffs.
- Ship: Commit in slices with notes you can defend later.
The free checklist
The AI Coding Workflow Checklist is a short, practical reference you can use today. It focuses on quality gates that reduce bad AI output before it reaches your repo.
Early reader input (optional)
If you want to influence the book, tell me your language, your tooling, and your pain points. I will prioritize workflows that solve real problems.