Series
The AI-First Developer
From toolkit setup to ethics and ownership — the complete 15-part workflow for AI-assisted development.
15 parts · 184 min total
Start with Part 0Part 0: Part 0 — Your AI Dev Toolkit: The Right Tools, The Right Setup, The Right Stack
Before the mindset. Before the frameworks. Before any of the workflow strategies in this series — you need the right tools configured the right way. Most developers pick the wrong tool, configure it badly, and blame the AI. This is the setup guide nobody wrote.
Part 1: Part 1 — The AI-First Mindset: Stop Coding, Start Architecting
You wrote the for loop. The AI wrote 800 lines while you were on the phone. The developers who thrive aren't the fastest coders — they're the ones who learned to stop thinking about how and start thinking about what.
Part 2: Part 2 — Green Light / Red Light: The Developer's Framework for AI Delegation
You handed everything to the AI. Three months later, you can't debug without it. The fix isn't using AI less — it's using it strategically. Here's the exact framework for knowing which tasks to delegate and which ones to own.
Part 3: Part 3 — The Specification Framework: Write Prompts That Generate Production-Ready Code on the First Try
Vague prompt: 40 minutes of refinement cycles. Precise prompt: production-ready code on the first try. The difference isn't the AI — it's the 5-part specification architecture that eliminates every source of ambiguity before the AI writes a single line.
Part 4: Part 4 — The Confident Junior: 4 Ways AI Fails and How to Catch Every One
The AI generated payment processing code with a subtle SQL injection vulnerability. The tests passed. The code review passed. It shipped to production. Understanding how AI fails — with complete confidence — is the skill that separates safe developers from dangerous ones.
Part 5: Part 5 — AI Debugging: The 3-Context Framework That Closes Bugs in Minutes
Two developers. Same AI tool. One fixes the bug in 5 minutes. The other spends 40 getting generic suggestions that miss the root cause. The difference isn't the model — it's the 3 pieces of context that unlock AI debugging. Here's the framework and the 4-step workflow.
Part 6: Part 6 — The Trust Spectrum: When AI Code Review Should Take 4 Seconds vs 4 Hours
AI generates code in seconds. The professional risk is the instinct to review it just as fast. A bug in formatCurrency costs ten minutes. A bug in verifySession costs your company. This is the framework for calibrating review intensity to blast radius.
Part 7: Part 7 — Design First, Code Later: How to Keep Architectural Control When AI Does the Building
You asked AI to build a feature. It gave you working code in the wrong architecture. Then you had to throw it away and start over. The fix isn't better prompting — it's a mindset shift: design the blueprint before the AI lays a single brick.
Part 8: Part 8 — The 4 Quality Gates: How to Stop AI-Generated Technical Debt Before It Ships
AI can generate technical debt faster than any team of humans. It creates consistent, compounding anti-patterns across an entire codebase at machine speed. The 4 Quality Gates are the systematic checks that catch it before it lands in your main branch.
Part 9: Part 9 — Pick the Right Model Every Time: The Three-Tier Selection Framework
You've been using a sledgehammer for everything. Using your highest-capability model for formatting fixes wastes money and time. Using a fast lightweight model for security-critical code is negligent. Here's the framework for matching the right AI to every coding task.
Part 10: Part 10 — Team AI: How to Build a Shared Standard That Scales Across Your Entire Engineering Team
One developer on your team uses AI brilliantly. Another ships bugs 40% faster. Without a shared standard, AI amplifies both good and bad engineering practices simultaneously. Here's how to build an AI standard that makes the whole team better.
Part 11: Part 11 — The Dependency Trap: What Happens to Your Skills After 6 Months of AI Coding
After 6 months of daily AI coding, a developer sat down with a blank file and no AI running. A task that should have taken 20 minutes took 2 hours. This is the predictable journey every AI developer faces—and how to come out on the right side.
Part 12: Part 12 — 100% Ownership: The Ethics, Responsibility, and Long Game of AI-Assisted Development
The AI wrote it — that's not an excuse. The moment you hit commit, every line becomes yours. Here's the complete framework for taking full ownership, avoiding the bias and security traps AI reliably creates, and building a career that compounds as AI handles more of everything else.
Part 13: Part 13 — AI-Powered Testing: Write Tests That Actually Test Something
The AI wrote your tests. They all pass. Your code coverage is 94%. Then production breaks. The problem isn't the AI—it's that most AI-generated tests are hollow. Here's how to write tests that genuinely protect your code.
Part 14: Part 14 — Taming Legacy Code with AI: From Archaeology to Modern Architecture
200,000 lines of code. No documentation. The original developer left 18 months ago. Before AI, this would take weeks of archaeology. With AI, you can understand, document, and safely modify a codebase you've never seen—in days.