I’ve been using AI-powered and agentic IDEs like Cursor and Antigravity extensively in real-world software development.
After spending hundreds of hours building with AI, I’ve arrived at one hard, non-negotiable truth:
AI is a force multiplier for your existing skills. Nothing more. Nothing less.
If you have weak fundamentals, AI helps you write bad code faster. If you have strong fundamentals, AI turns you into a significantly more effective engineer.
This post is not about hype. It’s my practical playbook for using AI to ship maintainable, production-grade software—without destroying your codebase six months later.
1. Fundamentals First: You Are the Architect
If you cannot explain the logic yourself, do not ask AI to write it.
AI should never be the decision-maker. You must remain the architect—AI is only the builder.
When engineers skip this step, the failure mode is predictable:
- Over-engineered abstractions
- Tight coupling between components
- Un-testable business logic
- “Magic” code no one understands or can safely modify
Before writing a single prompt, you should be able to answer:
- What problem does this solve?
- What are the inputs and outputs?
- What are the failure cases?
- Where does this logic live in the system?
If those answers aren’t clear, AI will happily invent them for you—and you’ll pay for it later.
2. Break Problems into Atomic Parts
AI struggles with large, ambiguous problem spaces.
Never ask:
Build the entire app.
Instead, break features into atomic, testable units with clear responsibilities.
What “Atomic” Means in Practice
Each task should:
- Do exactly one thing
- Be independently testable
- Have a clear definition of “done”
- Fit into an existing architectural boundary
AI performs best when solving small, well-scoped problems rather than generating massive chunks of loosely connected code.
3. Ditch the One-Liners: Precision Beats Brevity
Vague prompts produce vague results.
Bad Prompt
Make a login page.
Better Prompt
Build a JWT-based authentication flow using FastAPI and React. Use HTTP-only cookies. Implement refresh token rotation. Avoid localStorage. Use Tailwind for styling. Include unit tests for token expiry.
Think of prompts as technical specifications, not casual requests.
4. Provide Total Context or Expect Hallucinations
AI cannot infer what it cannot see.
Before asking for code, provide as much relevant context as possible:
- Existing documentation
- Database schemas
- API contracts
- Folder structure
- UI wireframes or screenshots
Without context, AI fills gaps with assumptions. With context, it behaves predictably and stays within boundaries.
5. Define Constraints Explicitly
Constraints are not optional. They are what prevent AI from “helpfully” rewriting your architecture.
Always be explicit about what must not change.
Example Constraint Block
Constraints: Do NOT introduce new libraries. Stick strictly to the existing tech stack. No schema changes. No external SaaS dependencies.
Clear constraints force AI to operate within your system instead of around it.
6. Refine the Prompt With the AI
One of the most effective techniques is asking AI to critique your prompt before writing code.
Try this:
I want to build X. What technical context am I missing that would help you do this perfectly?
This often surfaces:
- Missing edge cases
- Unclear responsibilities
- Implicit assumptions
- Overlooked constraints
Treat this as a design review, not a coding step.
7. Verify Relentlessly: Never Trust Blindly
AI-generated code is untrusted input.
Never:
- Copy-paste without reading
- Assume correctness
- Skip tests
A strong habit is to immediately follow up with:
Write a unit test suite that proves this code works. Include edge cases and failure scenarios.
Tests force clarity—for both you and the AI.
The Bottom Line
AI will not save you from poor engineering discipline.
But if you:
- Own system design
- Respect fundamentals
- Break work into atomic units
- Enforce constraints
- Verify everything
Then AI becomes what it should be:
A massive speed multiplier—not a replacement for thinking.
You provide the intent, structure, and judgment. Let AI handle the typing.
That’s how you ship high-quality software with AI—consistently.