I completed a project with 100% AI-generated code as a technical person. Here are quick 12 lessons

1. Start with structure, not code

The most important step is setting up a clear project structure. Don't even think about writing code yet.

2. Chat VS agent tabs

I use the chat tab for brainstorming/research and the agent tab for writing actual code.

3. Customize your AI as you go

Create "Rules for AI" custom instructions to modify your agent's behavior as you progress, or maintain a RulesForAI.md file.

4. Break down complex problems

Don't just say "Extract text from PDF and generate a summary." That's two problems! Extract text first, then generate the summary. Solve one problem at a time.

5. Brainstorm before coding

Share your thoughts with AI about tackling the problem. Once its solution steps look good, then ask it to write code.

6. File naming and modularity matter

Since tools like Cursor/Windsurf don't include all files in context (to reduce their costs), accurate file naming prevents code duplication. Make sure filenames clearly describe their responsibility.

7. Always write tests

It might feel unnecessary when your project is small, but when it grows, tests will be your hero.

8. Commit often!

If you don't, you will lose 4 months of work like this guy.

9. Keep chats focused

When you want to solve a new problem, start a new chat.

10. Don't just accept working code

It's tempting to just accept code that works and move on. But there will be times when AI can't fix your bugs - that's when your hands need to get dirty (main reason non-tech people still need developers).

11. AI struggles with new tech

When I tried integrating a new payment gateway, it hallucinated. But once I provided docs, it got it right.

12. Getting unstuck

If AI can't find the problem in the code and is stuck in a loop, ask it to insert debugging statements. AI is excellent at debugging, but sometimes needs your help to point it in the right direction.

* It was a training project, not a useful product.