I installed Cursor about two weeks ago with high expectations. I wanted to build a side project in a weekend. Instead, I spent the first day deleting code that the AI generated. It was confident, it was fast, and it was completely wrong.
The problem was not the tool. The problem was my prompt. I was treating the AI like an oracle. I asked it to "build a user authentication system" and expected it to know my specific stack, my database schema, and my security preferences. It did not. So it guessed. And LLMs are bad at guessing when the stakes are high.
After a few frustrating hours, I changed my approach. I stopped asking for features and started asking for functions. I treated the AI like a junior developer who is very fast but has no context about my codebase.
The biggest mistake I see developers make is relying entirely on the chat box. Cursor has a feature that lets you index your codebase. If you are not using this, you are leaving 80% of the value on the table. But indexing is not enough. You have to be explicit about what the AI should look at.
When I started, I would just type in the chat: "Add a validation error here." The AI would guess which validation library I was using. I am using Zod. It assumed I was using Yup. The code broke.
Now, I do this differently. I open the file where I want the change. I use the @
symbol to explicitly reference the files that contain my types and my validation schemas. Then I write the prompt. The difference is night and day. When I point it at the actual source of truth, it stops hallucinating imports.
Here is a comparison of my prompts:
Bad: "Add a function to calculate tax."
Good: "Look at `@types.ts`
and @utils.ts
. Write a function in @tax.ts
that calculates tax based on the Order
type. Use the calculateTax
logic found in the existing code. Do not install new dependencies."
The second prompt is longer. It takes more time to write. But it saves me ten minutes of debugging later. The AI has a clear boundary. It knows where to look and what rules to follow.
I used to ask Cursor to do three things at once. "Create the component, add the API call, and update the state management." It would try to do all three in one go. Usually, it would get the API call right, but botch the state update because it did not fully understand the reducer pattern I was using.
Now, I break it down. I ask for one thing. I review it. I accept it. Then I ask for the next thing.
This sounds slower. It is not. It is actually faster because I am not trying to parse a 200-line diff that mixes three different concerns. I can review a 20-line diff in seconds. I can trust it more because the scope is small.
Think of it like code review. You do not like it when a junior dev sends you a PR that changes 50 files. You want small, focused changes. The AI is the same. Give it small tasks. It will perform better.
There are times when I close Cursor and open my normal editor. This is important. If I am doing complex refactoring or debugging a subtle race condition, the AI is a liability. It will suggest "fixes" that break other parts of the system because it does not have the full mental model of the runtime state.
Debugging is where I still rely on my own brain. I set breakpoints. I read the logs. I understand the flow. Once I understand the issue, I might ask Cursor to write the specific function that fixes it. But I do not let it diagnose the problem.
The AI is great for boilerplate. It is great for writing tests for functions I already wrote. It is great for explaining how a specific regex works. It is terrible for architectural decisions. If you let it make architectural decisions, you will end up with a Frankenstein codebase that no one can maintain.
@
symbol aggressively. Reference specific files. Do not let the AI guess.Cursor is not a replacement for your skills. It is an amplifier. If you are a weak developer, it will make you a faster weak developer. You will produce more buggy code, faster.
If you are a strong developer, it will make you a faster strong developer. You will spend less time on boilerplate and more time on the hard problems. The key is to set boundaries. Tell the AI what to do. Tell it what not to do. Show it exactly where to look. Treat it like a tool, not a teammate.
I am not going to stop using it. It has saved me hours on my current project. But I am no longer surprised when it gets things wrong. I am just faster at correcting it. And that is the real value. Not the code it writes, but the speed at which you can iterate on your own ideas.
Go back to your editor. Open your project. Find a small task. Use the @
symbol. Ask for one specific function. See if it works. If it does, try the next one. If it does not, read the file it should have looked at. Adjust your prompt. That is how you learn to work with it.
Do not look for the magic button. There is none. There is only practice and precision.