CursorAgent mode, thinking I could just describe the logic and let the AI handle the boilerplate.
It started great. It scaffolded the components in seconds. Then it hit a wall.
The agent kept trying to import a utility function that didn't exist, then it "fixed" it by creating the function, but in the wrong directory. Then it tried to fix the import again, but accidentally deleted the Zod schema in my types.ts
file. It was a cycle of "I apologize for that error, let me fix it" followed by a different, weirder error.
The exact error that broke my brain:ReferenceError: useFormContext is not defined
The agent had imported useForm
but was trying to call useFormContext
inside a child component. Every time it tried to fix the import, it would somehow overwrite the package.json
dependencies or hallucinate a version of react-hook-form
that didn't exist.
The diagnosis was a context window mess
I realized the agent wasn't actually "seeing" the current state of my files correctly. It was relying on an outdated index of my project. It thought the types.ts
file still had the schema because it was reading from a cached version of the prompt context, while the actual file on disk was empty because the agent had just wiped it during a botched "refactor."
This is the danger of "Agent" autonomy. When the AI has permission to read, write, and execute terminal commands, it can enter a death spiral if its internal representation of the codebase diverges from reality.
I stopped the agent. I did a hard git checkout .
to recover my deleted schema. Then I changed my approach.
How I actually fixed the loop
Instead of giving it a broad goal ("Make this form work"), I started feeding it specific constraints and forcing it to verify its own assumptions.
First, I used the @
symbol to explicitly link the files it needed to read. I stopped letting it "search" for the files. I pointed it directly to the component and the schema.
Second, I changed my prompt to: "Before writing any code, list the imports you plan to use and verify they exist in the current project. If you aren't sure, use the terminal to ls the directory first."
The difference was night and day. By forcing a "think-then-act" step, the agent stopped hallucinating imports.
| Approach | Result | Time to Fix |
| :--- | :--- | :--- | | Pure Agent Mode (Hands-off) | 4 broken files, 1 deleted schema | 4 hours |
| Guided Agent (Explicit @
links) | Working form, 2 minor typos | 15 mins |
| Manual Coding (No AI) | Perfect code, but slow | 2 hours |
The reality of AI-driven coding
Cursor Agent mode is a beast, but it's not a "set it and forget it" tool. If you treat it like a junior dev who is slightly manic and forgets where they put things, you'll have a much better experience.
The wild part is that the AI actually performs better when you limit its autonomy. I found that by narrowing the scope of the Workflows I was asking it to handle, the "looping" behavior disappeared. It turns out the agent struggles when the "diff" it has to manage across five different files becomes too large to track in a single turn.
Getting out of the echo chamber
I actually figured out the "verify imports" trick after browsing some threads in the PromptCube community. I had been trying to solve the looping issue by changing my prompts to be "more polite" or "more descriptive," which is useless. The people in PromptCube don't care about politeness; they care about token efficiency and context management.
They’ve already mapped out which AI Models handle agentic loops better than others. For instance, some users found that switching the underlying model in Cursor from Claude 3.5 Sonnet to GPT-4o (or vice versa) changed how the agent handled file system errors.
If you're tired of fighting your tools, joining a community like PromptCube is basically like getting a cheat sheet for your IDE. You stop guessing why the AI is hallucinating and start using actual patterns that other developers have already stress-tested. You can join by hitting up their landing page and jumping into the discussions.
My current "Agent" rules of thumb
Now, I use a specific set of rules to keep the agent from burning my house down:
- Small Commits: I commit every single time the agent finishes a "task" that actually works. If it starts looping, I
git reset --hard
immediately.
-
The "Stop" Command: The moment I see the AI apologize for the same error twice, I kill the process. Apologies are a sign that the agent is lost in its own context window.
-
Explicit Context: Never assume the agent knows which file you're talking about. Always use
@filename
.
It’s not perfect. I still occasionally find a random console.log("test")
left in my production code because the agent thought it was "helping" me debug. But the speed gain is too high to go back to purely manual typing.
Next LLMs sending "death threats" to their own creators is a weird →
these real-world AI monetization case studies, with plenty of directly applicable cases.
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