# Build a feature with Claude Code and Cursor together > Source: > Published: 2026-09-11 17:18:24+00:00 # Build a feature with Claude Code and Cursor together If you are choosing between [Claude Code](/en/tags/claude%20code/) and Cursor, stop thinking of them as competitors. They are different species. Cursor is an IDE; Claude Code is a CLI agent. Last Tuesday, I spent four hours trying to migrate a legacy Express.js middleware to a FastAPI equivalent. Cursor handled the boilerplate fast, but Claude Code actually figured out why my environment variables were leaking across threads—something Cursor's "Composer" mode kept hallucinating a fix for. ## Which one actually ships the code faster? [Cursor](/en/tags/cursor/) is my home base. I use it for the 90% of coding that requires a visual map of the project. But when I need to do "surgical" work across 15 different files—like renaming a database column and updating every single reference—Claude Code is faster because it doesn't wait for me to accept individual diffs in a UI. It just does it. Here is the breakdown from my last three sprints: | Task | Cursor ([Claude](/en/tags/claude/) 3.5 Sonnet) | Claude Code (CLI) | Winner | | :--- | :--- | :--- | :--- | | Feature scaffolding | 2 mins (via Composer) | 3 mins (manual prompts) | Cursor | | Complex refactoring | 15 mins (lots of manual review) | 6 mins (agentic loop) | Claude Code | | Debugging runtime errors | 5 mins (Paste log → fix) | 2 mins (it reads the log itself) | Claude Code | | UI/CSS Tweaks | Instant (Visual feedback) | Slow (Edit → Save → Refresh) | Cursor | ## Setting up Claude Code and fixing the common "Permission Denied" loop Installing Claude Code is straightforward, but the first time I ran it, I hit a wall with file permissions on macOS. If you see `Error: EACCES: permission denied` when it tries to write to your `.git` folder, don't just `sudo` the whole thing. That's a recipe for permission hell later. Run this to get it moving: ``` npm install -g @anthropic-ai/claude-code claude ``` When it asks for permissions, if it fails to index your project, it's usually because your project root has a weird ownership setting. I fixed mine by ensuring the current user owned the directory:`sudo chown -R $(whoami) /path/to/your/project` The real pain point with Claude Code is the "loop of death." This happens when the agent tries to run a test, fails, tries to fix it, fails again, and repeats this five times without changing the strategy. When you see this happening, kill the process (`Ctrl+C`) and feed it a specific hint. Instead of "fix the test," try: "The test is failing because the mock database isn't initializing in time. Check the `setup.ts` timeout." ## How to stop your API keys from leaking into the LLM Since Claude Code and Cursor both have access to your file system, the risk of accidentally sending a `.env` file to the provider is high. Most devs just rely on `.gitignore`, but LLMs sometimes ignore it if you explicitly tell them to "read all files in the directory." I follow three strict rules for LLM security best practices. First, never use your primary production key for AI-assisted dev. Use a "Developer" key with limited scopes. Second, use a `.claudeignore` or `.cursorignore` file. Create a `.cursorignore` in your root: ``` # Ignore all secret files .env .env.local config/secrets.yml *.pem *.p12 ``` Third, if you're building an [AI agent](/en/tags/ai%20agent/) that executes code, wrap it in a Docker container. I recently had a script that accidentally deleted a `node_modules` folder because the LLM misinterpreted "clean up the project." Running your agent in a container prevents it from touching your actual OS files unless you explicitly mount a specific volume. ## Integrating agentic flows into your day The secret is using Cursor for the "What" and Claude Code for the "How." I use Cursor to map out the logic and write the initial functions. Then, I drop into the terminal and let Claude Code handle the tedious integration. If you find yourself struggling to organize these prompts, checking out some [Workflows](/en/category/workflows/) from other devs can save you a few hours of trial and error. I spent way too long trying to make Claude Code write CSS; it's just not built for that. Stick to logic and architecture in the CLI. The cost is the only real friction. Claude Code consumes tokens aggressively because it sends a massive amount of context (file trees, shell outputs) with every turn. In one session of debugging a Webpack config, I burned through $12 of credits in 40 minutes. It's a steep price, but cheaper than me staring at a config file for four hours. ## When to ditch the AI and go manual AI agents are great until they start "hallucinating" a library that doesn't exist. Last month, Claude Code tried to use a method from a version of `Zod` that wasn't released yet. It looked perfectly valid in the code, but the build failed. The tell-tale sign you've hit the limit is when the agent starts apologizing. "I apologize for the confusion, let me try that again..." If you see that twice, stop. Take over the keyboard. Manually fix the line, then bring the agent back in for the next task. If you're looking for more tools or benchmarks to compare these models, the [Resources](/en/category/resources/) section of our community is a good place to start. Most of us are just trying to find the shortest path from "idea" to "deployed." Joining a community like PromptCube is basically about not solving the same bug twice. We share the exact prompts that actually worked—not the generic ones you find in marketing blogs. You can jump into the [PromptCube homepage](/en/) to see how others are chaining these tools together. ## Final setup checklist for the speed-run To get the most out of this duo, configure your environment like this: 1. **Cursor**: Set to "Claude 3.5 Sonnet" → Enable "Composer" (Cmd+I) → Set to "Project" context. 2. **Claude Code**: Install via NPM → Authenticate → Create a `.claudeignore` for secrets. 3. **Workflow**: - Design/UI → Cursor. - Refactoring/Testing/Log Analysis → Claude Code. - Security → Dockerized environment + scoped API keys. [Next Wrapture is a massive upgrade over standard monkey patching for observability →](/en/threads/9220/) [a practical ChatGPT prompt guide](https://tanyan888.com/), with plenty of directly applicable cases.