Cursor vs. Claude Code: Which AI Coding Agent Reigns Supreme?
The emergence of AI-powered coding agents has been one of the most exciting developments for software developers recently. Just this past week, two major players—Cursor and Anthropic’s Claude Code—launched their coding agents simultaneously. Intrigued by which tool might better serve developers, I decided to put both to the test on a real-world Rails application running in production. Here’s a detailed breakdown of my experience, comparing their user experience, code quality, cost, autonomy, and integration with the software development lifecycle.
The Test Setup: A Real Rails App with Complex Needs
My project is a Rails app acting as an email "roaster" for GPTs—essentially bots that process and respond to emails with unique personalities. The codebase is moderately complex and had been untouched for nine months, making it perfect for testing AI assistance on:
- Cleaning up test warnings and updating gem dependencies.
- Replacing LangChain calls with direct OpenAI API usage.
- Adding support for Anthropic’s API.
Both agents used the same underlying model—Claude 3.7 Sonnet—to keep the comparison fair.
User Experience (UX): Terminal Simplicity vs. IDE Integration
Cursor:
Cursor’s agent is integrated into a fully featured IDE and has recently made the agent the primary way to interact with the code. While this offers powerful context and control, I found the interface occasionally clunky—multiple “accept” buttons, cramped terminal panes, and confusing prompts requiring manual clicks. The file editor pane often felt unnecessarily large given that I rarely needed to manually tweak files mid-action.
Claude Code:
Claude Code operates as a CLI tool right in the terminal. You run commands from your project root, and it prompts you with simple yes/no questions to confirm each action. This single-pane approach felt clean, intuitive, and perfectly suited for delegating control to the agent. The lack of a GUI was a non-issue given the agent’s autonomy.
Winner: Claude Code for its streamlined, efficient command-line interaction.
Code Quality and Capability: Documentation Search Matters
Both agents produced similar code given the same model, but Cursor’s ability to search the web for documentation gave it a notable edge. When adding Anthropic support, Claude Code struggled with API syntax and ultimately wrote its own HTTP implementation. Cursor, however, seamlessly referenced web docs to get the calls right, rescuing itself from dead ends.
Winner: Cursor, thanks to its web search integration.
Cost: Subscription vs. Metered Pricing
- Claude Code: Approximately $8 for 90 minutes of work on these tasks. While reasonable, costs could add up quickly for frequent use.
- Cursor: $20/month subscription includes 500 premium model requests; I used less than 10% of that for this exercise, roughly costing $2.
Winner: Cursor, offering more usage for less money and a simpler subscription pricing model.
Autonomy: Earning Trust with Incremental Permissions
Claude Code shines here with a granular permission model. Initially, it asks for approval on commands; after repeated approvals, it earns trust to perform actions autonomously. By the end of my session, it was acting independently with minimal prompts.
Cursor, in contrast, lacks this “earned trust” feature. It repeatedly asks for confirmation without a way to grant blanket permissions. Given the nature of coding agents, I believe this is a feature Cursor should adopt soon.
Winner: Claude Code for smarter incremental permissioning.
Integration with Software Development Lifecycle
I emphasize test-driven development (TDD) and version control (Git), so how each agent handled these was crucial.
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Claude Code: Excellent at generating and running tests before coding features, ensuring quality. Its commit messages were detailed and professional—better than any I’ve written myself. Being a CLI tool, it felt natural coordinating commands and output.
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Cursor: While it offers a nice Git UI within the IDE and can autogenerate commit messages, these were more generic and less informative. Its handling of test outputs in a small terminal pane felt awkward.
Winner: Claude Code, for superior test and version control workflow integration.
Final Verdict: Use Both, But Lean Towards Claude Code—for Now
Both agents completed all three complex tasks successfully—a testament to how far AI coding assistants have come. It’s remarkable to see agents not only write code but also tests and meaningful commit messages that improve project maintainability.
That said, this is not a binary choice. I recommend developers use both tools in tandem:
- Use Cursor for day-to-day coding within your IDE, benefiting from its subscription model and web documentation search.
- Use Claude Code for command-line driven tasks that require incremental permissions, superior test integration, and detailed commit management.
For now, I personally prefer Claude Code for its user experience, autonomy model, and lifecycle integration. But Cursor’s rapid iteration pace means it will likely close these gaps soon.
Takeaway for Developers
If you’re a software developer curious about AI coding agents:
- Get the $20/month Cursor subscription to familiarize yourself with agent-assisted coding.
- Experiment with Claude Code in your terminal to experience granular control and trust-building autonomy.
- Use both to balance cost, control, and convenience.
- Embrace AI coding agents as powerful collaborators that can help you break through stalled projects and increase productivity.
The future of software development is here—and these AI coding agents are just getting started.
Have you tried Cursor or Claude Code? Share your experiences and thoughts in the comments below!