Why I Use Claude Code Instead of Cursor

Every week, someone asks me which AI coding tool they should use. Cursor? Windsurf? GitHub Copilot? My answer is always the same: Claude Code.

This isn't a popular opinion. Cursor has beautiful marketing. Windsurf has VC funding. But after building dozens of projects with AI assistance, I've learned that the pretty wrappers are often the wrong choice.

Here's why I work directly with Claude Code.

The Wrapper Problem

Let me explain what I mean by "wrapper." Cursor, Windsurf, Cody, and similar tools are essentially IDE plugins that sit between you and the underlying AI model. They add a layer of abstraction—sometimes a nice UI, sometimes useful features—but always at a cost.

What You're Actually Paying For

When you use Cursor, you're paying for:

A UI layer that translates your actions into API calls
Context management that decides what to send to the model
Prompt engineering that someone else designed
Feature limitations based on what the wrapper team prioritized

Notice what's missing? The actual intelligence. That comes from the underlying model—in Cursor's case, often Claude or GPT-4.

The Middleman Tax

Every layer of abstraction has a cost:

Context window waste. Wrappers often send boilerplate, system prompts, and metadata that eat into your precious context. Claude Code gives you direct access to the full 200K tokens. Wrappers? You're lucky to get half that in practice.

Capability lag. When Anthropic releases a new feature, Claude Code gets it immediately. Wrappers need to implement support, test it, and ship an update. That can take weeks or months.

Hidden prompt engineering. Wrappers inject their own prompts, which might not align with your needs. You're trusting their engineers made the right choices for your use case.

Debugging opacity. When something goes wrong, you can't see what actually happened. Was it the model? The wrapper? The prompt? Good luck figuring that out.

What Claude Code Actually Gives You

Let me be concrete about what working directly with the model looks like.

Full Context Window

Claude's 200K token context window is massive. That's roughly 150,000 words—an entire codebase in one conversation. I regularly work with projects that have 30K-50K lines of code, and Claude Code handles them without breaking a sweat.

Try that with a wrapper. Most limit you to a few files at a time because they're managing context on your behalf. That means more back-and-forth, more confusion, and worse results.

Terminal-Native Workflow

Claude Code runs in the terminal. No Electron app eating RAM. No GUI getting between you and your code. Just a clean interface that integrates with your existing workflow.

This matters more than people think. When your AI tool is a terminal command, it composes with everything else: shell scripts, pipelines, automation. You can run Claude Code in a loop (hello, Ralph Loops) or pipe its output to other tools.

Transparent Operation

Every interaction with Claude Code is visible. You can see exactly what context is being sent, what the model is doing, and what files are being modified. There's no hidden magic—just clear, auditable operations.

When something goes wrong, you know exactly where to look.

Latest Capabilities

Anthropic ships fast. New features, improved reasoning, better code understanding—these improvements land in Claude Code immediately. I'm always working with the latest version of the model.

Wrappers are inherently behind. They need to implement support for new features, which means you're always using yesterday's AI.

When Wrappers Might Make Sense

I'm not saying wrappers are always wrong. There are legitimate use cases:

Beginners who need training wheels. If you're new to AI coding and need a gentle introduction, Cursor's UI might help you get started. Just recognize you'll eventually want to graduate.

Teams with strict security requirements. Some organizations need to control exactly what data leaves their network. Enterprise wrapper deployments can provide that control. (Though Claude Code's headless mode increasingly addresses this too.)

Specific IDE integrations. If you absolutely must have AI in VS Code and won't use the terminal, a wrapper is your only option.

But for serious work—building real products, handling large codebases, maximizing productivity—direct model access wins.

The Real Skill: Model Understanding

Here's what most people miss: the value isn't in the tool, it's in understanding the model.

When you work directly with Claude Code, you learn:

How to structure prompts for best results
What context the model needs (and doesn't need)
When to break tasks into smaller pieces
How to verify and iterate on AI-generated code

These skills transfer. They make you better at working with any AI tool. They're the real competitive advantage in AI-assisted development.

Wrapper users often develop "tool muscle memory" instead. They know which Cursor button to click, but they don't understand why. When the wrapper changes or they need to use a different tool, they're lost.

A Practical Example

Let me show you a real scenario. Say I need to refactor a React component to use a new API.

With Claude Code:

claude --print "
Read src/components/UserProfile.tsx and src/services/api.ts.

The API has been updated to v2. The new endpoint is /api/v2/users/:id
and returns { user: { ...userData }, metadata: { ... } } instead of
the flat user object.

Update UserProfile to:
1. Use the new API response structure
2. Handle the metadata field appropriately
3. Maintain backwards compatibility during migration
"

I see exactly what's happening. I can refine the prompt if needed. I get the full context window for complex refactors.

With a Wrapper:

Click on the file. Cmd+K. Type a request. Hope the wrapper sends the right context. Get a response. Realize it missed something because the wrapper didn't include api.ts. Try again. Click more buttons.

The wrapper adds friction at every step.

The Business Case

If you're a business leader evaluating AI coding tools, here's what matters:

Total cost of ownership. Wrappers charge subscription fees on top of API costs. Claude Code is just API costs—often cheaper for heavy users.

Capability trajectory. Anthropic is shipping improvements constantly. Direct access means you benefit immediately. Wrappers mean you wait.

Skill development. Developers who learn to work with models directly become more valuable. They understand the technology, not just the UI.

Flexibility. Model vendors compete. Today Claude is best for coding; tomorrow it might be different. Direct model access means you can switch. Wrapper lock-in means you can't.

My Recommendation

If you're serious about AI-assisted development, invest time in learning Claude Code. Yes, there's a learning curve. Yes, it requires comfort with the terminal. But the payoff is worth it.

Start with simple tasks. Read the documentation. Experiment with prompts. Build up to larger projects.

And when someone asks you which AI coding tool to use, you'll have an answer that goes deeper than marketing and hype.

The Contrarian Position

I know this opinion isn't mainstream. The AI coding tool market is flooded with VC money, and wrappers have massive marketing budgets. Every week there's a new "Cursor killer" promising to revolutionize coding.

But when you look past the marketing, the logic is simple:

The intelligence comes from the model
Wrappers add layers between you and the model
Layers cost performance, capability, and control
Therefore, direct access is better

This isn't about being anti-tool. It's about being pro-understanding. The developers who will thrive in the AI era are the ones who understand the technology, not just the interfaces.

Claude Code gives you that understanding. Wrappers hide it.

Choose accordingly.

Want to see how direct model access can accelerate your development? Book a free consultation and let's explore what Claude Code can do for your projects.