Same tasks. Same codebase. Three tools. Two weeks. One developer who got increasingly opinionated.
I want to start with an admission.
I went into this comparison expecting Cursor to win. I've been using it for eight months, I know its quirks and I've got my keybindings dialled in. Trying two other tools for two weeks felt like the kind of exercise that confirms what you already believe.
That's not what happened.
Here's the setup: I'm a full-stack developer working primarily in React and Python. For the two-week evaluation period I ran three parallel workstreams, one in Claude Code, one in Cursor, one in Windsurf, rotating which tool I used for each task type to avoid the "I'm just more comfortable with this one" bias. Every tool got the same four task categories: refactoring a production React app, debugging a Python FastAPI service, writing tests for legacy code I didn't write and building a greenfield feature from a spec.
I scored each tool on four dimensions at the end of each task: speed (time to usable output), accuracy (did it actually work first try), context handling (did it understand the codebase, not just the file) and developer experience (did using it feel like assistance or friction).
This is what I found.
The Setup
Codebase: A mid-size SaaS application. React frontend (~18,000 lines), Python FastAPI backend (~12,000 lines), PostgreSQL, some legacy Flask code that predates the FastAPI migration and hasn't been touched in 18 months.
Claude Code: Terminal-based, runs in your existing environment. Uses Claude Sonnet under the hood. No IDE required, you work in your normal editor and interact with the agent through the terminal.
Cursor: VS Code fork with AI baked into the core editing experience. Inline completions, chat sidebar, Cmd+K for targeted edits. Model options include Claude, GPT-4o and Cursor's own models.
Windsurf: Also VS Code-based, from Codeium. Cascade is their agentic mode, it takes multi-step tasks and executes them with more autonomy than traditional inline completion.
All three were running with full codebase indexing enabled. This matters more than most reviews acknowledge, a tool with great generation capability but poor context retrieval is less useful than a tool with good generation and excellent context handling.
Task 1: React Refactoring
The task: A component file that had grown to 847 lines. Multiple concerns mixed together, data fetching, business logic, presentation. Classic "this was fine six months ago" situation. Goal: split into sensibly-scoped components with proper separation of concerns, without breaking any existing behaviour.
Claude Code performance: Score: 8.5/10
Asked Claude Code to analyse the component and propose a refactoring plan before touching anything. The plan it produced was genuinely thoughtful, it identified four distinct concerns, proposed a component hierarchy and flagged two places where the existing code had implicit dependencies I hadn't noticed. The actual refactoring took three rounds of iteration. Final output was clean and the tests still passed.
What stood out: it understood that I didn't want it to just split the file mechanically. It read the existing patterns in the rest of the codebase and matched them. That cross-file pattern recognition was noticeably better than I expected from a terminal-based tool.
What was annoying: the terminal interface creates friction when you want to make small adjustments. Having to type out instructions for minor tweaks felt slower than just doing it myself.
Cursor performance: Score: 8/10
Cursor's Cmd+K for targeted edits is fast and pleasant for this kind of work. The inline experience is better than anything else when you're making surgical changes. Where it struggled was with the big-picture refactoring question, what should the component hierarchy look like? It gave me a technically correct answer but it was generic. It didn't read the wider codebase conventions as deeply as Claude Code did.
Windsurf performance: Score: 8/10
Windsurf's Cascade mode handled this well. I gave it the task and it went away and came back with a restructured set of files. The output was correct and well-structured. The developer experience felt slightly more hands-off than I wanted, I like to be in the loop on structural decisions and Cascade's autonomous execution style means you're reviewing outputs rather than guiding the process.
Winner: Claude Code (narrow)
Task 2: Python API Debugging
The task: An intermittent 500 error in the FastAPI service. Showed up under specific query parameter combinations. No obvious error in the logs at first glance. The kind of bug that costs you a morning.
Claude Code performance: Score: 9/10
This is where Claude Code genuinely impressed me. I gave it the error symptoms and asked it to investigate. It read through the relevant endpoint code, traced the query parameter handling, identified that the issue was in how None values were being coerced in a Pydantic model with a custom validator and produced a fix with an explanation that made the root cause clear.
The investigation process felt like pairing with a senior developer. It reasoned through the problem rather than pattern-matching to common solutions. The fix was correct first try.
Cursor performance: Score: 7/10
Cursor found the right file quickly and made a reasonable suggestion. It identified the Pydantic model as the likely source and suggested a fix that would have resolved the most common version of this bug. It missed the specific None coercion issue in the custom validator and the fix it proposed wouldn't have caught the edge case that was actually causing the error. I would have spent time testing it and come back disappointed.
Windsurf performance: Score: 7.5/10
Better than Cursor on the diagnosis, slightly worse on the explanation. It got to the right area of the codebase faster than Cursor and its suggested fix was closer to correct. The explanation of why the bug existed was thinner, I understood what to change but not clearly enough to be confident I was fixing the right thing.
Winner: Claude Code (clear)
Task 3: Writing Tests for Legacy Code
The task: The legacy Flask code. 18 months old, written by a developer who's no longer at the company, no existing tests, inconsistent patterns throughout. Goal: meaningful test coverage on the three most critical endpoints.
Claude Code performance: Score: 7.5/10
Claude Code read the legacy code carefully and wrote tests that covered the actual behaviour, including some edge cases that weren't obvious from the function signatures. The tests were correct. They were also verbose, it has a tendency toward comprehensive coverage that sometimes produces more test code than you need for a first pass.
Cursor performance: Score: 8.5/10
This was Cursor's best category. The inline test generation is smooth, the pytest structure it produces is idiomatic and it strikes a better balance between coverage and conciseness than Claude Code. For test writing specifically, the IDE-native experience works in its favour, seeing the test appear in context, alongside the code it's testing, is genuinely nicer than receiving it in a terminal output.
Windsurf performance: Score: 7.5/10
Competent but not standout. The tests were correct and covered the right scenarios. Nothing exceptional about the developer experience in this category, it felt like a capable tool doing its job rather than surprising me.
Winner: Cursor
Task 4: Greenfield Feature
The task: A new notification preferences system. Users can configure which events trigger email vs in-app notifications, with per-workspace overrides. I had a spec document and the existing user and workspace models to work from.
Claude Code performance: Score: 9/10
This was the task that changed my prior. Claude Code read the spec, read the existing models and asked two clarifying questions before writing any code, questions that revealed a genuine ambiguity in my spec that I hadn't noticed. The implementation it produced was architecturally coherent with the existing codebase patterns. Database migration, Pydantic models, API endpoints and a suggested React component structure, all in one session, all consistent with each other.
The clarifying questions are worth highlighting separately. I've never had a coding tool ask me a clarifying question before. It felt like the tool was treating the spec as a brief rather than a command, which is the right orientation for a complex feature.
Cursor performance: Score: 7.5/10
Good at generating individual pieces but less strong at the architectural coherence question. I got a database model, then endpoint code, then frontend components, each individually reasonable, but with minor inconsistencies between them that I had to reconcile manually. For a multi-component feature, the lack of a planning step shows.
Windsurf performance: Score: 8/10
Windsurf's autonomous mode handled the coherence problem better than Cursor. It planned the implementation before executing it, which resulted in more consistent outputs across the components. The developer experience was still more hands-off than I wanted for a complex feature.
Winner: Claude Code
The Summary Scores
The Honest Caveats
These scores reflect my stack, my codebase and my working style. Three things worth knowing before you weight them.
Cursor wins on developer experience for small, fast tasks. The inline completion and Cmd+K workflow is genuinely better than anything else for surgical edits. If you spend most of your day on targeted changes rather than large reasoning tasks, Cursor's average score in my evaluation undersells it.
Claude Code's terminal interface is a real trade-off. The reasoning quality is the best of the three. The interface friction is also the highest. Whether that trade-off works depends on how often you're doing the kinds of tasks where reasoning depth matters.
Windsurf's autonomous mode needs trust. It produces good outputs but it does things without narrating them, which is uncomfortable until you've built confidence in it. For developers who want to be in the loop at every step, this is friction. For developers who are comfortable delegating, it's efficiency.
For the full Claude Code vs Cursor vs Windsurf comparison including enterprise team considerations, model tier analysis and pricing breakdown, the Dextra Labs deep-dive covers what two weeks of personal evaluation can't.
What I'm Using Now
Two weeks in, I've settled into a hybrid approach that I didn't anticipate: Claude Code for complex reasoning tasks, debugging, architecture, greenfield features and Cursor for the day-to-day editing flow where the inline experience is hard to beat.
Windsurf is genuinely impressive and I expect it to be my primary tool within six months as I build more trust in Cascade's autonomous execution. The output quality is there. The workflow integration is almost there.
Your mileage will vary by stack and team size. For enterprise teams evaluating these tools with a structured benchmark against your actual codebase, Dextra Labs runs tailored evaluations that go beyond what a two-week personal trial can surface. The tool that wins on my React and Python stack may not be the tool that wins on your Java monolith or your data engineering pipeline.
Published by Dextra Labs | AI Consulting & Enterprise Development Tools
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