I have been using AI coding tools every single day for over a year now. Not casually, not for side projects on weekends — I mean eight-plus hours a day, shipping production code with these tools across mobile apps, backend services, and full-stack projects. I currently have active subscriptions to GitHub Copilot, Cursor, and Claude Code (via Claude Pro/Max). Each one lives in a different part of my workflow, and I have strong opinions about all of them.

This is not a feature-list comparison you can find on any marketing page. This is what it actually feels like to use these tools when deadlines are real and code quality matters.

My Setup

Here is how my daily workflow breaks down. I write code primarily in VS Code and the terminal. Copilot runs as a VS Code extension and handles inline suggestions while I type. Cursor is my go-to when I need to do medium-complexity refactors where seeing the diff visually matters. Claude Code lives in my terminal and handles the heavy lifting — large refactors, greenfield project scaffolding, and anything that requires reading and modifying many files at once.

I do not use one tool exclusively. That would be leaving performance on the table. Each has a sweet spot, and knowing when to reach for which tool is half the skill.

GitHub Copilot

Copilot is the gateway drug of AI coding. It is fast, it is everywhere, and it is good at exactly one thing: autocomplete on steroids.

When I am writing boilerplate — a new data model, a controller skeleton, repetitive test cases — Copilot nails it. The tab-to-accept flow is so natural that it feels like the IDE is reading my mind. For languages with strong patterns like Swift, Dart, or Go, Copilot’s suggestions are right more often than not.

But here is where it falls apart. Copilot has a narrow context window. It mostly looks at the current file and maybe a few open tabs. Ask it to refactor something that spans multiple files and it has no idea what you are talking about. It cannot reason about your project architecture. It does not understand that renaming a method in one file means updating imports in twelve others.

Copilot Chat improved things somewhat, but it still feels bolted on rather than integrated. You ask it a question, it gives you a code block, and you manually paste it in. That is not an AI workflow — that is Stack Overflow with extra steps.

Best at: Inline autocomplete, boilerplate generation, writing repetitive code fast.

Worst at: Multi-file edits, architectural reasoning, anything requiring deep project context.

Cursor

Cursor is what happens when you build an IDE around AI instead of adding AI to an existing IDE. And honestly, it shows.

The Composer mode is Cursor’s killer feature. You describe what you want changed across your project, and it generates a multi-file diff that you can review and apply. It is context-aware — it indexes your codebase and can reference files you have not even opened. For medium-sized refactors, this workflow is genuinely faster than doing it manually.

The inline editing with Cmd+K is also smooth. Highlight code, describe what you want, and it rewrites it in place. The UX is polished and the visual diff preview before applying changes gives you confidence.

But Cursor has problems. It can be slow — especially with large codebases, the indexing and response times lag noticeably. I have also caught it hallucinating file paths more than once, confidently referencing files that do not exist in my project. The subscription cost adds up too, and if you want the best models, you are paying premium on top of premium.

The biggest issue, though, is that Cursor is still fundamentally an IDE. You are limited to what you can do inside that window. It cannot run your tests, execute shell commands, or interact with your development environment the way a true agent can.

Best at: Multi-file refactors with visual diffs, codebase-aware editing, polished UX.

Worst at: Large-scale architectural changes, hallucinated paths, speed with big projects.

Claude Code

Claude Code is a different beast entirely. It is not an IDE extension. It is not even a GUI. It is a terminal-based agent that reads your files, writes code, runs commands, and iterates on the results. When I first tried it, the learning curve was steep. No pretty buttons, no syntax-highlighted previews — just you, your terminal, and a very capable AI.

But once it clicks, Claude Code is the most powerful coding tool I have ever used.

What makes it special is the agentic loop. You give Claude Code a task — “refactor the authentication module to use JWT tokens” — and it does not just suggest code. It reads your existing auth files, understands the current implementation, writes the new code, updates imports across the project, runs your tests, sees failures, fixes them, and runs the tests again. All without you touching the keyboard.

For greenfield projects, Claude Code is unmatched. I have scaffolded entire Flutter apps, complete with feature folders, GetX controllers, services, and routing, in a single conversation. I actually tested this to the extreme by building a full app without writing a single line manually. The MCP (Model Context Protocol) support means you can connect it to documentation servers, databases, and external APIs, making it even more context-rich — I covered how MCP servers work and why they matter in a separate post.

The weaknesses are real though. There is no GUI — you are reviewing diffs in the terminal, and if you are not comfortable with that, you will struggle. It is token-heavy, meaning complex tasks can burn through your quota fast. And because it has full file system access, you need to pay attention. I have had it delete files it should not have when instructions were ambiguous.

Best at: Large refactors, greenfield projects, agentic multi-step tasks, MCP integrations.

Worst at: Quick inline edits, visual feedback, token efficiency, beginner friendliness.

Head-to-Head Comparison

When I Use What

My workflow has settled into a clear pattern:

Copilot stays on all the time. It is background intelligence. While I am typing a function, it suggests the next line. While I am writing a test, it fills in the assertions. I do not think about it — it just makes me faster at the mechanical parts of coding.

Cursor comes out when I need to change something across three to ten files and I want to see what is happening. Renaming a shared component, updating an API response shape that touches multiple layers, refactoring a utility module. The visual diff review gives me confidence that nothing broke.

Claude Code is my power tool for the big jobs. Starting a new project from scratch. Migrating an entire codebase from one architecture pattern to another. Writing a comprehensive test suite for an untested module. Setting up CI/CD pipelines. Anything where I would normally spend half a day planning before writing code — Claude Code compresses that into a conversation.

The rule of thumb: if the task takes less than a minute of thought, Copilot handles it. If it takes five to fifteen minutes of planning, Cursor is the right tool. If it takes an hour or more, Claude Code saves me the most time.

The Future

These tools are converging fast. Copilot is adding agent capabilities. Cursor is getting better at running commands. Claude Code is improving its UX with each release. In twelve months, the lines between them will be blurrier than they are today.

The direction is clear: agents are the next frontier. The IDE-as-we-know-it is becoming a legacy interface. The future is describing what you want built, having an AI agent implement it across your entire codebase, run the tests, and hand you a working pull request. Claude Code is closest to that vision today, but everyone is racing toward it.

I also expect MCP to become a standard. The ability for your AI coding tool to pull in live documentation, query your database schema, or check your deployment status while it writes code — that is not a nice-to-have, it is table stakes.

My Recommendation

If you can only pick one, pick Claude Code. It has the highest ceiling and the broadest capability. Yes, the learning curve is real, but you are a developer — you learned Git, you learned Docker, you can learn to work in a terminal with an AI agent.

But if you want the actual sweet spot, here is my combo: Claude Code + GitHub Copilot.

Copilot handles the fast, low-effort suggestions while you type. Claude Code handles everything else — the big refactors, the new features, the debugging sessions that would normally take hours. Together, they cover the full spectrum from “autocomplete this line” to “rebuild this entire module.”

Cursor is a great tool and I still use it, but if I had to drop one from my stack tomorrow, it would be Cursor. Claude Code does everything Cursor does and more — it just does it in a terminal instead of a GUI.

Stop debating which AI tool is best. Use multiple. Know when to reach for each one. That is what separates developers who are using AI from developers who are leveraging it.