AI Code Review: Cursor, Claude Code, GitHub Copilot Reviewed
I use all three weekly. Here's what each is genuinely good at, and where each fails.
Three of the leading AI coding tools have very different strengths. I've spent enough time in each to have opinions worth recording. This is the working comparison I share with clients.
I use Cursor, Claude Code, and GitHub Copilot weekly across client work. They're often discussed as competitors. They're really three different tools that overlap in confusing ways. Here's how I use each.
The summary, if you only read this
- Claude Code for deep, multi-file changes where I want the model to plan and execute.
- Cursor for fast inline edits, when I want to drive and the model assists.
- Copilot for autocomplete inside the editor and PR review hints.
I use all three. I don't think they replace each other. I think they fit different parts of the loop.
Claude Code: deep work
Claude Code (the CLI) is the tool I use when I want to delegate. I describe a task, the model plans, executes file edits, runs tests, iterates.
Where it shines:
- Migrations. I migrated a 14-file Spring Boot service to Java 21 records in one Claude Code session. The model edited each file consistently, ran tests, fixed regressions.
- New features that span layers. Adding a new API endpoint with controller, service, repository, tests, and migrations. Claude Code holds the whole picture better than I can while typing.
- Refactors. Renaming, extracting, restructuring. Claude Code is more careful about consistency than I am at hour seven.
Where it fails:
- Debugging unfamiliar production issues. Without strong context, the model speculates. I'd rather drive.
- Tasks where I have a strong opinion already. I don't want it negotiating with me. I want to write it myself.
- Anything time-sensitive. It's slower than typing for small tasks. Don't reach for it for one-line fixes.
The cost is real. A serious Claude Code session can run $5-15 in API spend. For a one-day feature, that's a rounding error. For trivial tasks, it's overkill.
Cursor: fast inline assistance
Cursor is a fork of VS Code with deep model integration. I use it like an amped-up editor.
Where it shines:
- Cmd-K edits. Highlight a function, describe the change in plain English, get a diff. This is the killer feature.
- Tab completion in unfamiliar codebases. When I'm working in someone else's repo, Cursor's project-aware autocomplete reads context I don't have time to load mentally.
- Quick prototypes. When I'm exploring an idea, Cursor lets me iterate without context-switching.
Where it fails:
- Long-context reasoning. It doesn't hold the whole codebase the way Claude Code can. For deep planning, I switch out.
- Predictability. The same prompt sometimes gets a different model behavior between sessions, which makes it hard to build muscle memory.
- Cost in agent mode. Cursor's agent mode is similar in cost to Claude Code, without quite the same depth.
I use Cursor as my default editor. I switch to Claude Code for the heavy work.
GitHub Copilot: ambient autocomplete
Copilot is the tool I notice the least, which is its strength. It autocompletes as I type, occasionally hallucinates a function name, mostly stays out of the way.
Where it shines:
- Autocomplete in the IDE. Genuine productivity boost on idiomatic code (boilerplate, tests, common patterns).
- PR review summaries. The new Copilot pull-request review feature is solid for surface-level review of small PRs.
- Cost. $10/month flat. The cheapest way to get AI coding assistance.
Where it fails:
- Anything cross-file. Copilot's context is the open buffer, occasionally the open project. It's not cross-cutting.
- Architectural decisions. Don't ask. It will autocomplete the answer and the answer will be average.
- Languages outside the top 10. It's noticeably worse on less-common stacks.
For a team that doesn't want to think about AI tooling, Copilot is the cheapest, most boring choice. That's a real virtue.
Where each one is dangerous
Each tool fails in characteristic ways:
- Claude Code can confidently make sweeping changes that compile and pass tests but quietly change semantics. Always read the diff before committing.
- Cursor can autocomplete plausible-but-wrong code that's hard to spot in a 30-line block. Be slower than feels natural.
- Copilot has the highest hallucination rate on function calls. Verify any line of suggested code that calls into a library you don't know.
I have a personal rule: never accept AI-written code I don't understand. Read every line. If I can't explain why it's correct, I don't ship it.
How I'd compose them on a typical day
A real day from last week:
- 8 AM, planning: I describe the day's tasks to Claude Code, ask it to break each into a checklist.
- 9 AM-12 PM, deep work: Claude Code runs in the background on a multi-file migration while I review and steer.
- 1 PM-3 PM, feature work: I drive in Cursor with Cmd-K edits, ship a feature.
- 3 PM-5 PM, code review: Copilot summarizes PRs, I review the summaries, then read the actual diffs.
Each tool earns its keep. None of them replace the others.
The cost stack for one engineer
- Claude Code: typical $80-150/month at heavy usage.
- Cursor Pro: $20/month.
- GitHub Copilot: $10/month.
For around $120/month, you have an excellent AI-assisted setup. That's about 30 minutes of senior time. The break-even is roughly trivial.
The sharper insight
The tools that look most like editors get used most. The tools that look most like agents get used most carefully. Copilot blends in, so it gets used hundreds of times a day, mostly safely. Claude Code requires deliberate engagement, so each use is a deliberate decision. The middle tools, like Cursor's agent mode, are the dangerous ones, because they're tempting to over-use without the ceremony that an explicit agent invocation has.
Pick your tools based on the failure modes you can tolerate, not the demos you can be impressed by.
For more on AI in production, see agents in production 2026.