A year ago, "AI pair programming" mostly meant autocomplete that finished your current line. Now the leading tools can read your whole codebase, plan a multi-file change, run the terminal commands themselves, and iterate on the result — closer to an actual pairing partner than a smarter autocomplete.
The three names that come up constantly are Cursor, GitHub Copilot, and Windsurf, each betting on a slightly different idea of what "AI pair programming" should feel like. This isn't a "one tool wins" situation — which one fits depends heavily on your existing editor, your codebase size, and how much you want the AI acting autonomously versus staying in a tight suggest-and-approve loop.
In this article
- Quick Comparison
- Cursor — best for deep, codebase-wide understanding
- GitHub Copilot — best for editor flexibility and GitHub-native teams
- Windsurf — best for agentic, multi-step tasks
- Amazon Q Developer — best for AWS-heavy teams
- GitLab Duo — best if you live in GitLab end to end
- Frequently Asked Questions
- Do I have to switch my whole editor to use these?
- Which one is best for a large, existing codebase versus a new project?
- Is it safe to let these tools run terminal commands automatically?
- Can I use more than one of these at once?
- Which one is cheapest to try first?
- Final Verdict
Quick Comparison
| Tool | Editor | Standout strength | Pricing model |
|---|---|---|---|
| Cursor | Standalone (VS Code fork) | Deep codebase-aware chat and multi-file edits | Free tier + Pro/Business plans |
| GitHub Copilot | Plugin (VS Code, JetBrains, more) | Widest editor support, tightest GitHub integration | Free tier + paid individual/business plans |
| Windsurf | Standalone (VS Code fork) | Agentic "Cascade" flows that plan and execute multi-step changes | Free tier + paid plans |
| Amazon Q Developer | Plugin + CLI | Best fit for teams already on AWS | Free tier + paid Pro plan |
| GitLab Duo | Built into GitLab | AI woven through the whole GitLab CI/CD lifecycle, not just the editor | Included in higher GitLab tiers |
Cursor — best for deep, codebase-wide understanding
Cursor forked VS Code specifically to build AI in at a deeper level than a plugin can reach, and it shows in how well it understands context across an entire codebase rather than just the open file. Its chat and multi-file edit features are consistently the strongest reason developers switch their whole editor rather than just adding a plugin.
GitHub Copilot — best for editor flexibility and GitHub-native teams
GitHub Copilot works as a plugin across far more editors than Cursor or Windsurf, so teams that don't want to change their whole setup can add it to whatever they're already using. Its integration with GitHub itself — PRs, issues, Actions — is also the tightest of any tool here if your team already lives in GitHub.
Windsurf — best for agentic, multi-step tasks
Windsurf's "Cascade" feature is built for handing off a larger task — like "add this feature end to end" — and having the AI plan the steps, make the changes across files, and run commands to verify them, checking in with you along the way rather than one suggestion at a time. It suits developers comfortable delegating more and reviewing the result, rather than approving every individual suggestion.
Amazon Q Developer — best for AWS-heavy teams
Amazon Q Developer is the natural pick if your infrastructure is already deep in AWS, since it understands AWS services and can help with infrastructure code and cloud-specific debugging in a way the more general-purpose tools don't specialize in.
GitLab Duo — best if you live in GitLab end to end
GitLab Duo doesn't just live in the editor — it's woven through GitLab's CI/CD pipeline, merge requests, and security scanning, so teams already standardized on GitLab get AI assistance across the whole software lifecycle rather than just while writing code.
Frequently Asked Questions
Do I have to switch my whole editor to use these?
Only for Cursor and Windsurf, which are standalone VS Code forks — GitHub Copilot works as a plugin inside your existing editor, and GitLab Duo/Amazon Q Developer integrate into GitLab or AWS-adjacent workflows respectively without requiring an editor switch.
Which one is best for a large, existing codebase versus a new project?
Cursor and Windsurf both handle large existing codebases well thanks to strong codebase-wide context, while Copilot tends to shine more on smaller, well-scoped changes and inline suggestions rather than sweeping multi-file refactors.
Is it safe to let these tools run terminal commands automatically?
Windsurf's agentic Cascade mode and similar features in Cursor typically ask for confirmation before running commands by default, and most teams keep that confirmation step on for anything touching production systems or irreversible operations.
Can I use more than one of these at once?
Technically yes, but most developers settle on one primary tool since running two AI assistants against the same codebase can create conflicting suggestions; it's more common to pair one general coding assistant with a specialized tool like Amazon Q Developer or GitLab Duo for platform-specific work.
Which one is cheapest to try first?
All five have a free tier, so cost isn't usually the deciding factor for a first trial — editor preference and whether your team is already anchored to GitHub, GitLab, or AWS tends to matter more.
Final Verdict
If you're open to switching editors, Cursor and Windsurf currently offer the deepest AI integration — pick Cursor for codebase-wide chat and Windsurf if you want more autonomous, multi-step task execution. If you'd rather keep your current editor, GitHub Copilot is the safest, most widely supported choice. Teams anchored to a specific platform should weight Amazon Q Developer or GitLab Duo accordingly. Explore more in Development & Code tools.