BoilerPrompt

The best AI coding assistants

Four assistants that edit code in an existing repo, compared on how they behave when you actually prompt them.

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Picks last checked . Jump to: Cursor, Claude Code, GitHub Copilot, Windsurf

An AI coding assistant works inside a codebase you already have. You point it at files, describe a change, and it edits, runs commands, and reports back. That is a different job from an app builder, which starts from an empty project and generates a whole application. If you have no repo yet, the app builders are the better read.

The four below are the ones worth your time in 2026, and they differ less in raw model quality than in where they live and how much rope they take. An editor-based assistant keeps every change visible as a diff. A terminal agent will happily run your migrations. That choice shapes your prompts more than the underlying model does.

Each pick links to its full prompt library here, because the honest way to compare these tools is to run the same request through each one and read what comes back.

How these were ranked

Ranked on four things: how much repo context the tool can pull in without hand-holding, whether it can verify its own work by running tests or a type checker, how reviewable its changes are before they land, and how well it holds team conventions across requests. Pricing matters less than it looks — all four sit close enough that the workflow fit decides it.

1. Cursor

Best overall, and the default recommendation

Cursor is a VS Code fork with the AI built into the editing loop rather than parked in a sidebar. Agent mode plans multi-file changes, runs terminal commands, and iterates on failing tests, while every edit lands as a diff you accept or reject. That reviewability is why it wins for most people: you get agent-scale changes without losing sight of what changed. Prompts work best at 60 to 160 words with the files scoped by @ mention and a verification step at the end.

What it does well

  • @ mentions scope a request to exact files and folders, which cuts the wrong-guess rate more than any prompt phrasing does
  • Rules files (.cursor/rules) pin team conventions once instead of repeating them in every prompt
  • Agent mode runs the test suite and iterates, so a plausible diff becomes a checked one

Where it falls down

  • Agent mode can touch a dozen files in a pass, and accepting without reading is how bad code ships
  • You are committing to its fork of VS Code, extensions and all

Pricing: Free tier with limited fast requests; paid individual plan; usage-based pricing on top for heavy agent use.

Cursor prompts

Prompts to try in Cursor

All 31 Cursor prompts

2. Claude Code

Best for large repo-wide work and anything shell-shaped

Claude Code runs in your terminal instead of an editor, which sounds like a downgrade until you need it to install dependencies, run migrations, grep an entire monorepo, or drive git. It handles tasks that span more files than an editor UI comfortably shows, and it closes the loop by running your tests. The tradeoff is that changes arrive as a summary and a diff rather than inline in the file you were looking at, so review discipline has to come from you.

What it does well

  • Genuinely good at repo-wide reasoning: renames, dependency upgrades, and cross-cutting refactors
  • Runs the real toolchain — installs, migrations, test suites, git — instead of simulating it
  • CLAUDE.md carries project conventions into every session without prompt repetition

Where it falls down

  • No inline completion, so it does not replace an editor assistant for line-by-line work
  • Terminal-only output means large diffs need deliberate review before you commit

Pricing: Included with Claude paid plans, or metered through the API. Heavy agentic sessions consume tokens fast.

Claude Code prompts

Prompts to try in Claude Code

All 22 Claude Code prompts

3. GitHub Copilot

Best if your org already lives in GitHub

Copilot's advantage is not the model, it is the distribution. It is already approved in most enterprises, it works in the editors people already use, and its review and chat features hang off pull requests your team is already opening. As a pure agent it takes on less than Cursor or Claude Code, and prompts need more explicit scoping because it pulls less context on its own. But it is the path of least resistance in an org that will not install a new editor.

What it does well

  • Editor-agnostic: VS Code, JetBrains, Neovim, and Visual Studio all supported
  • Inline completion is still the strongest part of the product and the least disruptive to flow
  • Procurement and compliance are usually already solved for it

Where it falls down

  • Agent behavior is more conservative, so multi-file changes need to be broken up
  • Pulls less surrounding context automatically — be explicit about files in the prompt

Pricing: Free tier with monthly completion limits; paid individual and business plans per seat.

GitHub Copilot prompts

Prompts to try in GitHub Copilot

All 20 GitHub Copilot prompts

4. Windsurf

Best for a quieter, more automatic flow

Windsurf is also a VS Code fork, and its bet is that the assistant should infer context rather than make you attach it. Cascade tracks what you have been editing and follows the thread across files with less manual scoping than Cursor asks for. When that inference is right it feels smoother than anything else here. When it is wrong you have less visible control over what it looked at, so prompts benefit from naming the boundary explicitly even though the tool does not require it.

What it does well

  • Cascade follows a working session across files without constant re-scoping
  • Lower prompt overhead for iterative work in a part of the codebase you are already in
  • Clean, uncluttered agent UI compared with its peers

Where it falls down

  • Smaller ecosystem and community than Cursor or Copilot, so fewer worked examples exist
  • Automatic context selection is harder to audit when it picks wrong

Pricing: Free tier available; paid individual and team plans with credit-based agent usage.

Windsurf prompts

Prompts to try in Windsurf

All 20 Windsurf prompts

Assistant or app builder?

The split is whether a codebase already exists. Assistants edit repos: they read your files, respect your conventions, and leave a diff. App builders generate projects: you describe an application and get scaffolding, a preview, and often hosting. Prompting them is different work — an assistant prompt names files and constraints, a builder prompt is closer to a product spec. If you are starting from nothing, read the app builder roundup instead.

What actually changes your results

Across all four tools the same three things move quality more than tool choice does. Scope: name the files, or say explicitly that the tool should search. Constraints: state the framework versions, patterns, and libraries your team forbids, because none of that is inferable from code alone. Verification: end the prompt with how to prove the change works — run the tests, type-check, hit the endpoint. A prompt with all three gets a usable diff from any of these tools. A prompt with none gets a plausible guess from all of them.

Put conventions in a rules file, not in every prompt

Every assistant here reads a project-level instructions file: .cursor/rules for Cursor, CLAUDE.md for Claude Code, copilot-instructions.md for Copilot, and Windsurf's rules. Anything you have typed into a prompt twice belongs there instead. It frees prompt space for the actual task, it applies to every request automatically, and it travels with the repo so teammates inherit it.

Common questions

Which AI coding assistant is best for beginners?

Cursor, because every change lands as a diff you approve before it touches your files. Seeing what the AI proposes, one file at a time, is the fastest way to build judgment about when it is wrong.

Can I use more than one at once?

Yes, and plenty of people do. A common setup is Copilot or Cursor for inline completion while editing, plus Claude Code in a terminal for larger repo-wide tasks. They operate on the same files without conflicting, as long as you are not running two agents on the same working tree at the same time.

Do these work with any programming language?

All four handle mainstream languages well — TypeScript, Python, Go, Java, Rust. Quality drops on niche or proprietary languages with little public code, and on internal frameworks the model has never seen. In those cases lean much harder on the rules file and on pasting real examples into the prompt.

Is a free tier enough?

For inline completion and occasional chat, yes. Agent mode is where the free tiers run out fast, because a single multi-file task with test runs consumes a lot of usage. If you are using agents daily, budget for a paid plan.

Narrow it down

Claude Code vs CursorClaude Code vs GitHub CopilotCursor vs WindsurfCursor vs GitHub CopilotClaude Code vs WindsurfWindsurf vs GitHub CopilotThe best AI app buildersThe best AI website builders