We Compare AI

Best AI for Coding

Ship faster, debug smarter, and write cleaner code with AI pair programmers built for developers.

Top Tools

The best AI tools for this use case, ranked by fit.

GitHub Copilot

Paid

$10 / $19 per month

Best for: Inline autocomplete inside VS Code, JetBrains, Neovim

Claude (Anthropic)

Freemium

$0 / $20 per month

Best for: Architecture decisions, large refactors, code review

Cursor

Freemium

$0 / $20 per month

Best for: Full AI-native coding environment

Pros & Cons

Honest trade-offs for the top tools in this category.

GitHub Copilot

Paid
Pros
  • Deeply integrated into VS Code and JetBrains IDEs
  • Context-aware autocomplete from your entire codebase
  • Copilot Chat for inline Q&A, debugging, and explanations
Cons
  • No free tier (trial only)
  • Suggestions can be subtly wrong — always review

Claude (Anthropic)

Freemium
Pros
  • 200k context — paste an entire codebase for review
  • Excellent at explaining why code is wrong, not just fixing it
  • Strong reasoning for system design and architecture questions
Cons
  • Not embedded in an IDE by default
  • No real-time autocomplete

Cursor

Freemium
Pros
  • VS Code fork with built-in GPT-4o, Claude 3.7, and Gemini integration
  • Codebase-wide context awareness with @codebase
  • Agent mode can write, run, and debug multi-file features autonomously
Cons
  • Requires switching from your existing IDE setup
  • Pro plan needed for high-usage or GPT-4 models

Pricing Overview

What you get at each price tier across the top tools.

ToolFree TierPaid TierAPI Access
GitHub Copilot30-day trial onlyIndividual $10/mo, Business $19/user/moNo
Claude (Anthropic)Claude 3.5 Haiku with daily limitsClaude 3.7 Sonnet, 200k context — $20/moYes
Cursor2000 code completions + 50 slow requestsUnlimited completions, fast requests — $20/moNo

Example Workflows

Follow these step-by-step workflows to get real results today.

1

Debug a Tricky Bug

  1. 1

    Copy the error message, relevant stack trace, and the surrounding code (50–100 lines).

  2. 2

    Paste into Claude with: 'Here is the error and the code. Explain what is causing this and why.'

  3. 3

    Ask for a fix, then ask: 'What tests should I add to prevent this from regressing?'

  4. 4

    Copy the fix into your IDE and use GitHub Copilot to autocomplete the test cases Claude suggested.

2

Build a New Feature End-to-End

  1. 1

    Describe the feature to Claude: 'I need to build X. Here is my current data model and tech stack. Draft the architecture.'

  2. 2

    Iterate on the architecture plan until it covers edge cases and fits your stack.

  3. 3

    Open Cursor, use @codebase to give it full context, and implement each component using the plan.

  4. 4

    Ask Claude to do a final code review: paste the final implementation and ask for security, performance, and readability feedback.

  5. 5

    Write a one-paragraph summary of what the feature does and ask ChatGPT to turn it into a PR description.

Still not sure which tool is right for you?

Answer 6 questions and get a personalised AI stack recommendation matched to your exact needs and budget.

Take the AI Tool Finder quiz