The 5 Best AI Coding Tools for Developers (2025)

AI coding assistants have moved well beyond autocomplete. The best tools now read your codebase, edit multiple files, run commands, and review pull requests. Here are five strong options, what each does best, where each falls short, and how to pick the one that fits your workflow.

Quick comparison

Prices change often, so check each vendor's pricing page before you buy. You can also browse all AI coding tools in our directory.

1. GitHub Copilot

GitHub Copilot is the most widely adopted AI coding assistant, and it has grown into a full platform: inline suggestions, chat, agent mode in the editor, a command-line tool, AI code review, and a cloud coding agent that can work on issues and open pull requests.

Strengths

• Works in VS Code, Visual Studio, JetBrains IDEs, and more.
• Deep integration with GitHub issues, pull requests, and code review.
• Access to multiple models from different providers.
• Business and Enterprise plans add policy management, IP indemnity, and SSO.

Weaknesses

• Plan structure and usage credits can be confusing.
• Some advanced features are limited to higher tiers.

Best for: Developers and companies already living in GitHub.

Pricing: Free plan available with limited usage; paid plans from about $10/month, with higher tiers for heavier agent use (check current pricing).

2. Cursor

Cursor is a code editor built around AI, based on VS Code, so your extensions and keybindings carry over. Its agent can plan and apply changes across many files, and it supports cloud agents, MCP integrations, and automated code review through Bugbot.

Strengths

• Excellent multi-file editing and codebase-aware chat.
• Familiar VS Code feel with minimal setup.
• Choice of frontier models.
• Team plans include privacy mode, SSO, and admin controls.

Weaknesses

• You have to switch editors, which some teams resist.
• Heavy agent use can push you into higher tiers or usage-based billing.

Best for: Individual developers and startups who want the most polished AI-first editor.

Pricing: Free Hobby plan available; Pro from about $20/month, with Teams from about $40/user/month (check current pricing).

3. Claude Code

Claude Code is Anthropic's agentic coding tool. It runs in your terminal and also connects to IDEs such as VS Code and JetBrains, reading your project, editing files, running tests and commands, and working through multi-step tasks with your approval.

Strengths

• Strong at large refactors, debugging, and tasks that span many files.
• Works with any editor because it runs from the terminal.
• Extensible with MCP servers, custom commands, and hooks.
• Uses Anthropic's Claude models, which are widely used for coding.

Weaknesses

• Terminal-first workflow has a learning curve if you prefer a GUI.
• Usage limits depend on your plan, and API usage is billed per token.

Best for: Experienced developers who want an agent that can take on bigger, well-defined tasks.

Pricing: Included with paid Claude plans, starting from about $20/month, or pay-as-you-go through the API (check current pricing).

4. Windsurf

Windsurf is another AI-native editor, built around its Cascade agent, which tracks what you are doing and can make multi-step edits, run commands, and preview web apps. It offers its own SWE models alongside premium third-party models.

Strengths

• Agentic Cascade workflow that feels collaborative.
• Built-in previews and deploys for web projects.
• Lower entry price than some competitors.
• Enterprise options include SSO, RBAC, and hybrid deployment.

Weaknesses

• Smaller ecosystem and community than Copilot or Cursor.
• Credit-based usage takes some tracking.

Best for: Developers who want an agentic editor at a lower monthly cost.

Pricing: Free plan available; Pro from about $15/month, with Teams and Enterprise tiers (check current pricing).

5. JetBrains AI

JetBrains AI brings AI Assistant and the Junie coding agent directly into IntelliJ IDEA, PyCharm, WebStorm, and other JetBrains IDEs. Because it is built in, it can use the IDE's deep understanding of your project structure, refactoring tools, and inspections.

Strengths

• Native experience for JetBrains users, no extra editor needed.
• Junie can plan and carry out multi-step tasks inside the IDE.
• Supports multiple cloud models, with options for local models.
• Enterprise options for organizations with strict data policies.

Weaknesses

• Only useful if you work in JetBrains IDEs.
• Quota-based usage on lower tiers can run out quickly with agent work.

Best for: Java, Kotlin, Python, and other developers committed to JetBrains tools.

Pricing: Free tier available; paid AI plans add more usage (check current pricing).

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How to choose

Fit your IDE first

The best tool is the one you will actually use every day. If your team lives in JetBrains, start with JetBrains AI or Copilot's JetBrains plugin. If you are happy in VS Code, Cursor or Windsurf will feel natural. If you switch editors often, Claude Code's terminal-based approach works anywhere.

Check privacy and data handling

Read how each tool handles your code. Look for privacy modes, zero-data-retention options, and whether your code may be used for training. Some vendors offer hybrid or self-hosted deployment for enterprises; if code cannot leave your network, filter on that first.

Match team policy

Larger organizations should look for SSO, admin controls, usage analytics, audit logs, and IP indemnity. Agree on which repositories AI tools can access and who approves agent-generated pull requests.

Try before you commit

Most tools have a free plan or trial. Run the same real task, like fixing a bug in your own codebase, through two or three tools and compare the results. For more side-by-side options, explore our AI coding tools category.

Good-practice tips

1. Review every change. Treat AI output like a pull request from a new teammate: read it, question it, and understand it before merging.
2. Lean on tests. Ask the AI to write or update tests, and run your full test suite before accepting changes.
3. Watch for security issues. Check for hard-coded secrets, unsafe input handling, and outdated or made-up dependencies.
4. Keep tasks small and specific. Clear, scoped prompts produce better results than vague requests.
5. Give context. Point the tool at relevant files, docs, and coding conventions so its output matches your codebase.
6. Protect secrets. Keep credentials out of prompts and configure tools to ignore sensitive files.

AI can write code faster than you can read it. The developer's job is to make sure it is the right code.

Final thoughts

There is no single winner for every developer. GitHub Copilot is the safe all-rounder for GitHub-centric teams, Cursor offers the most polished AI-first editor, Claude Code shines on larger agentic tasks, Windsurf delivers agentic editing at a lower price, and JetBrains AI is the natural choice inside JetBrains IDEs. Start with the one that fits your editor and policies, then expand from there.

Want to compare more options? Browse the full list of AI coding tools on DNX AI.