The 9 best AI coding tools for developers of all levels

Whether you are an experienced developer looking for an efficient assistant or a newcomer hoping to accelerate the learning process, the right AI coding tool can make a significant difference.

And, just like with everything else AI related, finding the best AI tools for coding can be challenging. That’s why we tested out the top tools on the market so you can have a detailed analysis of the most promising AI coding tools available, ranking them based on their capabilities and identifying the best fit for different development needs.

1. GitHub Copilot

GitHub Copilot is one of the most well-known AI coding tools, and for good reason. Powered by OpenAI’s Codex, it provides real-time suggestions for code completions, entire functions, and even debugging assistance. It integrates seamlessly into major IDEs and speeds up development for a wide range of programming languages

Strengths

• Advanced code suggestions – Autocompletes lines of code, entire functions, and even complex algorithms.
• Understands natural language – Converts comments into working code.
• IDE integration – Works with VS Code, JetBrains IDEs, and Neovim.
• Security insights – Detects potential vulnerabilities in your code.

Where it could improve

• Occasionally generates incorrect code – Requires manual review, especially for complex logic.
• Limited offline functionality – Relies on cloud-based AI processing.

GitHub Copilot is the best AI tool for coding overall. It’s reliable, easy to integrate into existing workflows, and significantly boosts productivity.

2. Tabnine

Tabnine is an AI coding assistant designed for on-device processing, meaning your code never leaves your machine. It’s a privacy-focused alternative to cloud-based AI tools, offering intelligent code completions across multiple programming languages.

Strengths

• Runs locally – Keeps code private by processing AI completions on your device.
• Multi-language support – Works with Python, Java, JavaScript, PHP, Go, Rust, and more.
• Context-aware predictions – Understands code structure for more accurate completions.
• Team collaboration – Offers AI-assisted suggestions for team-based projects.

Where it could improve

• Not as advanced as Copilot – Lacks full-function generation capabilities.
• Takes effort to configure – Setting up offline mode can be tricky.

Tabnine is a great AI coding tool for developers prioritizing privacy. However, its AI-powered suggestions are not as advanced as GitHub Copilot’s.

3. Cursor

Cursor is a popular AI coding tool built as a fork of Visual Studio Code, integrating artificial intelligence directly into the development environment. It maintains the familiarity of VS Code while introducing advanced AI-powered features to improve productivity.

Strengths

• Automated coding with agent mode – Cursor can autonomously handle various tasks, reducing the need for manual intervention.
• Familiar interface – Since Cursor is built on VS Code, developers can transition seamlessly without having to learn a new workflow.
• Customizable AI models – Users can integrate different AI models instead of relying solely on default options.
• Structured file generation – It automatically creates essential project files, such as requirements.txt and README.md, reducing setup time.

Where it could improve

• Moderate speed – The AI response time is acceptable but slower than some competitors.
• Query limitations – Free-tier users face restrictions on the number of AI-assisted queries unless they upgrade to a paid plan.

Cursor is an excellent choice for developers who are accustomed to VS Code and want an AI coding tool that integrates directly into their existing workflow. It offers solid automation and AI-powered code generation, making it one of the best AI tools for coding for professionals.

4. Sourcegraph Cody

Sourcegraph Cody is an AI-powered coding tool designed for developers managing large-scale projects. Instead of just generating code, Cody helps search, navigate, and analyze large codebases, making it ideal for debugging and understanding existing projects.

Strengths

• Advanced code search – Finds relevant code snippets across repositories, branches, and hosts.
• Understands context – Uses AI to analyze dependencies and relationships within the codebase.
• Natural language search – Allows developers to find code using plain English queries.
• Works with GitHub and GitLab – Seamlessly integrates into existing development workflows.

Where it could improve

• Not a traditional coding assistant – Focuses on searching code rather than writing it.
• Most useful for large teams – Solo developers may not benefit as much from its features.

Sourcegraph Cody is a powerful AI coding tool for teams working on large repositories. However, if you’re looking for an AI-powered assistant to generate code, Copilot or CodeWhisperer are better options.

5. Windsurf

Windsurf is another AI-enhanced development environment that has gained attention for its agentic features. It offers many of the same AI-driven capabilities as Cursor but with a focus on handling multiple files simultaneously.

Strengths

• Efficient multi-file generation – Windsurf excels at creating multiple files in a project at once, reducing the need for manual setup.
• Claude 3.5 Sonnet AI integration – The AI model used in Windsurf is capable of reasoning through complex development tasks.
• VS Code familiarity – Like Cursor, Windsurf is built on a VS Code fork, making it easy for existing VS Code users to adopt.

Where it could improve

• Slower execution times – Compared to Cursor, Windsurf takes longer to generate code and complete project setup.
• Frequent unexpected errors – Some test cases resulted in unexpected bugs that required additional debugging.
• Higher cost – Windsurf’s pricing is higher than Cursor’s despite its slower performance.

Windsurf has strong multi-file generation capabilities, but its slower execution speed and higher cost make it less appealing than Cursor. While it is a capable AI coding tool, it is not the most efficient option available.

6. Aide

AIDE operates differently from traditional AI-powered IDEs. Instead of running locally, it functions as a cloud-based AI coding tool that integrates with GitHub. Developers can create an issue in their repository, and AIDE will generate a pull request with AI-generated code.

Strengths

• Completely cloud-based – No need to install software; it operates directly through GitHub.
• Free to use (for now) – AIDE does not currently charge users, making it an attractive budget-friendly option.
• Autonomous code execution – The AI handles the entire coding process without requiring manual input.

Where it could improve

• No real-time visibility – Developers cannot see what the AI is doing until the pull request is created.
• Lack of control – There is minimal ability to guide or adjust the AI’s output before it is committed to the repository.
• No version control checkpoints – Rolling back unintended changes can be difficult.

AIDE is an interesting concept, but its lack of real-time interaction and control limits its usability. While it may be useful for automating routine tasks, developers who require AI coding tools with more flexibility should look elsewhere.

7. Bolt

Bolt is an AI coding tool designed for speed and efficiency. Unlike Cursor and Windsurf, which run locally, Bolt operates entirely in the cloud. Despite initial skepticism about its performance, Bolt outperformed expectations by delivering rapid code generation and a highly responsive interface.

Strengths

• Fastest AI execution – Bolt generated a functional trading bot in seconds, outperforming all other tools in speed.
• Real-time project updates – Developers can see file structures and changes as they happen.
• One-click deployment – Bolt integrates with Supabase for quick and easy app deployment.
• Intuitive UI – The interface is user-friendly and designed for efficiency.

Where it could improve

• Cloud-only – Developers who prefer working locally may find this restrictive.
• Limited debugging tools – Lacks some of the advanced debugging capabilities available in Cursor.

Bolt is the fastest AI coding tool tested and is ideal for rapid prototyping and MVP development. For developers who prioritize speed, Bolt is the best AI tool for coding.

8. Replit

Replit is a well-known AI coding tool that supports cloud-based development. It offers mobile compatibility and an AI assistant designed to help with code generation. However, its performance did not meet expectations in testing.

Strengths

• Project planning assistance – Replit generates structured development plans before coding.
• Version control checkpoints – Developers can revert to previous versions of their code.
• Mobile support – Replit offers a mobile-friendly interface, allowing users to code from their phones.

Where it could improve

• Slow performance – Code generation was significantly slower than competitors.
• Frequent errors – Multiple test cases resulted in the AI getting stuck in error loops.
• High cost relative to performance – The pricing does not justify its functionality.

Replit has potential, but its current performance is unreliable. Until improvements are made, it is not recommended as a primary AI coding tool.\

9. Amazon Codewhisperer

Amazon CodeWhisperer is Amazon’s answer to Copilot, offering AI-powered code completions optimized for cloud and AWS-related development. It provides real-time suggestions across multiple programming languages and integrates with AWS development environments.

Strengths

• Optimized for AWS – Provides tailored recommendations for cloud-based applications.
• Inline code suggestions – Helps write and refactor code in real-time.
• Multi-language support – Works with Python, Java, JavaScript, and more.
• IDE compatibility – Supports VS Code, JetBrains IDEs, AWS Cloud9, and others.

Where it could improve

• Less powerful outside AWS – Performs best in AWS-based projects but feels limited for general development.
• Expensive team plans – Individual plans are free, but team pricing is on the higher side.

Amazon CodeWhisperer is a great AI coding tool for AWS developers. However, for general-purpose coding, GitHub Copilot is the stronger choice.

Choosing the right AI coding tool

AI-powered assistants are transforming how developers approach writing code, making programming tasks faster and more efficient. Just like the right content creation tools or marketing tools, the right coding tool depends on your workflow, whether you need real-time autocompletion, AI-driven debugging, or intelligent code search within a code editor.

While no AI can replace experience and creativity, the right assistant enables developers to streamline repetitive tasks, adapt to different coding styles, and focus on solving complex problems more effectively.