Top 7 AI Coding Assistants in 2024 🔥

While powerful AI chatbots like ChatGPT or Gemini allows you to generate code snippets in multiple languages, there is no support in code context and multiple calls and functionalities, which can only be supported through a dedicated inside-IDE developer tool.

AI coding assistants are intelligent tools that aid developers inside IDE by suggesting code, detecting bugs, or writing unit tests. They use AI to enhance coding efficiency and accuracy, offering real-time assistance based on natural language prompts or existing code.

1. GitHub Copilot • Developed by GitHub in collaboration with OpenAI. It uses the OpenAI Codex model to suggest relevant code snippets, complete functions, and even full algorithms in real-time as you type.

2. CodiumAI • It interacts with developers, analyzing code and suggesting non-trivial tests, identifying edge cases, and ensuring code functions as intended. With over 650,000 installs, CodiumAI is celebrated for making unit testing intuitive and boosting productivity.

3. Tabnine • Designed to autogenerate high-quality code, convert plain text into code, and eliminate repetitive tasks. It stands out for using private and personalized AI models, ensuring complete code privacy with zero data retention.

4. Replit AI • Renowned for its ability to streamline the coding process by automating repetitive tasks, which significantly enhances productivity. Moreover, it aids in debugging with precision, understanding code syntax, data types, and more, to help resolve complex errors.

5. Cody • Developed by Sourcegraph. Cody’s AI-powered chat can answer questions about code structure, functionality, and troubleshooting, making it easier to work on new or legacy projects. It also allows for custom and pre-built commands to generate, test, and fix code, which can enhance productivity.

6. Amazon Q Developer • It generates real-time code suggestions ranging from snippets to full functions based on your comments and existing code. It also supports CLI completions and natural language–to-bash translation in the command line.

7. CodeGPT • It’s similar to Github Copilot, but with added flexibility: you control the prompts, choose the LLM, and empower your coding with as many AI Assistants as you need.

Which AI coding assistant should I use?

Some of the most common use cases of using an AI coding assistant are:

• Writing new code
• Accelerating unit testing
• Extending and refactoring existing code
• Understanding existing or legacy code
• Generating documentation
• Generating boilerplate code
• Onboarding to a project

Choosing the right AI coding assistant for your project involves considering several factors to ensure that the tool aligns with your specific needs and preferences. Here are some key points to consider:

• Accuracy: Look for an AI coding assistant known for providing precise code suggestions and completions based on the context of your work.
• Supported Languages: Ensure the AI assistant supports the programming languages you use. It should cater to a wide range of developers and not limit you to a few languages.
• Supported IDEs: The tool should integrate seamlessly with your preferred code editors.
• Features: Determine which features are most important for your project. Do you need robust code suggestions, real-time bug detection, or assistance with refactoring? Make sure the AI assistant excels in these areas.
• Privacy and Security: If your project involves sensitive data, consider an AI coding assistant that prioritizes data privacy and has robust security measures in place.
• Pricing: Evaluate the cost of the AI coding assistant, especially if you’re on a budget. There are both free and paid options available, so consider what fits your financial plan.

AI-generated code adheres to coding standards, best practices, and design patterns, resulting in cleaner, more maintainable codebases. By automating routine coding tasks, you can work more efficiently and focus on higher-level problem-solving.