Best AI Tools for Coding in 2024
With all the buzz about AI taking over our jobs, why not flip the script and employ AI to help you write efficient code and boost your productivity instead? In 2024, the best AI tools for coding are designed to be your new sidekick, helping you code smarter, faster, and with less stress. Let's explore how you can make AI work for you before the inevitable machine world domination.
What is an AI coding assistant?
An AI (artificial intelligence) coding assistant is a tool designed to enhance your coding process by utilizing machine learning models to generate code snippets, provide code completion, and suggest improvements for code quality. These assistants can help you write code faster and more efficiently across multiple programming languages, offering context-aware suggestions and explanations. AI coding tools come in various forms, notably conversational chatbots or IDE (Integrated development environment) applications.
Chatbots, such as the recently popular ChatGPT, are the most user-friendly methods to help with code. They understand natural language and know how to process it; therefore, you can ask for advice or suggestions in human sentences. It's like asking for help from a very smart senior developer friend. Only this one works within seconds and doesn't need to set up an hour-long meeting beforehand.
IDE integrations are slightly different from chatbots in how they function. They offer real-time suggestions as you write your code, predict the next lines of script, or help you quickly set up snippets. Tools like these are very efficient, as they understand the context of your project from the very beginning, ensuring that the advice they provide is accurate and relevant. It's the other developer friend, but the one that stands behind your back and gives suggestions while you write code.
How can AI tools help with coding?
AI tools have various features and ways to help you write code. Here are some of the most popular ones:
- Code generation. Not sure where to start or how to write a complex function? No worries, AI tools can write the code for you if you provide context and a detailed explanation of what the code should achieve.
- Code completion. Integrated AI tools will auto-complete code as you write, saving time and effort. It can also help avoid errors by ensuring the syntax is correct. No more long hours of headaches trying to find out what's wrong with your code while it was just a missing semicolon.
- Error detection. Providing a snippet of code to an AI tool can help identify errors within it. It's a very effective way of detecting issues, as the tool can read the entire code and understand the context of what's happening. It can also assist in explaining error messages and fixing your code according to them.
- Code explanation. There's nothing more fun than finding old legacy code that a past developer wrote and left no comments or documentation explaining what's even going on. Thankfully, AI can read the code, provide a proper description, or write comments for each line or function.
- Context-aware suggestions. One of AI tools' most prominent features over other methods is understanding context. A piece of code can be written in several different ways, so a suggestion you found online might not fit your case and require manual adjustment. Context-aware suggestions can see your entire script or project, allowing it to provide accurate feedback.
Top AI coding tools in 2024
Without further ado, let's explore some of the most popular tools for coding in 2024. Remember that this list doesn't rank them, and the best tool will always be the one that best fits your needs.
1. ChatGPT (GPT-4)
ChatGPT (GPT-4) is a conversational AI model developed by OpenAI that generates human-like text, making it a versatile tool for coding assistance, problem-solving, and learning. Using it is super easy – simply write down your question as you would send a message to a person, and you'll get a detailed response. It's one of the most popular and straightforward tools that can be used for any coding-related tasks.
Key features
- Generates, explains, and refactors code. ChatGPT can write code from scratch based on a problem description or refactor existing code to improve efficiency and readability.
- Handles multiple languages. Supports nearly all popular programming languages, allowing it to be useful no matter your setup.
- Helps with algorithmic problem-solving. Provides step-by-step solutions for algorithmic problems and can suggest improvements or alternatives to complex logic.
Pros
- Complex query comprehension. ChatGPT is capable of breaking down difficult problems into simple steps and explanations and providing solutions.
- Error resolution and code optimization. Analyzes error messages to identify potential issues and suggests ways to fix or improve code performance.
- Solution brainstorming. Helps generate ideas and pseudo code to start with so that even big tasks can be broken down into smaller pieces to build upon.
Cons
- Incorrect code generation. ChatGPT might produce code that doesn’t work as expected or isn’t optimized, requiring human intervention and manual fixing.
- Lacks real-time integration with IDEs. Unlike tools like GitHub Copilot, it doesn’t integrate directly into coding environments, so you must frequently switch and copy-paste, reducing efficiency and speed.
- Large project incomprehension. Without the ability to directly interact with projects, it struggles with larger codebases or dependencies unless all context is provided manually.
Use cases
- Writing and understanding code snippets. ChatGPT is a great tool for quickly generating code based on queries, which helps get an idea on paper faster. It may also help understand code by asking it to provide explanations or add comments for difficult-to-grasp areas. For example, read here to learn how to use it for web scraping.
- Debugging and explaining errors. Huge error messages in your terminal tool can be scary, but with the help of ChatGPT, you can translate them into easy-to-read sentences. These provide an in-depth explanation of the problem and suggest potential solutions and fixes.
- Learning new concepts. You can use the tool as a great learning resource, asking it to explain how things work, break down difficult concepts, and provide high-quality examples to study.
Pricing
GPT-4 costs $20 per month and offers more advanced and accurate coding support, faster response times, and improved handling of complex prompts. The free version (GPT-4o mini) provides basic coding assistance with limited capabilities and slower response times.
2. GitHub Copilot
GitHub Copilot is an AI coding assistant developed by GitHub that integrates directly into popular IDEs, offering real-time suggestions and code completion based on the context and comments developers provide. It's a rising star in the development community as it drastically increases your performance by seamlessly integrating into any IDE.
Key features
- Autocompletes code based on context. Copilot provides smart code suggestions by considering the context of your writing and reduces the manual effort needed to finish long blocks of code.
- Works with popular IDEs. Perfectly integrates with IDEs like Visual Studio Code, JetBrains, and even Neovim, allowing developers to stay within their comfortable coding environments.
- Generates boilerplate code. Based on comments or function names, it can generate repetitive code sections like loops, functions, or database queries, reducing the manual labor needed.
Pros
- Faster development. Automatically completing repetitive or predictable code significantly reduces time spent writing boilerplate and routine code.
- Real-time suggestions. Because it works within the IDE, developers receive instant feedback, helping them stay focused on the task without leaving their coding environment.
- Beginner & expert friendly. Novice developers can benefit from Copilot’s code completion and suggestions, while experienced developers can use it to reduce routine tasks and focus on more important pieces of code.
Cons
- Insecure or incorrect code suggestions. Copilot's suggestions, while helpful, sometimes lack a deep understanding of secure or optimized coding practices, meaning human review is still necessary.
- Complex design struggles. The tool is primarily used for line-by-line or function-by-function completion, but it doesn’t assist with high-level software design or architectural decisions.
- Licensing concerns. As Copilot was trained on massive amounts of public data, it doesn't ensure that the generated code isn't violating and software license or copyright.
Use cases
- Writing repetitive code quickly. Ideal for generating repetitive code sections, such as looping structures or API calls.
- Autocompleting complex functions or methods. Helps finish writing larger functions or classes, especially when the logic is straightforward or predictable.
- Learning new languages or frameworks. Developers working with unfamiliar programming languages or frameworks can benefit from code suggestions to grasp concepts quickly.
Pricing
Github Copilot costs just $10/month for individuals and $19/month for teams and businesses. There's no free tier, but GitHub offers Copilot for free to students and open-source contributors.
3. Cursor
Cursor is an AI-powered code editor that enhances the coding experience by offering intelligent code suggestions, autocompletion, and debugging features. Unlike Copilot, it's a separate software on its own, so you get powerful AI suggestions and a pretty neat code editor all in one package.
Key features
- Suggests and generates code. Cursor provides code completions and snippets based on the project context, making coding faster and more efficient.
- Helps write comments and documentation. Cursor can generate meaningful comments and documentation, saving you time doing it yourself or missing sections for code that may seem intuitive but probably aren't.
- Refactors and optimizes code. Offers suggestions to refactor code, improving structure, efficiency, or readability without altering the functionality.
Pros
- Documentation generation. Automatically generates comments or even full documentation, making it easier to maintain large codebases.
- Streamlined debugging. Quickly finds and offers suggestions for fixing errors in real time before even launching the code.
- Contextual learning. Cursor often provides inline documentation, usage examples, and explanations based on the developer's coding context.
Cons
- Lack of language support. While effective in several languages such as Python, JavaScript, and TypeScript, Cursor may not work with every programming language or framework, limiting its use and effectiveness for developers working only with specific technologies.
- Manual intervention requirement. Cursor’s suggestions may require human intervention and manual tweaking for more complex logic or highly nuanced code to not cause errors or slow down performance.
- No integration. Cursor is a standalone software application; therefore, if you want to use it, you'll be limited to the IDE it provides. Many developers might find that a hassle, getting comfortable with a new tool and missing other useful extensions.
Use cases
- Writing and refining code. Boosts productivity by offering AI-powered suggestions to help developers write cleaner, more efficient code faster.
- Creating documentation. Every developer dreads spending hours writing documentation, explaining every little detail of their code. Cursor solves this headache, as it can quickly generate not only helpful comments but entire pages of documentation that clearly explains the written code.
- Improving code. Writing code isn't enough; it needs to be easy to read, optimized, and foolproof against any potential issues. Together with AI tools such as this one, you can be sure your code is of the highest standard.
Pricing
You can use Cursor for free, albeit with limited access and basic AI suggestions. To fully use it, you can buy the Pro version for $20 monthly, with all the features one developer might need. A Business plan for $40 a month is also available, offering an org-wide enforced privacy mode and an admin dashboard to manage the project safely and efficiently.
4. Claude 3 Opus
Claude 3 is a conversational AI developed by Anthropic, designed to be a safe and ethical assistant. While it’s primarily built for natural language interaction and assistance in various tasks such as graph creation and document drafting, it can assist developers by explaining and generating code.
Key features
- Handles large context. Capable of analyzing and generating code even when dealing with larger codebases or long blocks of text, making it suitable for more complex coding tasks.
- Generates and explains code. Like most tools on this list, Claude 3 provides clear, easy-to-understand explanations of code snippets or technical concepts.
- Follows ethical and safety-focused rules. Built to provide responsible and secure code suggestions, focusing on generating content that’s ethical and minimizes the risk of errors, copyright, or harmful issues.
Pros
- Safe, secure suggestions. Claude 3 is designed to prioritize safe coding practices and ethical AI usage, minimizing the chances of suggesting risky or insecure code.
- Complex code explanation. Its natural language capabilities allow it to explain complex technical concepts clearly and understandably.
- Large context handling. It's one of the best tools for working with big projects with lots of code, libraries, and files, suggesting code that understands the full context, not just the file currently being written.
Cons
- No real-time IDE integration. Claude 3 doesn't offer the ability to integrate into any IDEs, making it a bit inefficient to copy over code between the platform and the coding application.
- Reduced flexibility. Its emphasis on ethical coding might prevent it from generating more experimental or unconventional code, making it less flexible in some scenarios.
- Incomplete or inaccurate responses. While Claude 3 is trained on a large dataset, it may sometimes provide incomplete or inaccurate information, particularly in specialized fields.
Use cases
- Explaining code for educational use. Claude 3 is excellent for explaining code in a simplified, educational manner, helping developers, especially beginners, understand complex programming logic or concepts.
- Debugging large codebases. Its ability to handle large contexts allows it to assist in debugging or reviewing entire projects.
- Refactoring algorithms. Developers can use Claude 3 to review or discuss algorithms, with the AI offering safe, ethical refactoring suggestions for better efficiency or readability.
Pricing
Claude 3 offers a free version of the software, which limits you to simple interactions, such as asking about images or text documents. A Pro version costs $20 monthly and includes more advanced features, including the ability to work with large coding projects. The Team version is a great choice for a group of developers for just $25 monthly per member, offering collaborative tools and higher usage limits. Finally, if you're serious about using Claude 3 professionally, there's the Enterprise version for a custom price based on your chosen features.
5. Tabnine
Tabnine is an AI code assistant that integrates directly into popular IDEs. It provides intelligent, context-aware code suggestions and is known for its privacy focus, allowing developers to train models on private repositories for more personalized assistance.
Key features
- Supports custom models. Developers or teams can train Tabnine's AI on specific repositories, creating custom models that are tailored to the coding style and structure of their projects.
- Focuses on privacy. Tabnine prioritizes security and privacy, allowing to train its models locally so sensitive code doesn’t need to be shared with external servers.
- Assists with code completion. Similar to GitHub Copilot, Tabnine also offers real-time code suggestions and auto-completes chunks of code based on the context.
Pros
- Multiple IDE support. It integrates easily with many popular IDEs so developers can continue using their favorite tools without dedicating time to learning something new.
- Very accurate predictions. The AI models that you can train on your specific project help developers complete code faster and avoid issues of the code not being accurate in the current context.
- Strong privacy controls. Tabnine's focus on privacy makes it a great option for companies handling sensitive or proprietary code.
Cons
- Feature limitation. Unlike Copilot, which offers broader support for code generation and problem-solving, Tabnine focuses primarily on code completion and lacks a more interactive AI interface for higher-level discussions.
- Inaccurate suggestions. As with any AI-based completion tool, the generated code snippets may not always be perfect or contextually correct, requiring developer interference and adjustments.
- Resource intensive. Since it uses local AI models, these can be very straining on your machine and use up a lot of resources, leading to poor performance, especially on lower-end computers.
Use cases
- Predicting code. Tabnine excels at providing quick and accurate code completion suggestions, enabling you to write code faster and smarter and avoid problems.
- Working with large projects. Teams can use custom AI models trained on their specific codebases to ensure consistency in code completion according to their requirements.
- Handling multiple programming environments. Whether you’re switching between languages or working in different IDEs, Tabnine offers consistent support no matter what you choose.
Pricing
A fully functional free version of Tabnine is available and has basic code-completion features, as it doesn't offer custom AI models. You can try the powerful AI assistant by getting the Pro version for 90 days for free; after that, it's just $12 a month. Finally, there's the Enterprise plan for $39 monthly per user, which offers a private and secure platform that's fully optimized for large businesses.
Final thoughts
AI coding tools are changing how developers write code and revolutionizing the industry. They offer powerful code generation, completion tools, and context-aware suggestions across multiple programming languages. These powerful assistants not only speed up development and improve code quality but also have built-in security and ethical considerations to ensure safer, smarter coding practices. Don't stay behind the trends and hop on the latest technologies to build a new future together with your AI right-hand man.
About the author
Zilvinas Tamulis
Technical Copywriter
Zilvinas is an experienced technical copywriter specializing in web development and network technologies. With extensive proxy and web scraping knowledge, he’s eager to share valuable insights and practical tips for confidently navigating the digital world.
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