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10 Best AI Coding Assistant Tools in 2024

An AI coding assistant can help you write code more accurately and efficiently. They offer real-time code suggestions, corrections, bug detection, and more. Check out the top 10 AI coding tools here.

Home / Blogs / 10 Best AI Coding Assistant Tools in 2024
Raghav Tayal

Head Of Operations - Digital Web Solutions

April 3, 2024

Artificial intelligence (AI) is no longer just a part of science fiction. In the last 10-15 years, there has been a significant development in the field of AI, and for some of us, it has become an integral part of our workflow. If you are a professional programmer or software developer, you must have heard how AI coding assistants can help you write more accurate and error-free code. Let’s explore some crucial aspects of these AI tools that are taking the software development industry by storm.

What is an AI Coding Assistant?

  • Support in code reviews
  • Assist in writing and debugging code
  • Offer real-time code suggestions, auto-completions, corrections, and optimizations
  • Detect security vulnerabilities and bugs to improve the quality of code

These AI tools act as virtual companions, offering intelligent and automated assistance to optimize the software development process and boost efficiency.

AI coding assistant tools serve a broad range of users. While novice programmers can use them for guidance and learning opportunities, seasoned developers can improve their productivity by ensuring their source code complies with the best practices and latest guidelines. The best thing about these tools is that they can adapt to different coding styles and project needs.

Challenges for programmers

Software developers and programming professionals face numerous challenges while writing code. Some of those challenges are mentioned below:

  • Bugs and Errors

    Identifying and fixing bugs and errors is a time-consuming process that can drain you mentally. You need to be careful while analyzing the code behavior, tracking variables, and understanding the execution flow.

  • Complexity of Syntax and Language

    While dealing with different programming languages, you may come across complex syntax rules and a steep learning curve. It often seems challenging to understand and apply the correct syntax, especially when you are a beginner or working on the language for the first time.

  • Compatibility and Integration

    You may also face compatibility challenges while integrating different components, third-party APIs, and libraries. You need to make sure that the pieces work together smoothly and properly handle data interchangeably.

  • Code Efficiency and Performance

    It can be difficult to always write perfect code that is efficient, optimized, and performs significantly well. As a developer, you need to consider memory management, algorithmic complexity, and resource utilization to make sure your code runs smoothly, especially when the resources are limited.

  • Collaboration and Version Control

    When working in teams, managing code changes, coordinating efforts, and resolving conflicts may seem a lot more challenging for individual programmers. In order to maintain a consistent and productive workflow, you need to ensure proper version control and effective collaboration.

  • Scaling and Maintainability

    It may become more challenging to manage and scale the code as the project grows. You need to make sure the code remains maintainable, scalable, and modular. Careful design decisions and adherence to best practices can help you achieve that.

  • Security and Vulnerability Mitigation

    In order to build secure software, you need to consider the potential vulnerabilities and implement appropriate security measures carefully. It may often seem challenging to address security concerns, ensure data privacy, and protect user data against cyber threats.

  • Continuously Adapting to Technological Advancements

    With the regular introduction of new languages, frameworks, and tools, the field of technology continues to evolve. It often becomes a challenge for programmers to keep learning and adapting to these new technologies throughout their careers.

  • Documentation and Code Readability

    For seamless collaboration and ease of future maintenance, it is important to write clear, concise, and well-documented code. It may seem challenging to ensure code readability and comprehensibility when your codebases become large and intricate.

  • Deadline Constraints

    Programmers often need to work under tight deadlines, which adds more pressure to the coding process. Even though it is challenging, you need to maintain speed and efficiency in such situations to deliver code within the specified timeframe.

    The good news is that you can face these challenges with more confidence when you have an efficient AI coding assistant by your side.

Advantages of using AI Coding Assistant

Here are several ways an AI code assistant can improve your coding efficiency and experience:

  • Simplifies Syntax and Language

    These coding tools help programmers navigate the complexity of different programming languages by offering real-time suggestions and rectifications for syntax errors. These AI assistants help identify and correct common mistakes such as missing semicolons, brackets, or mismatched parentheses.

  • Helping with Error Detection and Debugging

    AI coding assistants are also extremely useful in detecting and resolving errors in code. They can analyze the code in real-time, which allows them to easily identify potential bugs or errors and offer the right suggestions to fix them. They can also offer insights into the reasons for errors, suggest potential solutions, and provide links to relevant documentation. You can use it to debug while flagging and resolving issues more efficiently.

  • Autocompletion and Smart Code Suggestions

    These AI tools are great at autocompleting code snippets, helping you save time and effort. They also analyze the context of the written code and offer smart suggestions for completing code statements, method names, variables, or function parameters. The suggestions provided by the AI assistants are contextually relevant and help accelerate the coding process.

  • Optimizing Code for Efficiency and Performance

    With the help of AI coding assistants, you can optimize your code for efficiency and performance. They can help analyze code snippets and identify areas that need improvement, such as redundant loops, inefficient algorithms, or suboptimal data structures. You can write more efficient code, perform better, and consume fewer resources when you have the right suggestions for code refactorings or alternative implementations.

  • Compatibility and Integration Assistance

    These AI tools can make your job easier by suggesting compatible APIs or libraries on the project’s requirements. They also help guide the seamless integration of specific functionalities or code snippets. They can reduce potential compatibility issues and save you time.

  • Collaboration and Version Control Management

    These AI coding assistant tools can provide conflict resolution suggestions to reduce conflicts during code merging. They also help with highlighting modifications made by different team members, tracking changes, and ensuring hassle-free collaboration within a project.

  • Improving Documentation and Code Readability

    You can use the AI coding assistant tools to enhance code documentation and readability. They can provide documentation templates, prompt you to add comments, or suggest more precise variable and function names. They can help facilitate maintainability, code comprehension, and ease of future development.

    Apart from these common features, you can enjoy some exclusive benefits that come with specific AI coding assistants.

10 best AI Coding Assistants

1. Copilot

Copilot aims to transform the coding experience with its capabilities and advanced features. Developed by GitHub in collaboration with OpenAI, Copilot was the first of its kind to use the advanced GPT-3.5 model. It showcased amazing speed and accuracy, which surpasses a number of other tools you can find in the market.

Some of the major highlights of this tool include:

  • A large community because of its massive popularity
  • Easy navigation through several code snippets and intelligent code completion
  • Integration with various IDEs (IntelliJ products, Visual Studio Code, Neovim)
  • Support for various major programming languages
  • Has the ability to block code suggestions matching public code snippets. This feature helps avoid accidental open-source license violations.

This AI coding assistant tool is available in three different pricing plans for businesses, enterprises, and individuals. The enterprise plan costs $39 monthly per user, while the business plan and individual plans cost $19 and $10 per month per user, respectively.

2. ChatGPT (GPT-3.5/4)

ChatGPT is perhaps the most popular AI tool available to the public right now. Apart from its common generative feathers, it is also a great AI coding assistant. It can help generate code snippets, brainstorm project ideas, and solve issues. 

You can start using ChatGPT by providing code context or a detailed description of your project. This context or description allows ChatGPT to generate more accurate and relevant responses. The primary goal of this AI coding assistant is to help users with their unique tasks and inquiries.  

It is fast and reliable. GPT 3.5 is available to everyone free of charge.

3. Gemini 1.5

Gemini is a powerful AI coding assistant tool from Google. Its AI-powered assistance allows you to build applications more quickly and efficiently in popular code editors like JetBrains and VSCode. The massive context window of Gemini 1.5 pro far exceeds competitors like Copolit from GitHub.

Gemini can generate and translate code into a simple one-shot query output. It supports over 20 programming languages, including C++, Java, Python, SQL, and PHP. Moreover, it is capable of large-scale code translation. Its context window also allows businesses to convert a long code or even the complete codebases into another programming language.

4. Amazon CodeWhisperer

This is a machine learning-driven tool for code generation. You can use it for real-time coding recommendations to match your individual style and current project. It offers relevant code suggestions, ranging from simple code snippets to complete functions. It can also generate comments and code documentation.

Some of the key features of this AI coding assistant are:

  • Seamless integration with Amazon’s ecosystem
  • Security scans
  • Accurate code suggestions in real-time

While the individual tier of this tool is available for free, the professional tier costs $19 monthly per user.

5. Tabnine

This is one of the leading AI coding assistant tools that prioritizes privacy, compliance, and security while simplifying and accelerating software development. This tool also covers copyleft issues. Its SOC-2 compliance further reinforces adherence to best practices.

Tabnine has the capability to reflect the collective knowledge of an organization. It personalizes its assistance based on your specific codebase, aligning with your team’s coding style.

It operates in an isolated mode within your chosen environment – whether it is a secured SaaS setup, on your VPC, or on-premises. This ensures that your sensitive data is always under control. It also enables centralized policy enforcement.
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6. Blackbox AI

You can use Blackbox AI to write better code. It uses artificial intelligence to offer real-time suggestions for documentation, code completion, and debugging. Moreover, it can easily integrate with a number of developer tools, allowing you to use it within your existing workflow without any hassle.

Blackbox AI offers a number of amazing features, including AI chat, autocomplete, AI commit, AI code generation and suggestion, file difference comparison, and more.

7. Replit AI

It is a cloud-based IDE that helps improve the software development experience. The major highlight of Replit AI is its intelligent code completion feature. It can also generate code like any other AI coding assistant on this list. While it offers a strong performance with Python and JavaScript, it can work with a variety of programming languages. It even includes SQL, HTML, and CSS.

Some of the key highlights of this tool are:

  • Availability of numerous functionalities free of charge
  • AI chat within the IDE
  • Proactive code debugging, where AI fixes the issues for you without having to analyze the error messages manually

The starter plan is available for it. However, if you want unlimited access to the AI chat and centralized billing and user management, you need to choose the paid plans.

8. SQLAI

This tool generates queries for SQL and NoSQL databases. You can get immediate results from this platform and also receive a personal library to store and share custom SQL and NoSQL snippets. You can enjoy one-click integration with popular databases, such as Oracle, Postgres, MySQL, SQL Server, and MongoDB. Moreover, it supports manual connections, such as CSV imports, for broader compatibility.

You can run AI-generated queries directly on your connected data sources by simplifying the process of getting real-time data insights. You get the results in tables or through AI-crafted charts. It is designed to make the acquisition and display of data intelligence straightforward.

9. Codeium

If you are looking for a free AI code assistant, Codeium is one of the best options out there. It has the ability to improve your development experience with context-aware code generation, intelligent autocomplete, AI chatbot, and various other developer features. It is completely secure and as fast as GitHub Copilot.

It also has a paid option that lets you access the advanced GPT-4 model and other administrator tools. If you are just starting out and need fast and accurate code generation, this AI code assistant is one of the best choices.

10. Tabby

You can host this AI coding assistant on your local machine using Docket. It offers an open-source and on-premises option to GitHub Copilot. This tool is known for being self-contained and does not require any data management system or cloud service.

The OpenAPI interface allows you to integrate it easily with the existing infrastructure, such as cloud IDE. It even supports consumer-grade GPUs. With Tabby, you get a large language model server service that you can self-host. It also offers several extensions that you can use on platforms like IntelliJ, Vim/NVim, and VSCode.

Conclusion

With the advancements in the field of technology, AI coding assistant tools are expected to play an increasingly important role in the software development industry. Since these tools have the ability to constantly learn and improve, they can potentially revolutionize the coding experience for the better. By choosing the right AI coding assistant, you, too, can overcome common coding challenges, enhance your productivity, and create superior-quality software solutions with ease.

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