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How to Choose the Best AI Coding Assistant & 28 Impressive Tools to Try

Are you tired of being stuck on complex coding tasks, wishing you had AI copilots to assist you through the process? Well, look no further! If you are on MacOS and aiming to effectively Use AI anywhere as an AI copilot/assistant, this article is just what you need. Here, we will delve into the best AI coding assistant tools available to simplify your coding struggles and boost your productivity significantly.


Introducing Omnipilot's AI copilot tool! This innovative solution is designed to be your perfect assistant, offering seamless support to help you Use AI anywhere on MacOS as an efficient AI copilot/assistant. With this tool at your disposal, you can revolutionize your coding experience and easily achieve your objectives.

What Is an AI Coding Assistant?

AI coding assistants can do much more than just autocomplete and static analysis. They can also help you debug your program, provide documentation hints, help you write tests, and even refactor code. Advanced AI coding assistants can save you more time by generating whole classes or functions. This means that you can write your programs without even having to leave your IDE!


Underlying Technologies of AI Coding Assistants

AI coding assistants use machine learning models to provide more accurate suggestions. This machine learning model is trained on much code to understand what you are trying to do. It can also use natural language processing to parse the comments in your code, error messages, and other text. This allows it to understand what you are trying to do and provide suggestions based on that understanding.


14 Benefits of Using an AI Coding Assistant

When it comes to incorporating AI coding assistants into your development workflow, several advantages can significantly enhance your programming endeavors. These benefits include increased productivity, improved code quality, enhanced collaboration, faster onboarding for new developers, and reduced technical debt. Let’s dive into the advantages of incorporating an AI coding assistant into the development workflow:


1. Time-to-market Reduction

By accelerating the coding process, AI coding assistants can help bring products to market faster, providing a competitive edge. This reduction in time to market can significantly impact a project's success. 


2. Cost Savings

Automation can reduce the need for extensive manual labor. You can cut costs associated with manual coding processes by leveraging AI coding assistants. This efficiency translates into cost savings in the long run.


3. Accessibility for Non-Experts

AI coding assistants can make app development more accessible to those with less experience. They can bridge the gap between novice and expert developers, ensuring that even less experienced team members can contribute effectively to a project.


4. Scalability

AI tools can easily scale with the project as they learn from the growing codebase. This scalability supports projects as they increase in size and complexity, providing a flexible solution to growing development needs.


5. Continuous Improvement

Because they’re trained with a lot of data, the suggestions and insights offered by AI code tools become more sophisticated and valuable over time. This continuous improvement ensures that your coding practices are continually optimized.


6. Stress Reduction

AI coding assistants can reduce the mental load on developers by handling many mundane aspects of coding. This stress reduction allows developers to approach coding challenges more clearly and focus on creating innovative solutions.


7. Increased Efficiency

AI tools can automate routine or repetitive coding tasks, such as boilerplate code, enabling developers to focus on more complex and creative aspects of their projects. This increased efficiency can significantly enhance productivity across the development team.


8. Enhanced Code Quality

With real-time suggestions and the ability to flag potential errors, AI-powered code assistants help maintain high coding standards and reduce the likelihood of bugs. This focus on code quality ensures that the final product meets the highest standards.


9. Learning and Growth

Developers can learn from AI-driven recommendations, which often reference best practices and newer, more efficient ways of coding. This learning opportunity ensures that developers are continually improving their skills and knowledge.


10. Faster Debugging

AI coding assistants can detect issues and offer solutions, significantly speeding up the debugging process. This rapid identification and resolution of bugs can streamline the development process and ensure that the final product is of the highest quality.


11. Code Refactoring

When it comes to improving structure and readability, AI tools can refactor code without changing the external behavior of the codebase. This refactoring capability can enhance the maintainability and readability of the code, making it easier for developers to work with.


12. Personalized Assistance

By adapting to individual coding styles and preferences, AI coding assistants provide tailored support that improves over time. This personalized assistance ensures developers receive the specific guidance they need to enhance their coding skills.


13. Integration with Development Environments

Many AI coding assistants can be integrated into popular IDEs, streamlining the software development process and workflows. This integration ensures developers can access AI coding assistance directly within their preferred development environment, enhancing their productivity.


14. Image Processing

Some AI coding assistants support images in prompts, allowing developers to get answers as quickly as possible. This image-processing capability enhances the usability of AI coding assistants, providing developers with the information they need to code effectively.


Unlocking Seamless Workflow Efficiency with Omnipilot's AI Copilot

Imagine an AI that can type anywhere on macOS, with the full context of what's on your screen. Imagine if, your email wrote itself, your terminal was fluent in Bash, your team updates became effortless. You don’t have to imagine any of this anymore. You can download Omnipilot’s MacOS AI Copilot for free and use AI anywhere on MacOS! 


Try our free AI copilot today — just head to omnipilot.ai and enter your email, and you’ll be able to download our MacOS app in seconds! Let Omnipilot make your life easier.


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How to Choose the Best AI Coding Assistant

Different tools have varying degrees of integration with popular IDEs like Visual Studio Code. This can significantly impact your workflow and how seamlessly the AI assistant integrates with your existing tools.


Support for Languages and Frameworks

Consider the languages and frameworks you use most frequently. Some tools may excel in web development languages like JavaScript and HTML, while others focus on system programming languages like C and Rust.


Open Source vs. Proprietary

Decide whether you prefer proprietary tools backed by companies, offering advanced features, or open-source tools that are freely available but require more setup and maintenance.


Security and Privacy Features

Given the sensitive nature of code, especially in enterprise environments, look for AI coding assistants that emphasize security features such as data encryption and privacy controls.


Specialized Features

Look for AI tools that offer unique features tailored to specific tasks. For example, some may automatically generate unit tests, while others excel in natural language to code translation, facilitating contributions from non-developers.


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28 Impressive AI Coding Assistants to Try in 2024

1. Omnipilot

Imagine an AI that can type anywhere on macOS, with full context of what's on your screen. Imagine if, your email wrote itself, your terminal was fluent in Bash, your team updates became effortless. You don’t have to imagine any of this anymore. You can download Omnipilot’s MacOS AI Copilot for free right now and use AI anywhere on MacOS!


Try our free AI copilot today — just head to omnipilot.ai and enter your email, and you’ll be able to download our MacOS app in seconds! Let Omnipilot make your life easier.

2. DataLab AI Assistant

Datalab is a cloud-based Jupyter Notebook that uses the latest AI technology to assist users with insights generation, writing code, debugging, and auto-completion. It can also identify errors and offer solutions within seconds, meaning that generating a proper data analysis report, usually taking hours for a professional data scientist, can now be done in just a few minutes. Within a few seconds, you can load your data and ask the AI to generate or analyze interactive visualizations. It will automatically create the code and run it for you.


3. ChatGPT

ChatGPT is well-known for its use as an AI coding assistant that helps generate code snippets, solve issues, and brainstorm ideas. It is fast, reliable, and available for free to everyone. The best way to use ChatGPT is to provide code context or a detailed description of your project before asking technical questions. 


By offering context, you enable ChatGPT to generate more accurate and relevant responses, helping you write and test your code more effectively. ChatGPT's primary goal is to assist users in their inquiries and tasks, making it an invaluable resource for developers and learners.


4. Codeium

Codeium is the most popular and free solution for enhancing your development experience with intelligent autocomplete, AI chatbot, context-aware code generation, and more developer features. It is secure and provides a faster response similar to GitHub copilot. It also provides a paid option to access the advanced GPT-4 model and other administrator tools. Overall, this is a good AI coding assistant if you are starting out and want fast and accurate code generation.


5. Blackbox AI

Blackbox AI is a coding assistant that uses artificial intelligence to help developers write better code. It provides real-time suggestions for code completion, documentation, and debugging. It integrates with various developer tools, making it easy to use within your existing workflow. Blackbox AI has several features, including autocomplete, AI chat, AI commit, AI code suggestion and generation, and file difference comparison.


6. GPT4ALL

GPT4ALL is an open-source chat user interface that runs open-source language models locally using consumer-grade CPUs and GPUs. Just download and install the software, and you are good to go. This chatbot is context-aware, meaning you can provide it with the location of your coding project and ask the AI questions to understand and improve the existing code. 


Using open-source extensions, you can use GPT4ALL, an API server that you can integrate into your Integrated Developer Environment (IDE). The GPT4ALL is a private chatbot that supports all open-source models and runs seamlessly on any machine.


7. Tabby

Tabby is an AI coding assistant that can be hosted on your local machine using Docker, providing an open-source and on-premises option to GitHub Copilot. It offers several significant features, such as being self-contained and not requiring any database management system or cloud service. Its OpenAPI interface allows for easy integration with existing infrastructure, such as cloud IDE. It supports consumer-grade GPUs.


8. Code GPT

CodeGPT VSCode extension is a reliable tool that assists you in coding more efficiently by offering AI chat assistance, auto-completion, code explanation, error-checking, and much more. It also allows you to use various AI models from different providers, enhancing your coding experience. 


Although it is not an open-source tool, you can use this extension to access open-source models online and locally. It supports Ollama and LM Studio, private software that can run your LLMs locally. You can connect LLM models using API keys provided by OpenAI, Microsoft Azure, Google, Anthropic, Cohere, Mistral, and Huggingface.


9. Cody

Cody is a powerful open-source AI coding assistant designed to help developers write and debug code more efficiently. You can start using it by installing the extensions in VSCode and JetBrains. Cody uses state-of-the-art AI models (Claude 2, GPT-4) to provide autocomplete and answer various coding questions about your project. It helps you write better code by fetching relevant code context from your entire codebase.


Cody also has an inline chat feature that allows you to ask Cody to fix or refactor code from anywhere in a file. You can use commands such as "Document code," "Explain code," or "Generate Unit Tests" to further improve your coding experience.

10. GitHub Copilot

GitHub Copilot is a coding AI assistant that made waves when it was launched as it was the first of its kind to use the advanced GPT-3.5 model. Its initial release showcased impressive speed and accuracy, surpassing many other tools available. 


Over time, GitHub Copilot has continued to improve and now offers an even better experience for developers. The latest version of GitHub Copilot has various features, including AI chatbot, inline chatbox, code generation, autocomplete, CLI autocomplete, and other GitHub-based features to help with code search and understanding.


11. Tabnine

Tabnine is the leading AI coding assistant that prioritizes privacy, security, and compliance while accelerating and simplifying software development. In addition to code completion and debugging, it includes a real-time chat feature that allows you to write code more quickly. It also generates unit testing, refactors your code, helps you understand your code, and generates documentation. It is faster at generating code than most other tools.


12. Replit AI

Replit AI is a cloud-based IDE that uses artificial intelligence to enhance the development experience. While some AI features are free, the complete set is only available through a subscription to Replit Core. With Replit Core, users can access unlimited AI chat responses, advanced AI models, additional features, and unlimited private projects. 


You can chat with AI-powered assistants like ChatGPT or use In-line AI for code editing and generation. This is a perfect platform for kids and beginners who want to learn and build new and exciting things without paying much for cloud services.


13. Amazon CodeWhisperer

Amazon CodeWhisperer may be the perfect choice for developers working on AWS-based projects. With support for over 18 programming languages including Java, Python, JavaScript, TypeScript, and C#CodeWhisperer offers a versatile and efficient coding experience. CodeWhisperer sets itself apart from other AI coding software by employing the vast knowledge and experience of Amazon's developer community. 


It provides intelligent code suggestions and completions based on best practices and real-world examples, helping developers write clean, efficient, and maintainable code. Native integration with AWS services and tools, such as AWS Cloud9, further improves workflow efficiency and development productivity.


14. CodeWP

CodeWP is an AI-powered coding assistant designed specifically for WordPress developers. It integrates well into your WordPress development workflow, providing intelligent code suggestions, snippet creation, and error detection. Unlike other AI coding assistants that work with a wide range of languages and frameworks, CodeWPis is designed exclusively for WordPress development.


15. Android Studio Bot

Android Studio Bot is a dedicated coding AI helper built specifically for the Android ecosystem. With its focus on Java and Kotlin, the two main languages used in Android app development, Studio Bot integrates flawlessly into the Android Studio IDE, providing developers with intelligent code completion and generation capabilities in the familiar development environment. 


One of Android Studio Bot's distinguishing features is its ability to generate code snippets based on natural language chat messages. Developers can simply describe what they want to accomplish, and Android Studio Bot will provide relevant code suggestions and completions.


16. AskCodi

AskCodi is a coding assistant characterized by its ability to understand and respond to natural language queries. Supporting over 50 programming languages, AskCodi provides instant answers and code snippets to help developers quickly overcome coding challenges. AskCodi also offers several specialized AI tools, such as the Code Fixer, regex explainer, Big-O analyzer, and Language Translator. This makes it ideal for experienced programmers and those just learning a new language.


17. SQLAI

SQLAI is another niche coding assistant that focuses on helping developers work with SQL queries. Unlike other AI for coding that supports many programming languages, SQLAI dedicates its expertise to SQL, making it an ideal choice for developers who work extensively with databases.


With SQLAI, you can easily generate SQL queries by describing your requirements in natural 

language. The AI assistant will understand your intentions and provide accurate and optimized SQL code snippets. It also offers detailed explanations of the generated queries, helping you understand their logic. SQLAI can detect and fix errors in your SQL queries, saving you valuable debugging time.


18. DeepCode AI

Snyk is an innovative security tool that uses AI to detect and fix vulnerabilities in code. It combines multiple AI models, security-specific training data, and the expertise of top security researchers.


DeepCode AI, the backbone of Snyk Code, is designed to provide the market's fastest and most accurate static application security testing (SAST). With support for 11 programming languages and a vast knowledge base of over 25 million data flow cases, Snyk's DeepCode AI is specifically designed to find and fix vulnerabilities while helping to manage technical debt.

19. Amazon CodeGuru

Amazon CodeGuru is a powerful AI-driven tool that helps developers improve their code's quality, security, and performance. CodeGuru consists of two main components: CodeGuru Reviewer and CodeGuru Security. CodeGuru Reviewer uses machine learning to identify potential defects, bugs and optimization opportunities in your code. It provides intelligent recommendations based on best practices and common coding patterns


20. MutableAI

MutableAI is a tool that revolutionizes the coding experience with features such as AI autocomplete, one-click production code enhancements, prompt-driven development, test generation, and extensive language and IDE integration, empowering developers to write code more efficiently and effectively.


21. Codiga

Codiga is designed to elevate the coding experience by providing intelligent support, autocomplete suggestions, and code optimizations, enabling developers to write code more efficiently and effectively. Supports languages like:

  • Dart
  • Python
  • C
  • C#
  • Scala
  • Ruby
  • Go, 
  • GitHub
  • BitBucket
  • VS Code 
  • JetBrains IDEs

22. CodeT5

CodeT5 is an advanced tool specializing in text-to-code generation, code-to-code translation, and code summarization, empowering developers to bridge the gap between natural language instructions and executable code, facilitating language translation, and simplifying code comprehension. CodeT5 excels in generating code snippets or functions from natural language descriptions, enabling developers to convert textual instructions into executable code.


23. OpenAI Codex

OpenAI Codex offers quick setup, AI-driven code completion, and natural language prompting, making it easier for developers to write code efficiently and effectively while interacting with the AI using plain English instructions.


24. Cursor

Cursor is the code editor dedicated to pair programming with AI. It supports code generation and autocomplete suggestions. There is also a chat to talk with AI taking the currently open file into account. The Cursor can crawl the documentation of third-party libraries.


Auto-Debug proposes fixes directly in the open terminal window. Similarly, quick fixes for issues detected by lint are available. The Terminal feature turns the English language into proper commands. The cursor supports images in the prompt.

25. Divi AI

Divi AI is an advanced artificial intelligence tool designed to work within the Divi Builder ecosystem, a popular WordPress theme and visual page builder. It can generate written content, code, and create images directly within the Divi Builder. Divi AI considers the overall context of your site and the specific page you’re working on, ensuring that the content it creates aligns with your website's aesthetic and functional aspects.


26. CodeGeeX

CodeGeeX is a large-scale, multilingual AI coding assistant pre-trained on a large body of code from over 30 programming languages. Trained on a cluster of Ascend 910 AI processors (arguably the world’s most powerful AI processor), CodeGeeX’s AI was designed with only one function in mind: making developers code more in less time. CodeGeeX has four modes: stealth, prompt, interactive, and translation. 


The most impressive mode out of all four is the translation mode — in which CodeGeeX takes your code and translates it into any language you choose. This means you can copy someone’s code in JavaScript and translate it into C#, or vice versa. If you’d like a more in-depth exploration of CodeGeeX, you can read about it here.


27. Visual Studio IntelliCode

Visual Studio IntelliCode is an AI-powered coding assistant developed by Microsoft. It utilizes machine learning algorithms to analyze patterns and best practices from various code repositories, including open-source projects on GitHub. By learning from this vast codebase, IntelliCode can offer contextually relevant suggestions to developers as they write code, saving time and reducing errors. 


IntelliCode is designed to recognize common coding tasks. Because of this, it can recommend the right quick action, and even complete it while you’re typing. With multilingual support, customization, and context aware recommendations, CodeGeeX is designed to enhance the productivity and efficiency of developers.


28. Sourcery

Sourcery is a coding assistant and refactoring tool specifically for Python and JavaScript. It aims to automate repetitive or tedious coding tasks and helps improve code quality. Sourcery analyzes code and suggests automated refactoring, code optimizations, and best practices. It suggests ways to enhance code quality by identifying potential bugs and performance bottlenecks. 


Sourcery aims to assist developers in improving code quality, reducing technical debt, and automating repetitive tasks. By leveraging automated refactoring and code analysis, Sourcery enhances the coding experience and promotes cleaner, more efficient codebases.


8 Best Practices for Leveraging AI Coding Assistants

1. Encapsulate AI-Generated Code

When you integrate AI-generated code into your software development project, encapsulate it into defined modules or functions. This approach immediately boosts readability and usability. By wrapping the AI-generated code into higher-level structures, such as functions or classes, you create cohesive units that can be invoked or interacted with easily. 


Encapsulating code promotes modular design, breaking down complex systems into more manageable units and making your codebase more modular and easier to understand. Encapsulated units can be reused across different parts of a program or other projects, enhancing efficiency and maintenance.


2. Document AI Usage Thoroughly

Thorough documentation is crucial when incorporating AI-generated code into your work. Documenting the AI-generated code enhances transparency, making it easier for team members, stakeholders, and future developers to understand how AI models are utilized within the codebase. 


Proper documentation also facilitates replication of the AI models, aiding future developers or researchers in reproducing, validating, improving, or adapting the models to new data. Documentation serves as a reference for understanding the intended functionality of the AI components and identifying potential areas for improvement. It also aids in knowledge transfer between team members, reducing the risk of knowledge silos within the team.


3. Familiarize AI Tools with Your Coding Standards

To optimize the performance of AI coding assistants, provide them with information about your coding standards, style preferences, and project-specific guidelines. Equipping the AI assistant with knowledge of your coding rules and practices helps tailor the generated code to align closely with your team's best practices, reducing rework down the line and enhancing overall code quality.


4. Create Specific and Detailed Prompts

Craft specific and detailed prompts when engaging AI coding tools. Clearly articulating your requirements, including particular libraries, frameworks, or constraints, helps the AI assistant understand your needs better and generate code that closely aligns with your project requirements. Detailed instructions are essential as AI coding tools lack human intuition and context needed to comprehend what you aim to achieve.


5. Review and Test AI-generated Code Thoroughly

Avoid blindly copying and pasting AI-generated code into your project. Take the time to comprehend and adapt the logic to meet your project's specific requirements. Reviewing and testing AI-generated code ensures seamless integration and compliance with coding standards, performance considerations, and project-specific nuances. Use static code analysis to identify potential errors and require code reviews and approval of all auto-generated code to enforce quality standards.


6. Validate AI Coding with Human Expertise

While AI can offer valuable suggestions and insights, human intuition and experience are essential for ensuring the quality and appropriateness of generated code. Validate AI-generated code against established solutions, industry best practices, and company coding standards. By cross-referencing AI-generated code with human expertise, you can ensure high-quality code that meets your project requirements.


7. Create an Iterative Process

Develop an iterative process for refining and improving AI-generated code. You can achieve the desired outcome effectively by creating an ongoing cycle of generating, reviewing, and refining code. Input your coding standards, break down tasks into smaller steps, create specific prompts, review and analyze the generated code, refine the process if unsatisfied with the results, and continue iterating until achieving optimal outcomes. Iterative processes for validating AI-generated code quality are crucial for building a development culture that prioritizes code quality.


Try Our MacOS AI Copilot for Free Today

Omnipilot's AI Copilot for MacOS is a groundbreaking tool that has the capability to revolutionize your daily tasks with its artificial intelligence-powered assistant. Omnipilot can enhance your productivity and efficiency in coding, writing emails, and managing team updates. By seamlessly integrating AI into your workflow, Omnipilot ensures you have the support you need to excel in your coding projects and communication tasks.


Writing and Coding Efficiency with Omnipilot's AI Assistance

Imagine an AI accompanying you wherever you type on MacOS, providing intelligent suggestions and contextually relevant information to enhance your writing. Omnipilot allows you to effortlessly write emails and code in the terminal with Bash and streamline your team's updates. By leveraging the power of Omnipilot's AI Copilot, you can supercharge your productivity and reduce the time spent on repetitive tasks.


Accessing Omnipilot's AI Copilot for Free

The Omnipilot MacOS AI Copilot is available for free, enabling you to experience the benefits of AI assistance without any financial commitment. Simply visit omnipilot.ai, enter your email, and start using the MacOS app within seconds. Let Omnipilot become your trusted AI coding assistant and witness the positive impact it can have on your daily tasks. 


Try our free AI copilot today and unlock the full potential of AI in your coding journey.


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