32 AI Assisted Coding Tools You Need for Faster Development

AI assisted coding has revolutionized the healthcare industry, boosting productivity and efficiency. This technology, often referred to as AI Copilots, allows healthcare professionals to accurately document patient records and streamline the coding process. AI Copilots ensure accurate codes and improve provider reimbursement rates, reducing the risk of errors and increasing compliance. This technology helps healthcare organizations save time and reduce administrative burdens, allowing clinicians to focus on patient care.

What Is AI Assisted Coding?

AI-assisted coding is the use of machine learning models to generate code automatically. Most existing AI-assisted coding tools let developers describe in natural language what they want their code to do. Then, the tools automatically generate the code to do it, complete with custom variable names and the invocation of external modules or services, where necessary.

The role of AI-assisted coding in the software development process is to automate and expedite the process of writing code and debugging it. With the help of AI algorithms, developers can generate custom code from scratch entirely based on natural-language descriptions. This can potentially eliminate the limitations of traditional coding methods, allowing for the creation of highly complex applications.

Key Features of AI-assisted Coding

AI-assisted coding solutions have matured over the past couple of years and represent a major innovation in software development. These tools offer several key features such as

Code Suggestions

AI algorithms analyze large codebases, learn patterns, and generate 

recommendations for developers based on existing source code examples.

Automated Debugging

These tools can identify bugs in the code and offer automated debugging solutions to improve the efficiency of the coding process.

By utilizing vast amounts of existing source code, AI-assisted coding algorithms can provide developers with customized code on demand, making the software development process more efficient and less error-prone.

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Advantages of AI Assisted Coding

Increased Efficiency and Productivity

AI-assisted code generators streamline the coding process by offering intelligent suggestions and automating repetitive tasks. Code generation tools suggest code completion that can help developers code faster and create cleaner code that needs less debugging. Plenty of time-consuming and repetitive tasks associated with coding, like writing boilerplate code, code formatting and compilation, and performing basic SQL queries and data exploratory analysis, can be automated. 

A strong example of how generative AI can help developers work more efficiently is the international study from 2021, in which AI tools were used to translate legacy source code into Python. Even when the AI’s suggestions weren’t correct, the AI recommendations helped developers find and fix mistakes faster than manual translation. In collaboration with AI code generators, human developers can use the time they used to spend on mundane tasks to focus on more complex aspects of software development that require human creativity and intuition.

Provides Access to Non-Developers

AI-assisted coding tools empower non-developers within your team, such as product managers or designers, to understand and contribute to the codebase. Anyone new to coding can use these tools to significantly lower the learning curve of becoming a developer. 

Those learning to code with the help of AI tools can get code suggestions and textual guidance based on existing code examples and best practices, allowing novice coders to make requests and create functions in human language before they can speak programming languages. By encouraging non-developers to learn about code quickly and intuitively, AI coding tools can spur better cross-functional collaboration within software development teams.

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32 Best AI Assisted Coding Tools

1. Omnipilot: AI Copilot for MacOS

Omnipilot is an AI tool that enables efficient typing and code generation on MacOS. It can automate tasks such as writing emails, executing Bash commands, and updating team projects effortlessly. Omnipilot's key feature is its ability to provide context-aware assistance while typing, enhancing productivity and streamlining coding tasks on MacOS.

2. GitHub Copilot: Code Completion Tool

GitHub Copilot is a code completion tool that offers AI-driven coding assistance in real-time. It uses advanced AI to understand the context of the code being written and provides intelligent code completions and explanations directly within the IDE. GitHub Copilot is trained on a vast array of open-source code from GitHub, enhancing the development process by streamlining coding tasks.

3. Tabnine: AI Coding Assistant

Tabnine is an AI coding assistant focused on privacy and security. It is trained on a wide range of open-source code, ensuring privacy and security while offering tailored assistance to align with the team's coding style and best practices. Tabnine's key benefit is its ability to enhance code completion and align with the organization's collective knowledge, making it a preferred choice for developers.

4. Amazon CodeWhisperer: ML-driven Code Generation Tool

Amazon CodeWhisperer is a machine learning-driven code generation tool that provides real-time coding recommendations tailored to individual coding styles. It offers code suggestions ranging from snippets to entire functions based on the context of the existing code. CodeWhisperer can also generate comments and code documentation, further enhancing the coding experience.

5. Replit AI: AI Code Tools Suite

Replit AI offers a suite of AI code tools designed to elevate the coding experience on the Replit platform. It includes features such as intelligent code completions, code generation, and code explanations. The tools work in unison to streamline the development process and provide insightful modifications to the code, enhancing productivity and efficiency in coding tasks.

6. Sourcegraph Cody: AI Coding Assistant

Sourcegraph Cody is an AI coding assistant that enhances the speed and comprehension of software development. It provides AI-assisted autocomplete capabilities with a deep understanding of the codebase. Cody offers intelligent code suggestions for various languages, configuration files, and documentation, making it a valuable tool for developers seeking efficient code completion.

7. AskCodi: AI-Powered Coding Assistant

AskCodi is an AI-powered coding assistant based on OpenAI GPT, offering a suite of functionalities such as code generation, unit testing, documentation, and language translation. It supports popular development environments like Visual Studio Code and JetBrains' suite, enabling developers to engage in AI-facilitated coding dialogues. AskCodi supports a wide array of major programming languages, enhancing its versatility and applicability.

8. CodeWP: Simplifies WordPress Custom Functionality

CodeWP simplifies the integration of custom WordPress functionalities by providing up-to-date solutions and code suggestions. The AI evolves to deliver accurate and beneficial code snippets, offering ready-made solutions for typical WordPress challenges. CodeWP serves as a foundational element to expedite the development process, making it a valuable tool for WordPress developers seeking efficient code generation.

9. Android Studio Bot: AI-Powered Assistant for Android Development

Studio Bot is an AI-powered assistant within Android Studio designed to boost productivity and streamline development tasks. It interprets and responds to development inquiries in natural language, enabling users to receive assistance with code generation, resource location, best practices, and time management for Android development tasks. Studio Bot simplifies the coding process and enhances efficiency for Android developers.

10. SQLAI: AI Tool for Query Generation

SQLAI is a tool that generates queries for SQL and NoSQL databases, offering immediate results and a personal library to store custom SQL and NoSQL snippets. It supports effortless integrations with popular databases such as MySQL, Postgres, Oracle, SQL Server, and MongoDB, enhancing compatibility and flexibility for developers. SQLAI simplifies query generation tasks, making it a valuable tool for database developers.

11. DeepCode AI: Snyk SAST Component

DeepCode AI is a component of the Snyk SAST platform equipped with multiple AI models trained on extensive security-focused datasets. It efficiently identifies and remediates security vulnerabilities and manages technical debt, enhancing code quality and security. DeepCode AI offers valuable insights for developers seeking efficient security-focused code analysis and management.

12. OpenAI Codex: Prominent AI Code Tool

OpenAI Codex is a prominent AI code tool based on OpenAI's LLMs and trained on billions of lines of code. It supports more than a dozen programming languages and offers comprehensive code-generation capabilities. OpenAI Codex is proficient in handling various coding tasks with similar capabilities, making it a valuable tool for developers seeking efficient and accurate code generation.

13. ChatGPT (GPT-3/4): Popular AI Chatbot

ChatGPT is an AI chatbot created by OpenAI, capable of generating code and broadening contextual awareness through transformers. It offers a wider scope of responses and can generate human-like responses with code suggestions. ChatGPT is popular among developers seeking assistance in speeding up the coding process and generating code efficiently, making it a valuable tool for AI-assisted coding tasks.

14. CodeT5: AI Code Generator

CodeT5 is an open AI code generator that helps developers create reliable and bug-free code quickly. It supports various programming languages like Java, Python, and JavaScript, providing efficient code generation capabilities. CodeT5 is open-source and offers both online and offline versions for enhanced data security and flexibility, making it a valuable tool for developers seeking efficient code generation solutions.

15. Polycoder: Open-Source Alternative to Codex

Polycoder is an open-source alternative to OpenAI Codex trained on a vast codebase in multiple programming languages. It enables developers to generate code for a wide range of applications, including web development, machine learning, and natural language processing. Polycoder's capability of generating code quickly makes it a preferred choice for developers seeking efficient and reliable code generation solutions.

16. Codiga: Secure Code Analysis Tool

Codiga is a static analysis tool designed to ensure code security and efficiency, supporting popular languages like JavaScript, Python, Ruby, and Kotlin. It enables developers to test code for vulnerabilities and security issues in real-time, offering an auto-fixer to address any issues efficiently. Codiga enhances code security and quality, making it a valuable tool for developers seeking secure code analysis solutions.

17. PyCharm: AI Code Completion Tool

PyCharm is an AI code completion tool from JetBrains offering intelligent code completion capabilities for various programming languages like Java, Python, and JavaScript. PyCharm is well-regarded for its accuracy and efficiency in reducing the time spent on coding tasks. PyCharm enhances code completion and accuracy, making it a valuable tool for developers seeking efficient code completion solutions.

18. AIXcoder: AI-Powered Programming Pair

AIXcoder is an AI-powered programming pair designed to aid development teams in writing code efficiently. It supports languages like Java, Python, and JavaScript, offering features such as automated routine tasks, code completion, real-time code analysis, and error checks. AIXcoder streamlines the coding process and enhances productivity for development teams seeking efficient code-writing solutions.

19. Ponicode: AI-Powered Code Assistant

Ponicode is an AI-powered code assistant designed to optimize developers' coding workflow using natural language processing and machine learning. It generates code from user-defined descriptions, providing efficient code-generation solutions. Ponicode is maintained by CircleCI, offering valuable assistance for developers seeking streamlined coding workflows and efficient code generation capabilities.

20. Jedi: Open-Source Code Completion Tool

Jedi is an open-source code completion tool that functions as a plugin for editors and IDEs using Python static analysis tools. It enhances code completion efficiency and accuracy for developers seeking reliable code completion solutions, offering valuable insights and assistance in coding tasks.

21. Wing Python IDE Pro: Python-Specific Development Tool

Wing Python IDE Pro is a Python-specific software setup offering code editing, navigation, and debugging mechanisms for software development. It includes features like intelligent code completion, refactoring, multi-selection, and code snippets, enhancing the coding experience for Python developers. Wing Python IDE Pro streamlines the coding process and improves efficiency for developers seeking Python-specific development tools.

22. Smol Developer: AI Agent for Code Generation

Smol Developer is an open-source AI agent designed to function as a personal junior developer capable of generating code from specific product specifications. It can create any kind of application based on unique requirements, offering a simple, safe, and small codebase. Smol Developer provides an honest and helpful approach to AI development, making it a valuable tool for developers seeking personalized code generation solutions.

23. Bard (Google Gemini): AI Tool for Programming Tasks

Bard is an AI tool that assists with programming and software development tasks, including code generation, debugging, and explanation. It supports more than 20 programming languages and can assist with writing functions for Google Sheets. Bard streamlines programming tasks and enhances productivity for developers seeking efficient coding solutions.

24. Code Llama (Meta): Large Language Models for Coding

Code Llama is a set of large language models specialized for coding tasks, built on the Llama 2 platform. It includes models for various needs, such as general-purpose coding, Python-specific tasks, and instruction-based coding. Code Llama enhances coding efficiency and accuracy by offering valuable insights and assistance for developers seeking reliable coding solutions.

25. Claude 2 & 3 (Anthropic): Natural Language AI Model

Claude 2 is a natural language AI model introduced by Anthropic, designed for enhanced input and output lengths with superior performance. It can handle up to 100K tokens in each prompt, working over hundreds of pages of technical documentation. Claude 2 enhances coding efficiency and accuracy, offering valuable insights for developers seeking efficient natural language AI solutions.

26. Stable Code 3B: Large Language Model for Code Completion

Stable Code 3B is a 3 billion parameter Large Language Model specialized in code completion, offering real-time performance and efficient coding capabilities. It is trained on diverse programming languages and software engineering-specific data, running on modern laptops without a GPU. Stable Code 3B enhances code completion efficiency and accuracy, offering advanced features for developers seeking reliable code completion solutions.

27. Plandex: AI Tool for Task Management

Plandex employs persistent agents to tackle extensive tasks, segmenting sizable tasks into manageable subtasks to streamline the coding process. It aids in clearing backlogs, navigating new technologies, overcoming obstacles, and reducing time spent on mundane activities. Plandex enhances task management and efficiency for developers seeking productive coding solutions.

28. MetaGPT: AI Tool for Software Outputs Generation

MetaGPT automates the generation of software development outputs like user stories, competitive analysis, and requirements from a single input. It integrates roles typically found in a software company into its workflow, offering detailed Standard Operating Procedures (SOPs) for a streamlined process. MetaGPT simplifies and automates complex tasks, enhancing efficiency and productivity for developers seeking reliable software outputs generation solutions.

29. AutoRegex: AI Tool for Natural Language Translation to Regex

AutoRegex translates natural language to regex, assisting developers in writing regular expressions efficiently. It simplifies the process of translating natural language to regex, making it easier for developers to create regex expressions accurately.

30. llama.cpp: AI Tool for LLM Inference

Llama.cpp facilitates LLM inference with optimal performance and minimal initial setup across various hardware. It supports Apple silicon through ARM NEON, Accelerate, and Metal frameworks, offering extensive hardware support for efficient inference. llama.cpp enhances LLM inference efficiency and accuracy for developers seeking reliable and optimized inference solutions.

31. Codeium: Free AI Tool for Coding Assistance

Codeium is a widely known and free AI tool that offers features similar to GitHub Copilot, providing context-aware answers to coding-related questions. It can help refactor, explain, improve, and resolve errors in code efficiently, enhancing the coding experience for developers seeking free and efficient coding solutions.

32. MutableAI: AI Tool for Enhanced Coding Experience

MutableAI revolutionizes the coding experience with features like AI autocomplete, one-click production code enhancements, prompt-driven development, test generation, and extensive language and IDE integration. It empowers developers to write code more efficiently and effectively, streamlining the coding process and enhancing productivity for developers seeking enhanced coding experiences.

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5 Best Practices for Efficient AI Assisted Coding

1. Use AI as a Partner, Not an Authority

Leverage AI as a partner in the coding process. It's crucial to actively engage with the AI to maintain your coding skills and ensure quality. While AI can provide incredible efficiency gains, your expertise and input remain essential for high-quality results. 

2. Evaluate Compatibility, Features, and Pricing

Before selecting an AI assistant, it's important to assess compatibility with your preferred programming languages and frameworks. Make sure the AI tool aligns with your workflow and project requirements. Consider the pricing model to determine the cost implications of equipping your entire team with the tool.

3. Prioritize Security

When integrating AI into coding practices, pay close attention to security. It's vital to ensure that the AI-generated code does not introduce any vulnerabilities. Consider using offline AI to run locally on your machine to enhance security and minimize risks associated with cloud-based systems.

4. Train the AI with Your Codebase

If the AI tool supports it, take the time to train the model with your specific codebase. By enhancing the AI's context-awareness, you can improve the quality of its suggestions and code contributions. The more the AI grasps your unique coding environment, the more valuable its insights will be.

5. Maintain Oversight

Regularly review the code generated by AI for adherence to best practices, security standards, and maintainability. This practice allows you to enjoy the benefits of AI while minimizing potential risks. Keep your finger on the pulse of the coding process by actively monitoring AI-generated code and ensuring it aligns with high standards.

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Omnipilot, an innovative AI copilot that promises to revolutionize MacOS productivity. Imagine having an AI at your fingertips that can type anywhere on your macOS system, fully understanding the context of what's on your screen. With Omnipilot, your email can practically write itself, your terminal can execute commands flawlessly, and team updates can be effortlessly managed. 

The best part? You don't have to imagine it anymore. Omnipilot's MacOS AI Copilot is available for free, allowing you to experience the power of AI in your daily tasks. By visiting and entering your email, you can download the MacOS app in seconds, unleashing the full potential of AI-assisted coding. 

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