The Top 5 AI Code Generation Solutions For Developers
Streamline your coding process with our top AI code generation and documentation solutions. Get more done in less time.
Written by Joel Witts
Technical Review by Laura Iannini
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1.
Amazon Q Developer
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2.
OpenAI Codex
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3.
GitHub Copilot
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4.
Replit Ghostwriter
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5.
Tabnine
AI code generation and documentation solutions can help programmers to automatically generate code and documentation, improving the efficiency of the coding process. They use generative AI technologies to instantly produce high-quality code for developer teams.
Breakthroughs in Large Language Model (LLM) technologies are enabling us to interface with powerful AI generative chatbots, which can turn our natural language requests into anything from academic essays to movie scripts. This has powerful benefits to many industries, but particularly programming.
Programmers can ask AI technologies to create customized code using plain text requests, which can then be edited and refined by humans. The code generated by AI technologies is becoming increasingly accurate and can help speed up the coding process and improve the quality of documentation. However, it is important to note that this is an emerging category of product, and the technology is still very much being developed and iterated.
In this article, we’ll cover the top AI code generation and documentation solutions for programmers. We’ll cover how the service works and its key features and unique selling points to help you find the right AI code and documentation solution.
Amazon Q Developer
Amazon Q Developer is a generative AI-powered solution for software developer teams using AWS.
- The platform helps you code faster by generating real-time suggestions as you code. This includes snippets to full functions based on comments and existing code. It also offers CLI completions and natural language to bash translation to make using command line a lot easier.
- It can implement new features, generate code documentation and spin up new projects. You can use a single prompt to built out complex, multi-step tasks. It can also automate the process of modernising legacy code.
- It secures code by scanning for vulnerabilities and suggesting remediations that help to fix code, directly in the IDE, command line or console.
- Outside of coding, Amazon Q can be used to explain AWS features, analyze your bill, ask questions about AWS’ support documentation.
Amazon Q Developer
OpenAI Codex
OpenAI is a globally leading AI research and development company, with products used by tens of millions of users around the world.
- OpenAI Codex is a model built on OpenAI’s GPT-4o family of large language models – similar to OpenAI’s ChatGPT chatbot. OpenAI Codex translates natural language into code, with a very simple, intuitive user interface.
- Developers can use natural language prompts, such as “Say Hello World”, to generate code for any virtually any purpose and in any programming language, with varying levels of complexity.
- Users can modify and prompt for iterations on the code provided, and export to different applications via plug-ins.
- OpenAI Codex powers the GitHub Copilot tool, also featured on this list, which was launched in partnership with OpenAI. The model has been trained on billions of lines of code and is most capable in Python, but supports over a dozen coding languages.
OpenAI was founded in 2015 and has raised more than $11bn USD in funding to date. The company is headquartered in San Francisco.
OpenAI Codex
GitHub Copilot
GitHub Copilot is reportedly the most widely used AI coding tool, developed by GitHub and OpenAI. It suggests code and functions in real time from the GitHub editor.
It leverages the natural language capabilities of OpenAI’s GPT-3 family of large language models to generate code from natural language prompts. It is also able to describe code in natural language, autocomplete repetitive chunks of coding, and translate code between different programming languages.
- Copilot provides an autocomplete feature to automate the creation of repetitive chunks of code.
- It keeps track of your work, suggests descriptions, and helps reviewers reason with any changes made.
- A key benefit of this tool is that it enables programmers to navigate unfamiliar coding languages by describing code in plain English.
GitHub Copilot
Replit Ghostwriter
Replit is a collaborative software platform that enables programmers to work together on code from anywhere in the world, with a community of over 20 million software creators.
Replit’s Ghostwriter tool is an AI-powered assistant that automates repetitive coding tasks and detects and fixes errors.
The platform allows users to instantly start developing projects in any programming language, with zero set up required.
- AI chatbot, which you can ask to generate code in 16 common languages, review your code for errors, and answer questions about unfamiliar coding databases.
- Provides accurate, contextual answers to help improve the quality and speed of your workflow.
- It suggests autocompletes as you code, helping speed up more repetitive coding tasks, and it can provide natural language code summaries.
Replit was founded in 2016 and has raised $106m USD in funding to date. The company is headquartered in San Francisco.
Replit Ghostwriter
Tabnine
Tabnine is an AI tool for software developers that can generate whole-line and full-function code completions.
The tool has been used by millions of developers worldwide, with users including Amazon, SpaceX, and Sony.
Tabnine’s models are trained on code from the ground up, with each model optimized for different programming languages or domains.
- Predicts and suggests lines of code based on context, including turning natural language into code.
- Turns natural language into high-quality code as you type. It automates code generation, using generative AI to predict and autocomplete whole-line and full-function code completions.
- The completions are flexible and can be run on a laptop, inside your firewall, or in the cloud.
- It supports all popular coding languages, including JavaScript and Python, as well as more niche use cases, and you can switch AI models to ensure you’re using the most suitable one for your current task.
- Integrates with most popular IDEs.
Tabnine has raised $32m USD in funding to date. The company was launched in 2013, and is headquartered in Tel Aviv, Israel.
Tabnine
Other AI Security Solutions Services
We researched lots of AI code-gen solutions while we were making this guide. Here are a few other tools that are worth your consideration:
A free toolkit for writing better code, faster, with auto-complete, a support chatbot, and natural language search.
A gen-AI tool that helps you create interactive, living documentation, with the ability to "chat" with your codebase.
An AI assistant that helps you write and fix code more efficiently, using advanced search and codebase context.
FAQs
Everything You Need To Know About AI Code Gen Solutions (FAQs)
AI code generation and documentation solutions are natural language AI models that are trained on a massive amount of source code and natural language data, which enables them to generate code, given a natural language prompt.
These solutions can generate high-quality code by leveraging large neural networks that have been trained on a diverse set of programming languages and natural language data. They can then be used to generate a wide range of code, from small snippets to larger programs, based on plain text prompts given by developers, who can then use the code in their applications and products.
This is a new category of solutions, with many start-up players that are constantly iterating their technologies, as well as a variety of open-source options. Some have highlighted that the monetization strategy for this market is still immature, and so there are likely to be changes to the vendors and technologies in this market over time.
Read our other guides to the best AI technologies:
Written By
Joel Witts is the Content Director at Expert Insights, meaning he oversees all articles published and topics covered. He is an experienced journalist and writer, specialising in identity and access management, Zero Trust, cloud business technologies, and cybersecurity. Joel is a co-host of the Expert Insights Podcast and conducts regular interviews with leading B2B tech industry experts, including directors at Microsoft and Google. Joel holds a First Class Honours degree in Journalism from Cardiff University.
Technical Review
Laura Iannini is an Information Security Engineer. She holds a Bachelor’s degree in Cybersecurity from the University of West Florida. Laura has experience with a variety of cybersecurity platforms and leads technical reviews of leading solutions. She conducts thorough product tests to ensure that Expert Insights’ reviews are definitive and insightful.