Pieces for Developers

Lately, we have seen a boom in Artificial Intelligence, especially after ChatGPT, where more and more companies are putting their stakes and working to create useful tools.

As a developer, I am always searching for new tools to help me with my coding, and I have recently found Pieces - the copilot for your entire workflow. It’s an AI-enabled productivity tool to help you stay organized and develop apps efficiently.

The good news is it’s not one of these extensions only available on VS Code. It supports many different applications (VS Code, JetBrains, browsers, etc.) and operating systems (Windows, Mac, and Linux).

Here’s a short version of this blog covering some amazing features.

Pieces for developers

Features

It has many features, and covering all of them won’t be possible. However, I will list some of the possibilities with Pieces, and you can figure out more from the docs later. Some of the fantastic features are the following:

Getting Started

Whether you plan to use it within VS Code or in Chrome, installing Pieces OS along with the desktop application (Windows/Mac/Linux) as well as the specific IDE, browser, or collaboration tool integration (VS Code in this case) is recommended.

You can find the download links here.

Once you install the OS version, you can start using features such as copilot chat, generating descriptions, creating shareable links, etc.

For some features, you may need additional plugins, such as the

Chrome extension, to save Stack Overflow snippets.

Pieces overview

Pieces overview - taken from pieces.app/blog

Use cases

The use cases of pieces are pretty obvious, but the most common ones are:

Conclusion

Pieces is a personalized AI assistant that helps to improve your coding efficiency. Not only developers but technical content creators can also use it to generate examples for their content.

What sets it apart from other similar tools is the integration support and flexibility. Pieces integrates with various development environments including Chrome, Visual Studio Code, and JetBrains, making it an adaptable tool across different platforms. Additionally, the ability to switch between different Large Language Models offers unparalleled flexibility, allowing developers to choose the model that best suits their specific needs, even Local LLMs.