Pieces for Developers enriches your content as you save snippets and makes it easy to get back to where you originally saved your code.

Origin Details#

When you save something to Pieces for Developers, it not only saves the material itself; but further, our Context Awareness Engine and Origin Details automatically attach related context & metadata, enabling powerful organization, search, and suggestion capabilities.

Reference code is everywhere these days. Whether it's a solution that you're adapting from Stack Overflow or doc-site boilerplate sent over Slack or Microsoft Teams, all code comes from somewhere.

Where a code snippet came from and the larger context it was taken out of is often lost when saving or sharing reference materials, making it incredibly difficult to find, share, or reuse it later on.

Protecting Context#

In an effort to maintain this invaluable context, Pieces for Developers automatically extracts and associates useful origin details every time you save a resource.

Project Name, Source File, Line Numbers, Collaborators, Solution Publishers, Application Source, etc.

AI-Generated Smart Labels#

Doubling down on our efforts to make search and suggestion world-class, Pieces for Developers ships with an offline and on-device ML Material Labeling model that automatically generates smart labels for everything you save.

“HTTP Request”, “Flutter Framework”, "Dart Project", "Conditional For Loop"

User Added Tags#

In addition to our auto-generated smart labels, our Context Awareness Engine automatically layers in tags that correspond to origin details and related links.

You can easily add your own tags as a manual way to further organize your saved resources while driving a more personalized search and suggestion experience.

Our users are saving more than ever. That said, a large part of our material enrichment efforts are allocated toward making searches and suggestions first-class.

AI-Generated Smart Descriptions#

With these goals in mind, Pieces for Developers ships with an offline and on-device ML Material Description model that generates a smart description for everything you save.

e.g., What the code snippet or resource is, what it does, how to use it, and how it might be used in the future.

Associated Commit Messages#

These smart descriptions, coupled with relevant commit messages extracted via our Context Awareness Engine, enable awesome reference and reuse experiences later on in a user's workflow.

Related People#

These days, technical work is more people-centric than ever. Writing and reviewing code, upskilling on ever-evolving best practices, migrating to new framework versions, and onboarding new developers— it all builds on the work of others.

It's a challenge simply to know who to reach out to for additional context, who to add as a reviewer on pull requests, or who might provide a different perspective to save some serious time and prevent major headaches.

What problem does this solve?#

To help solve this dilemma, our Context Awareness Engine automatically associates Relevant Collaborators, Maintainers, and Content Authors with the resources you save.

Related Links, External Resources, & Reference Materials#

More and more developer resources live online nowadays. Saving the links you found while researching or problem-solving in the browser, code, or documentation has never been easier.

What type of Links?#

With Pieces for Developers, you can quickly associate URLs to external resources like Documentation Pages, Wiki Links, Jira Tickets, Pull Requests, and GitHub Issues with your saved materials.

Smart Warnings and Sensitive Information Detection#

Some of the most commonly saved snippets are Powershell and Command Line instructions, boilerplate for unit tests, .env variables, HTTP requests, and CI/CD build configs. These often contain sensitive data like API keys, auth tokens, usernames, passwords, or service account credentials.

Security Practices#

Pieces for Developers facilitates security and programming best practices by detecting sensitive information and warning against accidental uploads or sharing.