GitHub is quietly reshaping how AI fits into our workflows. And the most interesting project isn’t on the main site.
It’s a part of a small skunkworks style group called GitHub Next. One of their newer explorations: Continuous AI.
The idea borrows from something developers have used for years — continuous integration. When code is updated, it runs tests and ships changes automatically.
But now imagine that approach applied to AI-driven tasks.
Continuous Documentation: An agent updates the documentation. Fix a bug? It writes a changelog entry. Add a feature? It summarizes what changed and why.
Continuous Code Improvement: Incrementally improving code comments, tests, and other aspects of code
Continuous Triage: Labeling, summarizing, and responding to issues using natural language
What would “continuous” look like in your work? Continuous writing. Continuous research. Continuous decision support.
