We are a team of researchers and engineers at GitHub, exploring things beyond the adjacent possible. We prototype tools and technologies that will change our craft. We identify new approaches to building healthy, productive software engineering teams.
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What happens when you give PMs, compliance teams, and leaders their own agents? A tour of Agentics Beyond Code — an open-source set of GitHub Agentic Workflows for the non-engineering roles that ship, govern, and operate products.
GitHub Agentic Workflows filter untrusted GitHub content before it reaches the agent. Here’s why integrity filtering matters for repository maintainers, and how we built it.
Prompts are programs. You wouldn’t write a complex program completely from scratch, in a big, soupy loop without subroutines, and then write it again the next time you wanted to run it. Why let your agent work that way?
Borrowed from 3D rendering: level of detail. The loader shows more as it grows and strips back as it shrinks, so it reads cleanly at any size.
Canary puts a small, auditable gate in front of agentic workflows so untrusted artifacts are classified before powerful agents act on them.
https://github.com/githubnext/repo-assist-impact/blob/main/report.md
What happens when a proactive AI repository agent is deployed across 13 open source repositories? 578 issues closed, median 8x increase in issue closure velocity, and 10x in PR merge velocity — transforming largely dormant projects into actively maintained ones. The single most important factor? The rate at which human maintainers decide to act.