We want you to build the next Git platform on Cloudflare
Source
blog.cloudflare.com
Date
Key takeaways · AI-distilled
Artifacts repositories can now deploy to Workers through Workers Builds: pushes to the production branch build and deploy the Worker, while pushes to other branches create or update isolated, shareable Workers Previews.
An Artifacts binding makes Git programmable from a Worker: code can create or fork repos, read files and commits, and issue repo-scoped Git tokenThe chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.Full definition →. Cloudflare's example forks a project for a new AI agentAn AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.Full definition → task and reads its AGENTS.md for instructions.
Artifacts emits events when a repo is created, imported, forked, deleted, pushed to, cloned or fetched. Subscribing to push events lets a Worker start a review workflow for each push, passing the repo, branch and new commit to a review agent.
Namespaces can be pinned to U.S. or EU jurisdiction for storage and processing, and per-repo metrics show operations, pulls, pushes, errors and error rate. Billing for repository operations and stored data starts October 15, 2026.
Cloudflare's competition wants an agent-native Git platform on Workers and Artifacts, not GitHub with agents added. Entries need concurrent multi-agentUsing several AI agents on one problem — splitting work in parallel, checking each other, or filling different roles like planner and reviewer.Full definition → changes, permissively licensed source and a 5-10 minute demo by October 14, 2026; first place gets $25,000 in credits.
Terms in this piece · Glossary
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
multi-agent — Using several AI agents on one problem — splitting work in parallel, checking each other, or filling different roles like planner and reviewer.
