Automating Fork Maintenance with AI Agents | Cohere

This post details the application of AI agents to automate the maintenance of software forks, specifically syncing with upstream releases, resolving merge conflicts, running tests and benchmarks, and fixing regressions. It describes a general method for automating that cycle using AI coding agents, applied to a fork of vLLM. The approach compresses the time to absorb a new upstream release from weeks to days, with humans only reviewing the outcome. It introduces five open-sourced skills: install-vllm, local-test-runner, detect-upstream-base, rebase-assistant, and auto-rebase, which instantiate the general pattern of disturbance injection, measurement collection, and controller action.