Context-Aware AI Infrastructure & CI/CD-Native XOps for Open Source Governance

This project aims to build a context-first AI infrastructure to improve how contributors, maintainers, and repositories interact in open-source development. I will design and implement a system consisting of a Skill Bot (for answering contributor queries using repository-specific knowledge), a Skill Updater (to convert maintainer discussions into structured, reusable documentation), and a PR Dashboard (to help maintainers analyze and manage multiple pull requests efficiently). These components will be connected through a shared knowledge layer, ensuring that AI assistance is grounded in real repository context rather than generic responses, while maintaining a human-in-the-loop approach for reliability and control. In parallel, I will work on XOps, a CI/CD-native infrastructure for programmable value transfer in open-source workflows. This involves building a reusable execution engine that enables secure, policy-driven payouts triggered by repository events such as PR merges. The system will support multi-chain execution, configurable policies, and auditable workflows, reducing manual accounting overhead and enabling scalable, transparent contributor reward systems. Together, these systems aim to improve contribution quality, reduce maintainer workload, and introduce a standardized, automation-first approach to both collaboration and value distribution in open source.