Show HN: A deterministic governance harness for agentic development loops (github.com)

A new governance system, PPG (Platform Planning Gateway), has been introduced to enhance the deterministic control of AI coding loops, specifically with LLMs like Claude Code and GitHub Copilot. This framework consolidates governance by integrating hooks, a centralized validation server, and machine-level controls to ensure that AI-generated outputs adhere strictly to specified rules—eliminating the need for an additional LLM to verify the first one's decisions. This is significant for the AI/ML community as it addresses the inherent unpredictability of LLMs, which can lead to conflicting outputs without a reliable means of enforcement. PPG's architecture utilizes a robust validation process that provides deterministic outcomes, meaning that all edits and outputs must conform to pre-established policies. Each iteration of AI activity is scrutinized through a capability ticket system, ensuring that no action can bypass the policy controls. The validation occurs at both planning and artifact stages, enhancing accountability and reliability in AI outputs. By transforming rule adherence into a structured governance mechanism, PPG aims to eliminate conflicts and improve the trustworthiness of AI systems in real-world applications, marking a significant advancement in the development of responsible AI practices.