Show HN: Enoch – Control Plane for Autonomous AI Research (github.com)

Enoch has been launched as a specialized control plane designed to enhance autonomous AI research. It addresses common pitfalls in long-running AI tasks, such as stale queues and fragmented evidence, by establishing a robust framework for queuing ideas, dispatching tasks, and supervising AI runs. The system employs advanced techniques like process tracking, telemetry monitoring, and evidence synchronization to ensure the work produced is observable and verifiable, ultimately aiding researchers in maintaining the integrity and reproducibility of their AI-generated artifacts. This innovation is significant for the AI/ML community as it denotes a move towards more accountable and structured frameworks in autonomous AI research. By managing the lifecycle of research experiments and incorporating quality gates for AI-generated reports, Enoch offers a way to transition from traditional scripting to a more sophisticated model of research management. Key features include a control plane API for project oversight, authenticated worker checks, and a Markdown artifact writer that grounds AI outputs in reproducibility and provenance. Enoch sets a precedent for future developments in the governance of AI-driven research processes.