I built this with my son James: a real 367 sq ft greenhouse in Longmont, Colorado where an AI planning loop can suggest climate adjustments, but cannot directly control the hardware. The safety boundary is the point. The AI does not flip relays. The system collects greenhouse telemetry like temperature, humidity/VPD behavior, equipment state, resource use, weather context, and scorecards. The AI planner looks at recent conditions, plant target bands, known equipment limits, and forecasts. It can then propose bounded “tunables" for firmware enforcement. Every proposal goes through a dispatcher that validates schema, checks bounds, clamps invalid values, and rejects proposals outside the safety envelope. The ESP32 firmware owns the actual relay loop for fans, misters/fogger, and heat. The reason we built it this way is practical: plants need stable climate, but every correction costs water, electricity, or gas. The question is whether AI can help optimize that tradeoff without becoming the safety-critical controller. Project: https://verdify.ai/ Safety architecture: https://verdify.ai/reference/safety Evidence: https://verdify.ai/evidence GitHub: https://github.com/jrvallery/verdify Video overview: https://www.youtube.com/watch?v=deMuvwIcYLk submitted by /u/jvallery
Originally posted by u/jvallery on r/ArtificialInteligence