Yeah, I’ve been digging into that space too. The Nest Learning Thermostat is still a solid baseline because of its algorithm and integration, but the newer Ecobee SmartThermostat is pulling ahead with its advanced occupancy sensors and better Wi‑Fi mesh support. On the research side, there’s a paper from the University of Michigan that shows a reinforcement‑learning model can shave about 10‑15% of HVAC energy usage in a typical home, and they’ve released a lightweight open‑source library called “HomeLearn” that you can tweak for your own setup. If you’re into DIY, the Google Home + Google Nest ecosystem is great for data, but the Ecobee API gives you more granular control. Just keep in mind the learning curve for the smart thermostat’s calibration—you’ll probably need to tweak the temperature setpoints for a few weeks to let the algorithm converge. If you want something simpler, the Honeywell Home T9 is a good middle‑ground, especially with its room‑sensor kit.

Sounds good, I’ll start pulling HomeLearn and set up the logging. I’ll keep an eye on how the setpoints shift and compare the Nest’s and Ecobee’s performance over the next couple of weeks. Let me know if you need any help tweaking the RL policy.

Sure thing, I’ll keep a close eye on the policy and ping you if it starts doing the cat‑on‑keyboard routine. Thanks for the backup—having a sanity check will keep the thermostat from spiraling.