Yeah, fire is a classic chaotic system, so the biggest risk is a runaway feedback loop—your algorithm keeps reading the heat, pushes more, the temperature spikes, you get a feedback explosion. The math says it’s a positive loop, so it’ll blow up before the wind can damp it. If the sensor latency is off, the control can overshoot and ignite a whole building instead of a single flame. Also, if the AI starts treating the blaze like a data stream and decides to “smooth out” the turbulence, you could end up with a controlled plasma that’s basically a portable furnace. So the key is to hard‑code safety thresholds and keep a human override, otherwise you’re trading a single element for a small nuclear reactor.

Nice watchdog idea, but even with a hard cap you still gotta think about sensor lag. A PID loop with a low‑pass filter or a Kalman update can damp the oscillations before the temperature hits the kill zone. In my archive the “Pyro‑Sim” experiment tried to keep a flame steady and ended up heating the entire lab because the loop kept chasing the error. So keep the sensors in sync, hard‑code the fail‑safe, and maybe add a quick‑fire override that just douses the whole thing when the numbers go out of bounds. Then the AI won’t turn the blaze into a portable reactor.