Deploy edge models sparingly
Firmware AI is powerful but expensive to change. Only push models into controllers when latency, autonomy, or safety demand on-device inference. Everything else can run upstream where upgrades are safer and cheaper.
Engineer rollback and observability first
Embedded inference must satisfy data residency, logging, and rollback needs before it ships. Plan control loops, telemetry, and kill switches so operators can observe and reverse changes without bricking devices or risking safety.
Guard cognition-influencing behavior
Human-machine synergy cuts both ways. Treat firmware that influences operator cognition like a safety system: test rigorously, monitor continuously, and keep manual overrides. The cost of bad edge intelligence is measured in physical risk.
sys3(a)i POV: We approach critical systems work by stress-testing architectures, integrating observability and governance from day one, and designing sovereign or edge footprints where independence and continuity matter most.