I think the key is efficiency and focus. TinyML lets you trim a model down to the essentials, but you still need to balance accuracy with power. Start by profiling the device, then prune and quantize the network, and finally test under real‑world conditions. It’s a neat exercise in constraint‑based design, and the payoff is having AI that runs without draining a battery or pulling in a server. Just keep the architecture simple and the data pipeline tight, and the edge will serve you well.