In 2026, the hottest buzzword in the tech world is undoubtedly "On-Device AI."

From Apple Intelligence to the flood of AI PCs and AI smartphones hitting the market, the entire software industry is racing to cram large language models (LLMs) and vision models—previously running in the cloud—into portable devices weighing just a few dozen grams.

As a software engineer, you might have fine-tuned models on a workstation with a dedicated GPU or run flawless inference in the cloud. But when your team moves to mass production and deploys the model onto a custom PCBA (Printed Circuit Board Assembly) you designed yourselves, the nightmare begins.

The device gets burning hot, the battery drains in minutes, inference speed turns from silky smooth into a slideshow, and the system crashes and reboots repeatedly.

I work at AnyPCBA, a manufacturer specializing in small-to-medium volume PCB and PCBA production. I frequently see software AI teams hit the wall of physical reality.…