A few months ago I set out to answer a simple question: can I build a scientific framework for deciding when to sell my Google RSUs instead of making decisions based on gut feeling? The answer turned out to be "sort of, but the process taught me far more than the answer did." This post covers the full arc — hardware choices, architecture decisions, the bugs that kept predictions stuck at 0.00%, and finally a working system running at 2.5ms on the Edge TPU. I also added a second model — a direction classifier that predicts whether price will go up or down — to complement the original price regression model. The dual-model results are instructive and sometimes humbling. The Hardware Stack I started with what I had: a Google Coral Dev Board sitting on my shelf. The Coral has an Edge TPU coprocessor connected to the CPU via PCIe — not the USB Accelerator version, the on-chip variant. It's discontinued hardware, but it's genuinely capable for what I needed.…