> Yet, it's all the most likely token and my brain hurts trying to understand how that can be.
You and everyone else. That's the great mystery of transformer architectures as applied to language.
To be clear though, they're only good at schematic capture, which is very much a textual representation. Most of the data basically boils down to netlists, which are a text based format mapping connections between abstract pins that only later map to physical copper. The actual schematic portion is for human consumption and LLMs don't need to produce those to be useful.
Where LLMs completely break down is the next step, PCB routing. That's an NP-complete research problem that's been ongoing for decades without much progress. I've had some fun playing with using LLMs to better specify DRC rules in Altium so that the "classical" algorithms are more usable, but at the end of the day their geometric intuition is nonexistent.
Where LLMs completely break down is the next step, PCB routing.
No. Take a look at https://www.eevblog.com/forum/eda/claude-code-for-pcb-design... . Fable did that by working directly on an EAGLE .brd file (well, "directly" by writing a Python program to do it, but still.)
They actually can route just fine. I used Sol to design and route mine from start to finish. Sent it to PCBWay and had a working prototype in a few weeks.
It was a pretty simple rp2040 based thing, similar to Adadfruits USB feather.I just gave it kicad and it wrote python to route it. The board was probably larger than it had to be, and two of the silkscreens were swapped, but it worked on the first go.
FWIW - Computer vision is also NP complete, but we do that all the time now.