“Language models don’t apply to us because this is not a language problem,” Nesterenko explained. “If you ask it to actually create a blueprint, it has no training data for that. It has no context for that…” Instead, Quilter built what Nesterenko describes as a “game” where the AI agent makes sequential decisions — place this component here, route this trace there — and receives feedback based on whether the resulting design satisfies electromagnetic, thermal, and manufacturing constraints… The approach mirrors DeepMind’s progression with its Go-playing systems. This is kind of interesting and cool, and it’s not a hallucinating LLM. I’ve designed a couple of simple circuit boards, and running traces can be sort of zen, but it is tedious and would be maddening as a job. Definitely some hype levels coming from the company that give me pause, but it seems like an actual useful task for a machine learning algorithm.