In this case:

  LLMs know the USB Spec very well.

  LLMs know how to read raw packet dumps.

  LLMs know how to convert a packet dump to USB spec

  LLMs know how to write code to generate USB packets from the spec.

Basically, If you have a well-documented problem, the LLM is a shortcut to learning it yourself. LLMs fail when you have a novel or poorly documented problem. They also fail when you provide the LLM with terrible context or too much context.

After 5-6 consecutive approaches fail, I need a reason to think the next one might work out to stay motivated.

Claude will keep burning credits trying new approaches until something sticks. That's a huge advantage in a field where most of the things you try don't go anywhere.

Reverse engineering isn't so much hard as it is exhausting.

LLMs simply don't care about exhaustion.

It also has the benefit that it doesn't usually matter too much if it gets minor details wrong. It's definitely one of the areas - like hacking - where it's a) tedious and b) insensitive to mistakes where AI absolutely shines.