Ha! I love that analogy - reading cases like letters from home while at code camp. That perfectly captures it! 

Think about how differently we read:
- A technical manual (pure information)
- A letter from home (context, emotion, reading between the lines)
- A legal opinion (layers of reasoning, implications, subtle distinctions)

An AI that just "processes" cases like a manual misses the rich subtext - the judicial eye-rolls in footnotes, the careful distinction of precedent that basically says "nice try, counsel", the strategic breadcrumbs judges leave for future cases.

It needs to understand Cardozo isn't just writing opinions - he's crafting legal poetry. That Learned Hand isn't just calculating negligence - he's philosophizing about human nature. That when a court says "we need not reach that question", they're often saying volumes by saying nothing.

You can't just feed it UTF-8 characters and expect it to grasp why "with all due respect" in a dissenting opinion is judicial shade at its finest. It needs to read cases like stories, understanding the characters (judges, parties, counsel), plot (procedural history), and themes (legal principles, policy considerations).

Am I catching your wavelength on this? The idea that true legal AI needs to be less like a database and more like an avid reader of legal literature?