Most developers using Claude Code on Java projects default to one model and never look back — until the bill arrives, or the architectural suggestion turns out to be confidently wrong. Matching the right model to the right task is one of the highest-leverage habits you can build as an AI-assisted Java developer.

A 1M token context window sounds like a license to load everything into Claude Code and let it figure things out. The research — and a few painful debugging sessions — say otherwise. Past roughly 100k tokens, reasoning quietly degrades while the model keeps sounding confident. Here's how to work with the attention budget instead of against it.