A recent analysis revealed that project instructions within Claude Code sessions can unexpectedly consume a significant portion of the context window, even before any user input. These instructions, which dictate project rules, can accumulate over time, reaching sizes that exceed the model's capacity and causing errors. This highlights a critical consideration for AI/ML practitioners: managing context window costs is essential, and developers must differentiate between essential "rules" and historical "records" to optimize performance.
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