A technical retrospective details a production incident where an AI agent began ignoring its system prompt after approximately ten conversational turns. The issue was not due to model quality but rather a mismatch in token counting between the evaluation harness and the actual API tokenizer. The evaluation incorrectly estimated the prompt size, leading to silent truncation of older messages, including the system prompt, by the free model's smaller context window. The fix involved standardizing on a single tokenizer for evaluation and production, and implementing a context budget guard to reserve space for completions and manage message truncation more effectively. AI
IMPACT Highlights the critical importance of accurate token counting and context window management for reliable AI agent deployment.
RANK_REASON Article details a specific technical issue and its resolution in an AI application, not a new model release or major industry event.
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