Shipping Large Language Models (LLMs) into production requires designing systems that account for their inherent non-determinism and drift. Just as parents learn to manage the unpredictable behavior of toddlers, AI engineers must build systems that absorb variance rather than fight it. A key strategy involves using a small, consistently scored set of held-out inputs, akin to measuring a child's height against a doorframe, to detect when the LLM judge itself has changed its scoring behavior. AI
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IMPACT Engineers deploying LLMs must design for model drift and non-determinism, using calibration sets to monitor changes.
RANK_REASON The article is an opinion piece discussing the challenges of deploying LLMs in production, using analogies and personal experience rather than reporting on a specific event or release.