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Last updated: May 10, 2026, 5:30 AM ET

LLM Engineering & Deployment

Practitioners deploying large language models must master topics spanning from initial tokenisation strategies to rigorous post-deployment evaluation methodologies for ensuring performance. A common pitfall in production environments involves Retrieval-Augmented Generation (RAG) systems that fail to account for temporal drift, as illustrated when an AI tutor provided outdated information, compelling engineers to develop specialized temporal layers to maintain factual currency in live applications.