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Context engineering—the practice of crafting effective instructions and inputs for AI models—has emerged as a persistent challenge in AI development, evolving from the "RAG is dead" moment of late 2024 when developers pursued massive context windows as a solution. While longer context windows have improved capabilities, context engineering remains fundamentally difficult because models have unique failure modes distinct from human communication, making it essential to understand how models are built and optimized rather than simply scaling context size.
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