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Enterprise AI agents depend on messy documents, making reliability a challenge. Context engineering treats knowledge as app-specific, not shared. Different teams process the same documents, creating inconsistent embeddings and indexes. This fragmentation breaks down as more AI applications and agents deploy.
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