Agentic AI Hype Hides a Critical State Management Infrastructure Gap

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A growing concern in AI development suggests that the popular 'agentic' trend is obscuring a fundamental infrastructure problem. Most agent frameworks treat agents as black boxes, relying on flat retrieval-augmented generation (RAG) implementations for state management. This approach leads to catastrophic context drift during long-term tasks, where agents lose coherent memory over time. Experts argue that the industry needs to adopt bi-temporal architectures at the storage layer to properly address this challenge.

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