The O(N²) Trap: Why Your Agentic AI Workflow is Bankrupting Your Context Window

As AI agents perform multi-step workflows, they re-transmit every previous tool response, causing token costs to explode exponentially rather than linearly. Traditional text summarization fails on structured JSON data, necessitating a new 'Semantic Distillation' approach to handle schema redundancy and persistent entities. This shift is critical for enterprises looking to scale agentic workflows without hitting financial or technical performance ceilings.