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January 22, 2026
How We Cut Latency by 50% by Simplifying Our Agentic Architecture
When we first designed ChatGenie's agentic system for customer chat operations, we followed a principle that seemed intuitive: separate concerns into separate agents. Intent classification? That's one agent. Policy enforcement? Another agent. Response generation? Yet another.The result was a five-agent core chain that was clean, modular, and easy to reason about. It was also slow.Each agent in the chain required a separate LLM call. Five agents meant five round-trips to the model. In customer chat, where users expect near-instant responses, this cumulative latency was becoming a problem. Users would see typing indicators for seconds before receiving a response. Containment rates suffered as impatient users escalated to human agents.We needed to rethink our architecture.
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