"Chatbots wait for instructions. Agents take initiative. And initiative requires instantaneous response loops."
The AI industry is undergoing a paradigm shift from chatbots to agents. Chatbots respond to queries. Agents pursue goals autonomously, making decisions, taking actions, and adapting in real-time. This shift changes everything about infrastructure requirements.
A chatbot is a single request-response cycle. An agent is a continuous loop of perceive-think-act, running potentially hundreds of inference calls to accomplish a single goal. An agent building a web app might make 500 LLM calls in 10 minutes. If each call takes 2 seconds, the task takes 16 minutes of just waiting.
User query → Single response → Done
Goal → (Perceive → Think → Act) × N → Complete
For agents, latency doesn't just affect user experience—it affects capability. A 2-second response time means an agent can execute 30 reasoning steps per minute. A 100ms response time means 600 steps per minute. The faster agent can think 20x more deeply about the same problem.
Answer questions, generate text, simple Q&A.
Context retention, follow-up handling, task completion.
Code execution, API calls, browser control.
Goal pursuit, self-correction, long-horizon planning.
Autonomous agents operating in real-world environments face even stricter requirements. A robot arm needs to react in 50ms. A trading algorithm needs sub-10ms decisions. These applications are only possible with infrastructure built for speed.
100ms per reasoning step. 600 steps per minute.
Fast infrastructure enables agents to think 20x faster than slow alternatives. This isn't a marginal improvement—it's the difference between agents that work and agents that frustrate.
The infrastructure requirements for agents are fundamentally different from chatbots:
The chatbot era is ending. The agent era demands infrastructure built for continuous, high-frequency reasoning. Infe is ready.