You're Not Building an AI Agent. You're Building a Very Expensive Chatbot.

Short summary

The distinction between AI agents and chatbots is architectural, not semantic. Chatbots respond in closed loops with no persistent state or dynamic tool selection; agents maintain cross-session context, autonomously select APIs, plan sub-tasks, and recover from failures. Teams shipping chatbot architectures as "agents" waste 3–6 months reworking when production edge cases expose prompt-only reasoning. Use agents for order processing, multi-system workflows, and autonomous decision-making at scale; use chatbots for FAQ, support triage, and summarization. Anthropic's late-2024 MCP release made agentic architecture practically implementable.

• •Agents autonomously select tools, plan multi-step tasks, and maintain state across sessions; chatbots operate in closed loops with hardwired flows.
• •Wrong architecture costs 3–6 months of production rework when edge cases expose prompt-only reasoning without genuine planning.
• •Use agents for multi-system workflows requiring autonomous recovery; use chatbots for FAQ, support triage, and static-path tasks.

Generated with AI, which can make mistakes.