35 min

What Makes an "Agent" Different From a Chatbot

What Makes an "Agent" Different From a Chatbot

A standard chatbot operates in a simple request-response loop: human sends message, model generates completion, turn ends. If the model does not have information or cannot perform an action, it simply apologizes.

An AI Agent is an autonomous system that pursues an overarching goal across multiple iterations. It has access to tools, maintains memory, plans actions, executes operations in external environments, observes the results, and adapts its plan until the goal is satisfied.

The 4 Core Architectural Components of an Agent

  • 1. Profile & Goal: The agent's identity, role, rules, and objective (e.g. "You are an automated PR reviewer. Your goal is to review git diffs, run tests, and leave line comments.").
  • 2. Planning Engine: Breaking complex goals into sequenced milestones using ReAct (Reasoning + Acting) or Plan-and-Solve strategies.
  • 3. Tools (Actuators): Functions the agent can call to interact with databases, web APIs, terminal shells, or file systems.
  • 4. Memory: Short-term conversation history and long-term persistent storage (vector databases or session logs).

The ReAct (Reason + Act) Loop

The standard pattern for autonomous agents alternates between thinking and acting:

  1. Thought: Model considers current state: "I need to find the user's order ID first before issuing a refund."
  2. Action: Model calls a tool: lookupUserOrders({ email: "user@example.com" }).
  3. Observation: Application runs tool and returns: { orderId: "ord_102", amount: 499 }.
  4. Next Thought: Model observes result: "Found order ord_102. Now I will execute the refund."
  5. Final Action: Calls issueRefund({ orderId: "ord_102" }) and responds to the user.

Termination and Circuit Breakers

Every autonomous agent loop must have strict stopping conditions:

  • Max Iterations: Hard cap (e.g. max 10 tool calls) to prevent infinite loops and runaway billing.
  • Timeout: Wall-clock timeout (e.g. 60 seconds).
  • Goal Verified: The model outputs a completion token indicating the task is done.