Claude Architect · Lesson

What Makes a System Agentic

Autonomy, tool use and iterative decision-making.

What Is an Agentic System?

A normal program follows a fixed script. An agentic system is different: you give it a goal, and the model decides the steps to reach it.

Three properties make a system agentic:

Autonomy — the model chooses what to do next, not your code.
Tool use — it can act on the world (search, read files, call APIs).
Iteration — it loops: act, observe the result, decide again.

In the Claude Certified Architect track, these three ideas sit at the center of Agent Architecture & Orchestration, the largest exam domain (27%).

The Model Keeps No State

Each call to the Claude API is stateless. The model remembers nothing between turns. You must send the full message history every turn.

A request carries these fields:

model — which Claude model to use.
max_tokens — the output cap.
system — instructions and role.
messages — the entire conversation so far.
tools — what the model is allowed to call.

Because there is no hidden memory, you own the loop that grows messages over time. That loop is what turns a single answer into agentic behavior.

import anthropic

client = anthropic.Anthropic()

messages = [{"role": "user", "content": "Check today's open orders."}]

response = client.messages.create(
    model="claude-opus-4-8",
    max_tokens=1024,
    system="You are an operations assistant.",
    messages=messages,  # the FULL history, every single turn
    tools=TOOLS,
)

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