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intermediate15 min15 min read

Introduction to Agentic Workflows: From Chatbots to Agents

Learn how to build semi-autonomous systems that handle multi-step business tasks.

What you will learn

  • Define what an AI agent is and how it differs from a chatbot
  • Understand the Perceive-Plan-Act-Reflect loop
  • Design a multi-step agentic workflow using n8n or Python
  • Identify business processes ripe for agentic automation

In 2026, the value of AI has shifted from "talking" to "doing." Agentic workflows are systems designed to carry out a sequence of actions with minimal human intervention.

What is an AI Agent?

Unlike a standard chatbot which responds to a single prompt, an agent follows a loop:

  1. Perceive: Understand the goal and the available tools.
  2. Plan: Break the goal into smaller, logical steps.
  3. Act: Execute those steps using external tools (Email, CRM, Web Search).
  4. Reflect: Check the output and adjust if the goal hasn't been met.

The Power of Iterative Thinking

Standard workflows are linear (Step A -> Step B). Agentic workflows are iterative. If an agent drafts an email and realizes it's missing a key detail, it can "search" for that detail and rewrite the draft autonomously.

Real-World Workflow: The Research & Outreach Agent

The Goal: Find 10 potential partners in a specific industry and draft personalized intro emails.

How it works (using n8n or Python):

  1. Search Tool: The agent searches Google for companies matching the criteria.
  2. Scraper Tool: It visits the company websites to find their "About" section and mission.
  3. LinkedIn Tool: It identifies a key contact (e.g., Head of Marketing).
  4. LLM Brain: It synthesizes the company's mission and the contact's role into a tailored pitch.
  5. Output: It saves the personalized drafts into a shared spreadsheet for your final approval.
AgentsWorkflowsn8nCopilot
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