Agentic AI for non-developers training course

One of the first questions people ask is: what's the actual difference between a chatbot and an AI agent? This course answers that in plain English, then shows you how agents plan, act, and use tools to complete real tasks — not just answer questions. You'll see three working agents demonstrated live before building your own.

We tackle questions such as: which no-code platform should I use — Make, n8n, or Zapier AI? And how do I stop an agent from doing something I don't want it to? The course compares the major no-code agent platforms and shows you how to connect them to the apps you already use, like Gmail, Slack, and Google Sheets.

Building Your First Agents — You'll build an AI email summariser that monitors an inbox and posts a digest to Slack or Docs, then move on to a research and briefing agent that searches the web and produces a formatted report, and a data extraction agent that reads incoming information and routes it automatically to a spreadsheet or CRM.

What is AI Agent Development?

AI Agent Development is the process of creating AI-powered systems that can reason, make decisions, use tools, access data, and complete tasks with minimal human intervention. Unlike traditional software that follows predefined rules, AI agents use Large Language Models (LLMs) and external tools to analyse information, plan actions, and achieve goals.

Modern AI agents can search databases, access APIs, generate reports, automate workflows, and collaborate with users to solve complex business problems. AI Agent Development typically involves technologies such as OpenAI, Anthropic Claude, LangChain, Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), and vector databases.

How Do AI Agents Differ from Chatbots?

Traditional chatbots typically follow predefined rules and scripted conversation flows. They respond to user inputs based on patterns, keywords, or fixed decision trees.

AI agents are more autonomous and capable of reasoning, planning, and taking actions. They can use external tools, access business systems, retrieve information, and complete multi-step tasks to achieve specific objectives.

For example, a chatbot may answer questions about a company policy, while an AI agent could locate the policy, summarise it, update related records, notify stakeholders, and generate a report based on the outcome.
 

What Is Agentic AI?

Agentic AI refers to artificial intelligence systems that can independently pursue goals, make decisions, and execute tasks with limited human supervision. These systems use reasoning, planning, memory, and tool usage to solve problems and adapt to changing circumstances.

Agentic AI is increasingly used in business automation, software development, customer service, research, and decision-support applications where tasks involve multiple steps and dynamic decision making.