AI users and knowledge workers
You use tools such as ChatGPT or Claude and want to understand what agent capabilities add, where their limits are, and how to work with them productively.
AI Agents & Workflows - The Practical Guide
Understand how modern AI agents and workflows really work—and learn to use or build them with visual tools, Python, and leading frameworks.
Course Overview
About This Course
“AI agent” has become a buzzword—but real agents and AI-powered workflows can unlock a huge range of practical opportunities. They can summarize documents, generate files, support customers, research topics, and connect to tools such as Slack.
This course cuts through the hype and gives you a clear, practical mental model of what agents are, how they work behind the scenes, and how they differ from AI workflows. You’ll explore them both as a user of tools such as Claude Cowork and ChatGPT-style agents and as a builder who wants to plan or create agents visually or in code.
This is not primarily a programming course. Visual n8n projects, step-by-step Python examples, and framework-based builds make the concepts concrete without tying them to one stack. By the end, you’ll understand the moving parts, know when a simple workflow is the better choice, and be ready to use agents productively or design your own.
What You'll Learn
Build a practical, transferable understanding of modern AI agents and workflows—from the agent loop and tool use to visual n8n builds, Python examples, safety controls, and agent frameworks.
Agents vs workflows
Understand what AI agents and AI workflows really are, how they differ, and when a predictable workflow is a better choice than an autonomous agent.
Master the agent anatomy
Explore models, harnesses, the agent loop, tools, instructions, context and sessions, skills, memory, sandboxes, and humans-in-the-loop as the core building blocks of modern agents.
Build visually and in code
Create practical AI workflows and agents with n8n, then follow step-by-step Python implementations to see how the same ideas translate into code.
Understand tool use
Learn how LLMs use tools, compare primitive and provider-native tool calling, and build agents that can summarize text, create PDFs, work with files, and run commands.
Control context and safety
Steer agents with system instructions, AGENTS.md, CLAUDE.md, and skills; manage context, sessions, compaction, and memory; and constrain risky actions with sandboxes and human approval.
Use frameworks and integrations
See how frameworks such as Eve and CrewAI accelerate agent development, survey options including Vercel AI SDK, LangGraph, and Pydantic AI, and expose task-specific agents through integrations such as Slack.
Ready to get started?
See enrollment optionsPrerequisites
No prior AI-agent or advanced AI knowledge is required.
You do not need to be a developer—the visual projects and code examples are explained step by step.
Basic programming knowledge is helpful if you want to follow and adapt the Python examples.
Who Is This Course For?
Automation and no-code builders
You want to design useful AI workflows and agents visually, connect them to real tools, and choose the right level of autonomy for each task.
Developers and technical builders
You want a stack-independent mental model plus practical Python and framework examples you can transfer to your preferred language, model, or platform.
Curriculum Overview
Start NowPreview the structure and pacing of this course before you begin.
Getting Started24m
- 01Welcome To The Course!1:22 min
- 02What Is An AI Agent?2:13 min
- 03General vs Task-specific Agents2:39 min
- 04Where Agents Run / Execute2:07 min
- 05AI Agent Harnesses, LLMs & Limitations3:25 min
- 06How Agents Use Tools5:15 min
- 07Understanding Session Context2:17 min
- 08Core AI Agent Building Blocks - Overview2:25 min
- 09AI Agents vs AI Workflows2:18 min
Using & Steering AI Agents26m
- 01Module Introduction0:57 min
- 02Three Main Ways For Controlling AI Agents You Should Know0:49 min
- 03Managing Agent Tools & The Environment3:42 min
- 04Choosing The Right Model1:17 min
- 05Understanding Developer-provided System Instructions1:39 min
- 06Providing Your Own Instructions & Understanding AGENTS.md / CLAUDE.md3:29 min
- 07Understanding Agent Skills8:28 min
- 08Understanding Agent Memory3:23 min
- 09Sometimes Important: Humans In The Loop2:57 min
Building Agents & Workflows - An Overview9m
- 01Module Introduction0:36 min
- 02Options For Building Agents & Workflows2:46 min
- 03WHO Builds It, WHERE Does It Run?3:36 min
- 04Options When Building WITH Code0:52 min
- 05Choosing Your Agent Building Blocks1:56 min
Building AI Workflows & Applications31m
- 01Module Introduction & Expectations1:35 min
- 02Building Workflows - The Basics1:20 min
- 03Workflows vs Agents2:39 min
- 04Building Visually with n8n - First Steps2:38 min
- 05Running a Demo n8n Project Locally1:41 min
- 06Exploring n8n & Its Workflow Builder6:44 min
- 07Exploring & Understanding a Realistic Workflow4:24 min
- 08Onwards To A Code-based Solution!3:15 min
- 09Exploring & Understanding A Code-based Workflow6:20 min
- 10Module Summary1:11 min
Building AI Workflows & Applications [LEGACY]2h 9m
- 01About This LEGACY Section0:00 min
- 02Module Introduction2:21 min
- 03No Code vs With Code2:07 min
- 04Building AI Apps & Using AI Programmatically4:12 min
- 05Proprietary vs Open (Local) LLMs5:51 min
- 06Using Open LLMs0:00 min
- 07Understanding Our Development Environment2:29 min
- 08Creating a New Python Project (using "uv")1:43 min
- 09OpenAI Setup & Pricing5:41 min
- 10Getting Started With A First Example Workflow2:44 min
- 11Preparing HTTP Requests For The OpenAI API8:40 min
- 12Choosing & Using a Model2:04 min
- 13Prompt Engineering4:35 min
- 14Extracting & Using the LLM Response4:50 min
- 15More on the OpenAI API & SDK0:00 min
- 16Code Deep Dives vs Provided Code Snippets0:00 min
- 17Use Those Docs!1:38 min
- 18Using The OpenAI Python SDK5:49 min
- 19Leveraging Few-Shot Prompting4:02 min
- 20Generating Prompts Dynamically With Dynamic Content2:12 min
- 21Building Multi-Step & Multi-Model Workflows6:47 min
- 22Workflows vs Agentic Systems1:34 min
- 23Using Locally Running Open Models via Ollama8:08 min
- 24Enforcing & Using Structured Outputs10:53 min
- 25More On JSON Schemas & Structured Outputs0:00 min
- 26Structured Outputs via SDK & Pydantic3:56 min
- 27Using Prompt Engineering To Control Output0:00 min
- 28Onwards To Another Example5:38 min
- 29Generating Images In a Workflow6:27 min
- 30Controlling Workflow Execution with Control Flow Adjustments2:45 min
- 31Control Flow In Action8:42 min
- 32Adding a "Human In The Loop"6:51 min
- 33Integrating External Services - Example: Slack6:21 min
- 34Important: Potential Problems & Security Risks0:00 min
Build AI Agents56m
- 01Module Introduction & Expectations1:55 min
- 02Setting Up & Starting the n8n Demo Project Server3:08 min
- 03Creating Agents Visually With n8n3:42 min
- 04Understanding Tools & The Agent Harness (in n8n)2:51 min
- 05Running The n8n Agent2:45 min
- 06Finding Key Agent Building Blocks in n8n0:59 min
- 07Onwards To Code-based Agents!3:53 min
- 08Defining Tools As Functions2:26 min
- 09Analyzing The Agent Loop3:23 min
- 10How The Agent Learns About Tools & Behaves Correctly6:03 min
- 11Using Provider-native Tooling To Make Things Easier5:14 min
- 12Onwards To A General Agent1:43 min
- 13Analyzing Tools, Instructions & Context Engineering For A General Agent6:19 min
- 14Demo: Using The General Agent3:15 min
- 15Analyzing An Example Sandbox Implementation2:44 min
- 16Adding A Human To The Agent Loop2:35 min
- 17How Agent Execution Is Constrained3:21 min
Building AI Agents [LEGACY]1h 16m
- 01About This LEGACY Section0:00 min
- 02Module Introduction1:36 min
- 03How LLMs (Do Not) Use Tools6:04 min
- 04Implementing Tool Use From Scratch11:24 min
- 05Using OpenAI's Function Calling Feature10:23 min
- 06Building a Multi-Tool Versatile Agent11:16 min
- 07Using Advanced AI Models0:00 min
- 08Building Reusable Elements With Classes7:53 min
- 09Getting Started with a Multi-Agent System7:14 min
- 10Extracting Website Content0:00 min
- 11Building & Connecting Specialized Agents10:24 min
- 12Universal vs Specialized Agents3:38 min
- 13Agent Memory: Short-Term & Long-Term5:21 min
- 14Wrap Up1:09 min
Build Agents With Frameworks - With "eve"29m
- 01Module Introduction0:52 min
- 02Library & Framework Options - An Overview0:58 min
- 03Libraries vs Frameworks2:33 min
- 04An Introduction To The "eve" Framework2:23 min
- 05Diving Into An "eve" Project2:53 min
- 06Configuring Tools For The "eve" Agent2:32 min
- 07Connecting The Agent To A Knowledge Base & Skills3:52 min
- 08Seeing The "eve" Agent In Action3:58 min
- 09Deep Dive: Connecting Slack As A Channel9:06 min
- 10More On Tunnels / cloudflared0:00 min
- 11Onwards To CrewAI0:34 min
And 2 more sections in the full course.
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