AI Agent Course

AI Agent Course: Build Autonomous Agents People Actually Pay For

An eight-week AI agent course for builders who are tired of demos. You will ship four working autonomous agents, price them as client projects, and join a community of 500+ students who have done the same. Taught live by Harry Lee and Frank Yao.

By Harry Lee, founder of Visionary Academy. Reviewed by Frank Yao. Last updated April 2026.

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40%

of enterprise apps will run AI agents by EOY 2026 (Gartner)

+1,445%

increase in multi-agent inquiries Q1 2024 to Q2 2025 (Gartner)

500+

students in the Skool community

live calls every week with real mentors

What You Are Actually Building

An AI agent is a worker, not a chat window.

A chatbot answers the question in front of it and forgets the conversation an hour later. An agent is different. You give it a goal, a set of tools, and a budget, and it keeps working until the job is done or it hits a limit you set. It reads email. It writes to your CRM. It pulls data from Stripe, summarizes it, and posts the result in Slack. If one step fails, it tries a different route.

This is the skill Gartner calls the defining capability of the next two years. In their 2025 research, 40% of enterprise applications are expected to include task-specific AI agents by the end of 2026 — up from fewer than 5% the year before. Client inquiries about multi-agent systems jumped 1,445% in a single year. That is not hype. That is a backlog of real projects without enough people to build them.

This AI agent course closes the gap between watching a demo and shipping a system a paying client will trust with their money.

Agents you will build in the course

→A research agent that scrapes competitor websites, extracts pricing, and drops a weekly brief in Notion
→A sales agent that reads inbound leads, qualifies them against your ICP, and routes the hot ones to a human
→A finance agent that reconciles Stripe and QuickBooks and flags mismatches before close
→A content agent that watches a list of RSS feeds, drafts original summaries, and queues them for review
→A supervisor agent that manages the four above and reports to you once a day

The Case For Learning Now

The job market has already priced this in.

Stanford's 2025 AI Index Report tracked AI-related job postings across the United States and found they were growing faster than any other technical category, with agent-specific roles — “AI engineer,” “agent developer,” “applied AI engineer” — leading the pack. McKinsey's Economic Potential of Generative AI report estimates that generative AI could add $2.6 trillion to $4.4 trillion in annual value across the global economy, with autonomous agents driving a large share of that number.

Anthropic shipped Claude 3.5 Sonnet with computer-use capabilities in late 2024 and rolled tool use into the core API the same year. OpenAI followed with the Assistants API and then agentic function calling. The pattern is clear: the frontier labs are no longer shipping models, they are shipping agents. That means every company with a backlog of internal processes is now a potential customer for someone who can build one.

At the same time, the supply of trained people is thin. A single Udemy course on AI agents has more than 231,000 enrolled students, but only a fraction finish, and fewer still can ship a production system with monitoring, retries, and a contract behind it. The ceiling for a competent agent builder in 2026 is not a job. It is a practice. Consultants who understand tool use, planning loops, and evals are charging $5,000 to $20,000 per project and booking out months in advance.

This course is built for that market. You do not get a certificate. You get a portfolio, a price list, and a peer group.

The Stack

Tools we teach because clients pay for them.

No toy projects. Every tool in the course is one you can install on a client's account and hand off with a straight face.

Claude API

Anthropic's model is the reasoning core. You will use it for planning, tool selection, and structured output.

N8N

Open-source workflow automation. Self-hosted or cloud. Connects to 400+ apps.

Make

Visual automation platform clients already pay for. Fastest way to deliver a billable agent project.

OpenAI SDK

For projects that need GPT-class models or vision. You will learn when to reach for each provider.

Vector databases

Pinecone, pgvector, or Chroma for memory and retrieval.

8-Week Curriculum

From the perceive-decide-act loop to a signed client contract.

Agent Foundations

Understand the perceive-decide-act loop. Learn when an agent is the right tool and when a plain script will do. Set up Claude API, environment variables, and your first function-calling example.

Tool Use and Function Calling

Give your agent hands. Write tool definitions, handle retries, parse structured output, and debug the most common failure modes — wrong argument types, hallucinated tool names, silent errors.

Memory and Planning

Short-term context, long-term vector memory, and plan-then-execute patterns. When to use ReAct, when to use a planner-worker split, and how to keep token costs under control.

N8N Workflow Agents

Build agents that run on a schedule or trigger. Connect Gmail, Slack, Notion, Airtable, and webhook endpoints. Ship your first unattended agent that runs every hour without you watching.

Make Integrations for Client Work

The tool clients already trust. Visual scenario building, error handlers, data stores, and how to package a Make blueprint you can resell to small businesses.

Multi-Agent Systems

When one agent is not enough. Supervisor-worker patterns, agent-to-agent messaging, and the 1,445% spike in multi-agent system inquiries Gartner reported between Q1 2024 and Q2 2025.

Testing, Evals, and Guardrails

The difference between a demo and a product. Write evals, set spend caps, add human-in-the-loop checkpoints, and log every tool call for audit.

Packaging and Selling

Price a client project, write a scope, deliver, and get paid. The full sales motion — from cold outreach to signed contract — taught by people who have closed real deals.

Who This Is For

Five people walk out of every cohort with a new income stream.

The course is open to anyone, but it was designed for the five profiles below. If you see yourself on this list, the work is going to feel like it was written for you.

Developers who want to move past chatbots into real automation
Marketers and operators who keep hitting the ceiling of Zapier
Consultants adding an AI service line to an existing agency
Product managers who need to ship an agent feature this quarter
Side hustlers looking for a skill that pays $5,000 to $20,000 per project

How the Live Calls Work

Two calls a week. Real mentors. No Discord ghost town.

One call is a build session. A mentor picks a project from the cohort and walks through the code live, including the parts that did not work the first time. The second call is office hours. You bring your error message, we fix it together.

Calls are recorded for anyone in a different time zone. Singapore, London, Toronto, Los Angeles — we have students joining from all of them every week.

The community lives on Skool. 500+ members, weekly wins thread, job board, and a running list of client leads that alumni share when they are full.

Who Teaches This

Harry Lee and Frank Yao.

Harry Lee runs the Visionary Academy community on Skool and built the first version of this curriculum in 2024. He has shipped agent systems for marketing agencies, e-commerce operators, and a handful of SaaS companies. His YouTube channel has tens of thousands of developers following weekly agent tutorials.

Frank Yao is the second founder and the one who teaches the business half of the course. His background is sales, marketing, and agency operations. He writes the contract templates, the pricing sheets, and the onboarding scripts the students use to land their first clients. You can see his public work at frankyao.com.

Between them, they have trained more than 500 students across six cohorts. Cohort 6 finished with a 92% completion rate, which is many multiples higher than the average online course. The reason is simple: two live calls a week, small groups, and a curriculum that ends with a finished product, not a quiz.

Questions we get every week

Frequently asked questions.

What is an AI agent, in plain English?

An AI agent is a program that uses a language model to decide what to do next. It can read data, call tools, wait for results, and keep going until the task is done. A chatbot answers one question. An agent handles a whole job — researching a lead, drafting an email, sending it, logging the reply, and following up three days later if nothing comes back.

Is this course for beginners or experienced developers?

Both, but with different paths. If you have never written a line of code, you will start with N8N and Make and build working agents in week one. If you are a developer, you will move into the Claude SDK, tool use, and multi-agent patterns by week two. Every module has a no-code track and a code track. You pick.

How is this different from the free AI agent tutorials on YouTube?

YouTube shows you a demo. A demo is not a business. This course walks you through the full motion — building an agent that survives real traffic, pricing the project, writing the contract, onboarding the client, and collecting payment. You also get two live calls every week with mentors who have shipped agents into production. YouTube cannot answer your specific question at 9pm on a Tuesday. We can.

How long will it take to finish?

Eight weeks if you follow the schedule. Ten to fifteen hours per week, including the two live calls. Most students hold down a full-time job while they go through it. Lifetime access to the community and recordings means you can also move at your own pace.

What will I have at the end?

A portfolio of at least four working agents, a signed pricing sheet, a proposal template, and a Skool community of 500+ alumni to ask for referrals and code review. Many graduates land their first $2,000 to $5,000 client project before the program ends.

Which language model does the course use?

Claude is the default because its tool use and long context handling are the best available today. You will also use OpenAI's GPT-4 class models for comparison, and we cover when to pick one over the other. The patterns you learn apply to any frontier model.

Do I need a computer science degree?

No. Half of our students came from marketing, sales, teaching, or finance. The non-technical track uses N8N and Make, which are visual. The technical track uses Python and the Claude SDK. Pick the one that fits you, or do both.

How big is the market for AI agents right now?

Gartner forecasts that 40% of enterprise applications will have task-specific AI agents by the end of 2026, up from less than 5% in 2025. The same research group reported a 1,445% increase in client inquiries about multi-agent systems between Q1 2024 and Q2 2025. Stanford's 2025 AI Index shows AI job postings grew faster than any other technical category. The demand is real and early.

Related Training

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We cap each cohort so the live calls stay small. Claim your seat to get the onboarding email and the first module.

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