Supervising AI Agents: A Manager's Playbook
Your team's AI agents do real work now. Learn to delegate, set checkpoints, review output, fix mistakes, and decide what's worth keeping — no coding.
You did not apply for the job, but you have it: someone on your team turned on an AI agent — a research assistant that pulls reports, a triage bot that answers tickets, an automation that drafts and sends emails — and now its work shows up with your name attached to the outcome. When it’s right, it saves hours. When it’s confidently wrong, you’re the one who has to explain it.
Almost every course about AI agents teaches you to build one. This one teaches you to supervise one — the skill nobody is writing the manual for, even though far more people will manage an agent than ever code one. You already know how to manage: you give people a clear job, you set limits, you check the work, you decide who’s accountable. An AI agent needs exactly the same things. This course translates the management you already do into the six moves that keep an agent useful and safe: deciding what to delegate, putting a human at the right checkpoint, reviewing output for silent failure, running a calm incident response, setting a team policy, and measuring whether the agent is actually worth its keep.
No coding. No theory you can’t use on Monday. By Lesson 2 you’ll have a one-page Agent Supervision Plan for a real task on your team — and by the end, a complete system for keeping the agents you supervise honest. Lessons 1 and 2 are free; the full playbook and your certificate come with Pro.
What You'll Learn
- Explain what an AI agent is in plain terms and identify which agents and automations your team already runs
- Evaluate whether a task belongs to an agent, a human, or stays manual using reversibility, stakes, and how checkable the result is
- Design human-in-the-loop checkpoints and approval gates so an agent never takes a costly action unsupervised
- Evaluate agent output to separate what must be verified from what is safe to accept, and recognize silent failure
- Design an incident playbook that names the accountable human and includes a kill switch and escalation path
- Create a one-page team agent-use policy covering what data, what actions, and what is never automated
After This Course, You Can
What You'll Build
Course Syllabus
Who Is This For?
- Managers and team leads whose teams already use an AI agent, assistant, or automation
- Ops, marketing, finance, customer success, HR, and project or program leads — not engineers
- Anyone newly responsible for an AI tool's output without having built it
- Beginner-to-intermediate AI users who can use ChatGPT but have never 'managed' one
Frequently Asked Questions
Do I need to be technical or know how to build agents?
No. This course is for managers and team leads who oversee AI agents, not engineers who build them. You will not write code or configure anything technical. If you can describe a task on your team and decide who is responsible for it, you are ready.
How is this different from your AI agent security course?
'Don't Trust Your AI Agent' is the technical security course — Docker isolation, prompt injection, permission boundaries — for whoever runs the agent. This course is the management discipline: deciding what to delegate, where to put a human checkpoint, how to review output, who is accountable when it breaks, and whether the agent is worth keeping. They complement each other.
Which AI tools does this cover?
The supervision principles work with any agent — ChatGPT Tasks and agent mode, Claude, Microsoft Copilot agents, and automation platforms like Zapier, Make, and n8n. We reference real tools but teach skills that survive any tool change.
Will I get a certificate?
Yes. Complete all eight lessons and pass the quizzes to earn a verifiable certificate. Lessons 1 and 2 are free; Lessons 3 to 8 and the certificate require Pro.
