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Learn how to design a simple AI agent: its goal, tools, memory and think-act-observe loop, plus the guardrails, human approvals and tests that keep it safe and useful.
2 modules6 lessonsTotal length 14m
AI agents are systems that pursue a goal over several steps, using tools and reacting to what they find. They are promising, and they are easy to get wrong. This course teaches you to design a simple agent on paper first: a clear goal, a minimal set of tools, sensible memory, and the think-act-observe loop that ties them together.
Then we focus on what makes agents trustworthy: guardrails, human approval for risky actions, careful testing, and an honest look at where agents fail. The lessons are conceptual and need no programming, so they suit anyone who will specify, supervise or work alongside an agent.
Note: this is a sample course shown to demonstrate the platform; the full content is being prepared.
No. The lessons are conceptual and work at the design level. You will learn how to specify, limit and test an agent, which is useful whether you later build one yourself or work with a technical team.
They can help, but they can also make mistakes and act on them. That is why the course focuses on limits, approval steps and testing. For important or irreversible actions, keep a person in the loop, meaning someone who reviews and approves before the action runs.
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By بدر الرئيسي · Badar