AI at Work
AI Agents Fundamentals
shashank
Learn what makes an AI agent different from a chatbot like ChatGPT: an LLM that plans steps, calls tools, keeps memory and works inside guardrails. You cover tool calling and function calling, short-term and long-term memory, failure modes like loops and hallucinated results, and how to write a system prompt for your first agent. Tia plays your team lead and asks you to explain each part out loud. You finish by pitching an agent for a real task at work and answering questions about cost and risk.
5 sessions · 3h 25m
Free
This Goal only
Recommended
$20/mo
Subscribe, 10 hours a month
Your learning path
Skills you will learn
What an AI agent is
You will meet with your coach to explore the key differences between standard chat systems and active smart helpers. You will discuss the four core building blocks and look at how they solve real problems in a typical workplace.
Tools and actions
You will meet with an expert to learn how smart assistants connect to outside software to perform tasks. You will discuss how to set safety limits and decide when a human needs to step in.
Planning and memory
You will meet with your instructor to explore how digital helpers break big goals into smaller, manageable steps. You will discuss the difference between temporary and permanent recall and look at real examples of helpers getting confused.
Designing your first agent
You will meet with your coach to select a practical daily chore for your virtual assistant to handle. Together, you will outline what it needs to accomplish and draft its very first set of instructions.
Explaining agents at work
You will work with a guide to structure a simple presentation about how your automated assistant works and why it is valuable. You will map out how to explain the helper's benefits, calculate potential costs, and handle safety concerns.
How goals work
Four steps, one real shift.
AI at Work
AI Agents Fundamentals
shashank
Learn what makes an AI agent different from a chatbot like ChatGPT: an LLM that plans steps, calls tools, keeps memory and works inside guardrails. You cover tool calling and function calling, short-term and long-term memory, failure modes like loops and hallucinated results, and how to write a system prompt for your first agent. Tia plays your team lead and asks you to explain each part out loud. You finish by pitching an agent for a real task at work and answering questions about cost and risk.
5 sessions · 3h 25m
Free
This Goal only
Recommended
$20/mo
Subscribe, 10 hours a month