The Ultimate Cheat Sheet for AI Agents: Mastering Workflow Automation with Claude MCP
Masocampus
AI writes on Slack and Notion for me? Work smarter with MCP, which goes beyond the limits of existing AI!
Beginner
Model Context Protocol, AI Agent, AI
We are launching a "Complete Reading Challenge" for the book "AI Agent Engineering," a practical guide to building proactive agent systems using LLMs. This book covers the core components of agents step-by-step, from tool selection to orchestration (designing planning and execution flows) and memory management. It also explores how to scale into multi-agent architectures where multiple agents collaborate by dividing roles. Furthermore, it expands your perspective from "how to build" to "how to operate" by covering essential production-level topics such as reliability, security, and governance. Do you want to design agent systems that go beyond simple automation to operate safely and transparently according to human intent? Join the book and the challenge to discover a concrete roadmap for turning your ideas into production-level systems!
1,594 learners
Level Intermediate
Course period Unlimited
Capable of completing an AI agent system design tailored to my tasks.
Capable of designing multi-agent collaboration structures
“I opened the package and the mug I ordered is broken!”
Is your chatbot simply connecting the customer to an agent at this point? A customer support AI agent can independently look up order history, verify photos of the damage, and then immediately approve and process a refund according to the regulations.
『AI Agent Engineering』 is a practical guide to building agent systems that work proactively using LLMs. It covers everything step-by-step, from tool selection and planning (orchestration) to memory management and multi-agent architectures where multiple agents collaborate by dividing roles. Furthermore, it expands your perspective from 'how to build' to 'how to operate' by including reliability, security, and governance, which are critical in production environments.
Do you want to design agent systems that go beyond simple automation to operate safely and transparently according to human intent? Check out the specific roadmap for connecting ideas to production-level systems through the book and challenge!
Who is this course right for?
A developer who wants to deploy a prototype as a live service
Engineers who want to increase the reliability and consistency of their agents
Those who want to learn how to build practical, real-world AI agents
Need to know before starting?
Experience in basic Python syntax and writing simple scripts
Basic concepts of LLM and RAG
All
13 lectures ∙ (5hr 21min)
All
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