Yujian Tang

Introduction to Agentic Systems

Stanford University

Amazon

LinkedIn

Author, Cracking Gen AI
Prev: Stanford, Amazon

Agents vs Workflows

Single agent systems, router based systems, orchestrator systems, and "octopus" systems.

Types of Agentic Systems

How autonomous agents differ from human in the loop systems and when to use either.

Autonomous vs Human in the Loop

Build AI Agents in 4 weeks with proven frameworks that add 6-8+ fig to a business bottom line, no coding required

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Agentic practitioner, speaker, educator

Sara Davison

Co-Founder AI Build Lab 

Agentic Practitioner, speaker, educator

Tyler Fisk

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‼️ 2026Curriculum! 👉Graduate with every prompt, agent &amp; workflow to replicate the system 👉Build the Skillset That Will Define the Next Era of WorkWe are in the single biggest shift of how work gets done in our lifetime. AI agents are changing how work gets done &amp; where you are 6 months from now depends on what you learn today:<ul><li>Where do I actually start? (sequencing: what's first vs next)</li><li>How do agents actually work together? (the orchestration piece that makes it work)</li><li>How do I know it's working? (evidence, not vibes)</li><li>How do I scale it / hand it off / sell it? (the actual point)</li></ul>What's missing is a clear, proven path - a step-by-step guide to build AI agent workflows you can demo, deploy, or sell. From real on-the-ground practitioners.📈 82% of leaders plan to scale their teams with AI agents 📉 47% say they can't find people who know how (MS 2025)WEF: work is shifting from execution to orchestration. The biggest demand is agentic workflow design: managing teams of agents.Tl;dr: almost no one can do this yet.This is the proven roadmap that's worked for 1,600+ graduates 👉 GRADUATE WITH A COMPLETE AGENTIC SYSTEM: EVERY PROMPT, WORKFLOW, STEP BY STEP INSTRUCTION TO USE BEYOND THE COURSE.

Build An AI Agent Team In 6 Weeks:Demo, Sell, Deploy. No Code, End To End System

How Do I Actually Orchestrate Agents? → Think Like an Architect, Not an AI User

How Do I Get Quality Results With Multiple Agents? → Master Context Engineering

How Do I Know What To Build Before I Start? The Requirements Build It For You

How Do I Make Agents Specialists? → Match Your Agents To The Right Knowledge

How Do Agent Teams Work Together? Learn Multi-Agent Orchestration

How Do I Ensure Consistency & Reliability At Scale? Learn Evaluations & HITL

Non tech-professionals wanting to become the 1% AI leaders &amp; operators in the workplace

Consultants and agencies looking to offer AI consulting and implementation services

Entrepreneurs &amp; business owners looking to build businesses as scalable, growth machines

Become an Agentic AI Engineer by building real-world, production-ready AI agents that autonomously reason and execute complex tasks.

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Professor & AI Expert (540K+ Students)

Microsoft

General Motors

Samsung

HSBC

Dr. Ryan Ahmed

Professor, AI expert, & YouTuber who has taught 540,000+ learners worldwide.

Director of Engineering @Launchpad.AI

Nike

Levi's

Mr. Cooper

Launchpad

Kukesh Kodess

Director of Engineering with 7+ years building cutting-edge AI/ML systems

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⭐"Join the instructor trusted by 540K+ students with 40K+ five-star reviews and 50M+ minutes of AI training watched worldwide."Agentic AI Engineering is 2026's most in-demand skill.Software is shifting from static systems to AI-native architectures, where autonomous agents reason, plan, and execute complex work.The problem: Most developers are stuck building API wrappers, and they lack the depth to manage state, memory, &amp; multi-agent coordination in real production systems.The Solution: This bootcamp is your bridge to elite Agentic AI engineering. We move beyond the basics to architect robust agent fleets in which specialized agents collaborate autonomously in production.What makes this course unique?<ul><li>Production-Grade Architecture: Engineer real systems using LangGraph, CrewAI, &amp; AutoGen.</li><li>Automate Agent Workflow Creation: Use Claude Code &amp; Codex to generate, refactor, and evolve agent workflows.</li><li>Enterprise Reliability: Design for guardrails, persistent memory, observability, &amp; human-in-the-loop safety. </li></ul><h3>Real-world Capstone Project</h3>Design &amp; deploy a production-grade, portfolio-ready agentic AI system for real-world use, demonstrating senior-level Agentic AI engineering skills.

Master Agentic AI Engineering & Architect Production-Grade Autonomous Systems

Architect, build & deploy production-grade agentic AI systems end-to-end

Orchestrate Autonomous Multi-Agent Teams

Master Tool Use & The Model Context Protocol (MCP)

Automate Workflows with AI Coding Assistants

Engineer Context-Aware Agents with Retrieval Augmented Generation (RAG)

Deploy, Monitor & Benchmark for Enterprise

Software Engineers &amp; Developers wanting to master state-of-the-art Agentic AI frameworks and build autonomous, production-grade AI agents.

Technical Founders &amp; CTOs who want to architect scalable, fault-tolerant autonomous systems that serve as your product's core engine.

Modern ML &amp; Data Science Practitioners who want to evolve from static models to dynamic Agentic AI workflows that reason, plan, &amp; execute.

This is a project-based course. In 6 weeks, you will learn a repeatable framework and build your multi-agent AI application ready to launch.

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Cognizant BR Turma 1

Pearson SME, O'Reilly teacher, ex-Cisco

Cisco

Claro Brasil

Pearson

O'Reilly

Carmelo Iaria

Agentic Architect, Pearson SME, Startup Founder, 30 years of global experience

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What alumni say<ul><li>Matt (Founder, SAVANT-AI): "Five stars for course logic, course structure, and course value."</li><li>Alexa (Lead UX Designer, Caseware): "I can already see how to bring it into my work."</li><li>Satyan (Group PM, AT&amp;T): "The concepts taught here make the difference between building a product that works and one that doesn't."</li></ul>Why this course mattersIn 2026, engineering value is shifting from task execution to orchestration and systems thinking. Anthropic’s research shows that being a software engineer increasingly means orchestrating agents that write code, evaluating their output, and ensuring the system solves the right problems—not just writing more code yourself. The gap between early adopters and everyone else is widening fast.You will leave with a production-ready capstone architecture, reusable templates, and a delivery playbook you can apply immediately.NOTE: <a target="_blank" rel="noopener noreferrer nofollow" href="https://maven.com/carmelo-iaria/agentic-architect?promoCode=EARLYBIRD">Promo Code "EARLYBIRD" 20% discount expires on May 17th</a>NOTE: Those enrolled to this course can join my <a target="_blank" rel="noopener noreferrer nofollow" href="https://maven.com/carmelo-iaria/agentic-architect-workshop">Workshop </a>for free

Software development is moving from writing code to orchestrating agents.

Define a solid foundation with clear research and project scope

Architect your complete multiagent solution — from roles to workflows

Design and build a production-ready Agentic AI Application

Define and configure your multiagent crew — from backend logic to integrations

Add enterprise-level quality: integrate human feedback, observability, and QA

Deploy, validate, and present your final Capstone solution with confidence

Own delivery outcomes in tech/product/design/consulting. Read-level Python is helpful; pair with a technical teammate if needed.

Experience & Background

Comfort with Git/GitHub, API basics, and AWS (or similar). If rusty, budget extra setup time in Weeks 1-2.

APIs & Cloud Platforms

Agentic IDE (Cursor, Claude Code, GitHub Copilot), OpenAI API credits (~$20+), GitHub account, AWS access (recommended)

Required Tools & Access

Technical Builders (software, AI/ML, data, platform) moving from demos to reliable delivery..

Product and Business Owners (PMs, founders, consultants) responsible for outcomes, priorities, and execution quality.

UX and Experience Leaders (UX, service design, research) shaping human-agent workflows, trust, and adoption.

Learn how to define task autonomy, decision thresholds, guardrails, and human override in agent-enabled systems.

BA-Cube Founder | LinkedIn Instructor

Angela Wick

25+ years practicing, shaping, and teaching analysis, product, and requirements.

Agentic AI Skills for Business Analysts

Agentic AI changes the game because AI can autonomously act. It can initiate actions, make decisions, and operate across workflows with increasing autonomy. Risk escalates, and so does opportunity! Without deliberate, disciplined, and structured analysis, agents act on incomplete logic, unclear boundaries, and undefined escalation paths. That is where exposure multiplies. This course matters because Business Analysts are uniquely positioned to define autonomy limits, decision thresholds, guardrails, and monitoring structures before agents scale. It equips you to design control into autonomy, so AI-driven systems remain accountable, coherent, and aligned with business intent rather than becoming fragile at scale.AI is moving beyond assistance. Agents can:<ul><li>Initiate actions on their own</li><li>Make decisions</li><li>Trigger workflows</li><li>Operate continuously</li></ul>This changes the role of Business Analysis.When agents act without clearly defined:<ul><li>Goals</li><li>Boundaries</li><li>Escalation rules</li><li>Monitoring thresholds</li></ul>Organizations lose control.This course teaches how to design and govern agent behavior responsibly.