Agentic Workflows Design End-to-End AI Processes

What you'll learn
Explain what an agentic workflow is in plain business language and how it differs from a standalone AI prompt or simple automation
Identify the key components of any agentic workflow: goals, inputs, steps, decision points, and outputs
Distinguish between human steps, agent steps, and system steps, and assign each correctly when designing a real workflow
Break down a complex business process into chainable sub-tasks that an AI agent can execute autonomously or with human oversight
Apply three core agent control patterns - Plan-Execute-Verify, Audit & Self-Review, and Multi-View - to structure reliable workflows
Design agentic workflows for real business functions including customer support, sales, marketing, and internal operations
Evaluate a workflow using quality criteria - clarity, control, business value, and risk - before moving to technical implementation
Present a complete agentic workflow design to a technical team or manager using a clear, business-friendly visual format
Requirements
No technical or programming knowledge required. If you work in a business environment and want to design smarter AI-powered processes, this course is built for you.
Description
Using AI tools like ChatGPT is a good start. But knowing how to design complete, end-to-end automated workflows is what actually transforms how a business operates. This course teaches you exactly that - with no coding, no technical background, and no jargon.
You will learn what an agentic workflow is in plain business Language: how it differs from a simple prompt, what its core components are, and how to structure it so that the right tasks go to the right actor - whether that is an AI agent, a human, or an automated system.
From there, you will explore three powerful control patterns that make agent workflows reliable and auditable: Plan-Execute-Verify, Audit & Self-Review, and Multi-View. These patterns give you a practical toolkit for designing workflows that are not just functional, but safe and controllable.
The course covers real business functions in depth - customer support, sales and marketing, and internal operations - with concrete examples that show you how agentic design works in practice, not just in theory.
You will also learn how to evaluate and refine a workflow before taking it to implementation, using clear quality criteria around clarity, control, business value, and risk.
The course closes with a hands-on workshop where you design a real workflow from your own work, map it step by step, identify control points, and prepare it to present to a technical team or manager.
No code. No complexity. Just a clear, repeatable method for designing AI-powered business processes that actually work.
Who this course is for
Any professional who has started using AI tools like ChatGPT and wants to take the next step by designing complete automated workflows around them.
Entrepreneurs and business owners who want to systematically redesign their operations using AI agents to scale without proportionally increasing headcount.
Business students and recent graduates who want to stand out by learning how to design AI-powered workflows before entering the job market.
Junior professionals and analysts who want to go beyond using AI tools and start designing structured, end-to-end automated processes.
Operations and process managers who need to map, evaluate, and improve business workflows by integrating AI agents into existing processes.
Sales and marketing professionals who want to design automated workflows for account research, outreach, follow-up, and lead qualification.
Customer support team leaders looking to design agentic workflows that handle incoming tickets from start to resolution with minimal manual effort.
Project managers and business analysts who need to communicate workflow designs clearly to technical teams and stakeholders without coding.
Managers, directors, and executives who want a practical, non-technical framework for designing and evaluating AI-powered business processes.