Udemy

Agile Business Analysis: Getting / Writing Lean Requirements

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  • 25,933 Students
  • Updated 3/2026
4.5
(6,347 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
5 Hour(s) 38 Minute(s)
Language
English
Taught by
Tom and Angela Hathaway
Rating
4.5
(6,347 Ratings)

Course Overview

Agile Business Analysis: Getting / Writing Lean Requirements

Meeting the Agile, Lean, and DevOps Requirements Challenge — In the AI Era (with ChatGPT)

Let's be honest: if you are using AI to write requirements or user stories and nobody is checking them, you are not moving faster. You are just generating technical debt at scale.

Because speed without precision is just faster failure. Agile and Lean methodologies have helped organizations deliver more quickly, but the one problem that has never gone away is getting the "what" right. Clearly. Quickly. Without waste. Generative AI does not solve that problem. It intensifies it. When an AI tool confidently produces a user story that sounds complete but is ambiguous, untestable, or disconnected from actual stakeholder intent, the cost of that error travels straight into your sprint.

This course is built on that reality. It teaches the core skills of eliciting, expressing, and validating requirements in a Lean and Agile context, and at every step shows you how to put generative AI to work as your analyst's assistant. Not as a substitute for your judgment. As a force multiplier on expertise you already have or acquire here.

What Will I Learn?

The course moves through three interconnected areas of practice.

Requirements in a Lean and Agile context. You will learn what requirements actually look like when Agile, Lean, and DevOps are driving the delivery model, how to express stakeholder needs as features, user stories, and lean requirement statements, and how to use the Cynefin framework to analyze and prioritize work when complexity and uncertainty are high. AI tools will help you accelerate the analysis, but only if you give them the right context to work with.

Elicitation and expression. You will learn how to extract requirements from stakeholders, even when those stakeholders are unclear or contradicting each other. You will use a question file to track progress, apply a range of elicitation techniques suited to Agile environments, and see a live demonstration of moving from raw stakeholder input to usable drafts with AI assistance, without skipping the critical thinking that makes those drafts trustworthy.

Validation and quality control. You will learn how to eliminate ambiguity and subjectivity before they become rework, how to write test scenarios using Given-When-Then, and how to discover and document Non-Functional Requirements that real-world systems cannot afford to ignore. The validation standard does not change based on whether a requirement came from a stakeholder conversation or an AI tool.

Running through all of it are the two disciplines that define effective AI-assisted requirements work in any methodology: context engineering, which is about giving your AI tools the business goals, constraints, definitions, and edge cases they need to produce useful output rather than generic output, and output validation, which is about knowing what to look for when the AI delivers something that sounds right but is not.

How Will That Help Me?

The analyst who understands Lean and Agile requirements deeply, who can direct an AI tool with precision and catch its errors before they reach a developer, is not a person any delivery team wants to work without. This course is designed to make you that person.

Whether you are a newer BA building confidence in Agile environments, an experienced practitioner modernizing your workflow, or a product owner who needs to write better user stories without spending half your week doing it, this course gives you a practical toolkit that works today and holds up as AI tools continue to evolve.

Who Should Take This Course?

This course is designed for working professionals who operate in Agile, Lean, and DevOps environments and who are responsible, in whole or in part, for defining what should be built. It is particularly well suited for practitioners who want to sharpen their core elicitation and validation skills while learning to use generative AI with confidence and appropriate skepticism.

If you are newer to business analysis, the fundamentals are covered in enough depth to build on. If you have been doing this work for years, the AI integration content will show you that your existing expertise is exactly the advantage you need in an AI-assisted workflow.

No prior experience with AI tools is required. What the course assumes is that you work in or around software and digital product delivery, and that requirements, user stories, or acceptance criteria are part of your professional life.

The course is a strong fit for:

  • Practicing and aspiring Business Analysts

  • Product Owners and Product Managers

  • Scrum Masters and Agile Coaches

  • Project and Program Managers

  • Subject Matter Experts who contribute to requirements

  • Systems Analysts and Designers

  • Quality Assurance Professionals

  • Business Process Managers and Users

In short: anyone whose job involves getting the "what" right in a fast-moving delivery environment, and who wants to use AI to do that faster without sacrificing quality.

Fully updated content integrating the latest generative AI tools and techniques, including demonstrations using ChatGPT.

  • Quizzes and practical assignments throughout to reinforce learning and build real skills.

  • Direct access to the instructors for questions and additional guidance.

  • Our unique Requirements Template for AI Projects: Extends your standard Agile categories to capture the business, governance, and operational requirements that AI-enabled solutions demand (the ones that rarely show up in your backlog until a stakeholder asks an uncomfortable question in sprint review).

  • AI Project Requirements Working Template: The companion field document you take into an actual project. All eight requirement dimensions, ready to fill in, with just enough embedded guidance to keep you honest when discovery gets messy and the temptation to skip sections is at its highest.

  • An extensive Requirement Validation Prompt Library: A collection of pointed prompts that put your user stories and acceptance criteria under real pressure, surfacing the ambiguity, missing conditions, and untestable language that slip through refinement sessions and land in your sprint as someone else's problem.

  • Lifetime access to all course materials, including future updates.

  • 30-day money-back guarantee if you are not completely satisfied.

Upon completion, you will be able to:

  • Elicit stakeholder needs effectively, even when those needs are unclear or in conflict.

  • Express requirements as features, user stories, and lean requirement statements that Agile delivery teams can actually implement.

  • Apply the Cynefin framework to analyze and prioritize work in complex, uncertain environments.

  • Eliminate ambiguous and subjective language that causes rework, misunderstandings, and missed deadlines.

  • Write test scenarios using Given-When-Then that surface missing requirements before development begins.

  • Discover, document, and validate Non-Functional Requirements so that quality is built in, not bolted on.

  • Configure the information environment for AI tools using context engineering principles drawn from established business analysis practice.

  • Apply output validation habits that keep AI-generated requirements accurate, testable, and aligned with stakeholder intent.

Why Choose This Course?

Tom and Angela Hathaway have spent four decades helping organizations bridge the gap between what the business needs and what technology delivers. That experience shows up in every lecture, not as theory, but as the kind of hard-won, occasionally embarrassing, practical knowledge that only comes from doing this work at scale across industries and continents.

The course is regularly updated with current AI tool demonstrations, real project examples, and content that reflects how Agile requirements practice is actually changing, not how vendors wish it were changing.

About the Instructors

  • Over 40 years of combined expertise facilitating workshops and coaching students globally in business analysis and generative AI.

  • Authors of 12 books in the field of business analysis and requirements engineering.

  • Creators of 18 comprehensive Udemy courses with more than 150,000 enrolled students.

  • Active YouTube presence with over 20,000 subscribers and over 2 million views, advocating lean and agile methodologies.

Enroll today. The fundamentals are your advantage. This course is how you use them.

Course Content

  • 8 section(s)
  • 44 lecture(s)
  • Section 1 Introduction to the Course
  • Section 2 Requirements in a Lean and Agile World
  • Section 3 Requirements Discovery for Agile and Lean IT Projects
  • Section 4 Writing Business and Stakeholder Requirements and Features
  • Section 5 Avoiding Ambiguity and Subjectivity
  • Section 6 Finding Test Scenarios in a LEAN, AGILE World
  • Section 7 Dealing with Non-Functional Requirements (NFR)
  • Section 8 From Showtime to Go Time!

What You’ll Learn

  • Integrate Generative AI into elicitation, drafting, ambiguity detection, and test scenarios while maintaining the validation habits that protect quality, Apply context engineering to configure AI tools with the right information environment, reducing hallucinations and improving output quality, Explain the capabilities and tradeoffs of Lean, Agile, and continuous delivery for defining requirements, Apply 10 elicitation techniques adapted for Lean/Agile teams to uncover real stakeholder needs faster, Use ChatGPT to apply the Cynefin framework to surface uncertainty, assumptions, and complexity in requirements, Reduce miscommunication by identifying and removing ambiguous and subjective language from requirements, Use the 4-step output validation method to catch defective requirements before they waste developer time, regardless of source, Break down features, stories, and functions into Given-When-Then test scenarios to support automated testing, Identify 17 categories of Non-Functional Requirements (NFRs) and write GWT scenarios to verify them, Build a repeatable workflow applying these techniques on the job, from discovery through requirements, validation, and tests


Reviews

  • D
    Dulce Vitiza Neves Pires Mendes
    4.5

    The way the knowledge is delivered, combined with the opportunity to actively practice through assignments, is a real strength of this course.

  • A
    Alesia Minyard
    1.5

    Disjointed and too long - this training should be broken up into smaller classes and be a series of classes Also, for the practice scenarios, it is often difficult to know what kind of info is expected.

  • J
    Juan Manuel Morales Rodriguez
    3.5

    Interesantes conceptos

  • S
    Shekhar Anand
    5.0

    yes, it is interesting learning

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