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Path Steps

Follow these steps in order. Each one links to an EasyDNNnews article/video and gives you a quick, practical takeaway.

You’ll learn how to frame AI as a teammate that supports Scrum events and backlog work without replacing judgment or collaboration.
Do this exercise: Write a 3-sentence “AI usage policy” for your team (what you will use AI for, what you won’t, and what must be reviewed by a human).
You’ll learn repeatable prompt patterns to generate stories with clearer intent, constraints, and acceptance criteria.
Do this exercise: Take one messy request and prompt AI to produce (a) a user story, (b) 5 acceptance criteria, and (c) 3 key questions for the PO.
You’ll learn how to generate “plan options” (not commitments) and improve shared understanding of scope and dependencies.
Do this exercise: Ask AI for 2 sprint goal options based on your top backlog items, then pick one as a team and adjust wording together.
You’ll learn facilitation prompts that help teams extract insights, turn feedback into actions, and avoid “retro theatre.”
Do this exercise: Feed AI 5 bullet facts from the sprint and ask for (a) patterns, (b) 3 improvement experiments, and (c) 1 metric per experiment.
You’ll learn how to convert your best prompts and practices into a lightweight working agreement the team can actually follow.
Do this exercise: Create a “Prompt Library” page with 5 prompts: refinement, story writing, planning, review, retro—each with input/output examples.
 

Learning Path - Free

24 Feb 2026

Step 1: What AI Can (and Can’t) Do for Scrum Teams

AI is a productivity amplifier—not a Product Owner, not a Scrum Master, and not a Developer.

Used correctly, it accelerates learning, drafting, summarizing, and exploring options. Used poorly, it replaces thinking with automation theater.

This step helps your team position AI as a supporting teammate, not a decision-maker.

Author: Rod Claar
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24 Feb 2026

Step 2: Prompts That Produce Better User Stories

AI can help—but only if the prompt is structured.

This step introduces repeatable prompt patterns that improve:

  • Intent clarity

  • Constraints visibility

  • Acceptance criteria quality

  • PO alignment

Author: Rod Claar
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24 Feb 2026

Step 3: Backlog Refinement with AI (Without Losing the “Why”)

The Core Risk

When teams use AI in refinement, a common failure mode appears:

  • Stories get cleaner

  • Acceptance criteria get longer

  • Technical detail increases

  • Business intent becomes less visible

Scrum optimizes for value delivery, not documentation density.

AI must support the “why” behind the work.

Author: Rod Claar
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24 Feb 2026

Step 4: Sprint Planning Acceleration

The Key Principle

AI should propose:

  • Possible Sprint Goals

  • Possible scope groupings

  • Possible dependency flags

The team still decides:

  • What to commit to

  • What fits capacity

  • What aligns to product strategy

AI drafts.
The team commits.

Author: Rod Claar
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Learning Path - Member

 
 
✓ Featured Content

AI for Scrum and Agile Teams
Videos

A curated playlist of specific YouTube content.

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17 Feb 2026

AI-Enhanced Scrum: Transforming Agile Development with AI - April 22-24

Author: Rod Claar CST  /  Categories: Certified Scrum Developer  /  Rate this article:
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Event date: 4/23/2026 - 4/25/2026 Export event

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$749.00 - $949.00

AI-Enhanced Scrum: Transforming Agile Development with AI

Artificial Intelligence is rapidly changing how modern software teams design, plan, and deliver products. AI-Enhanced Scrum shows how to integrate practical AI tools directly into your Agile workflow so teams can generate specifications faster, automate development tasks, and improve collaboration.

In this immersive three-day workshop, you will learn how to combine the proven structure of Scrum with emerging AI capabilities. The course demonstrates how AI can assist with backlog refinement, technical specification generation, development workflows, and overall team productivity.

By the end of the class, participants will understand how to apply AI tools in real Scrum environments and create development workflows that significantly accelerate delivery while maintaining Agile principles. :

Key Learning Objectives

  • ✅ Understand how AI is transforming modern Agile software development
  • ✅ Integrate AI tools directly into Scrum workflows
  • ✅ Generate technical specifications and development artifacts with AI assistance
  • ✅ Improve backlog refinement, planning, and estimation with AI support
  • ✅ Automate repetitive development tasks to increase team productivity
  • ✅ Apply practical techniques to accelerate delivery while maintaining Agile principles
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