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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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8 Feb 2026

AI For Scrum Product Owners - February 17. 2026

Author: Rod Claar CST  /  Categories: AI for Scrum Product Owners  /  Rate this article:
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Event date: 2/17/2026 9:00 AM Export event

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AI for Scrum Product Owners

Use GenAI as a practical co-pilot for product work: refine stories and acceptance criteria, improve backlog ordering, sharpen stakeholder communication, and strengthen product strategy with AI-assisted insights.

Who it’s for

Product Owners, Product Managers, and agile practitioners who want to streamline PO workflows with AI—including Business Analysts, Project Managers transitioning to agile, Scrum Masters supporting Product Owners, and agile teams integrating AI into day-to-day delivery.

Enrollment
Investment
$299

Live virtual, interactive (instructor-led)

 

Private In-Person (up to 18 students + travel): $499

Format
Live Virtual

Hands-on workshop with real-time instruction and collaboration

Duration

4 hours (half-day workshop)

Delivery

Live virtual (instructor-led)

Pacing

Single-session workshop

Outcomes
  • Use prompt-engineering patterns to generate PO-ready artifacts: story drafts, acceptance criteria, release notes, and stakeholder updates.
  • Improve backlog ordering with AI-assisted discovery: clarify outcomes, uncover hidden dependencies, and surface risk/assumptions.
  • Strengthen product strategy using AI for market/competitor synthesis, roadmap narrative, and hypothesis-driven planning.
  • Run higher-signal Scrum events with AI support (planning, reviews, retros): better inputs, tighter facilitation assets, cleaner outputs.
  • Apply guardrails for responsible AI use (privacy, bias, transparency) when working with product, customer, and team information.

 

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Author: Rod Claar
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