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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.

Search Results

24 Feb 2026

Step 2: Backlog Refinement with AI (Without Losing Collaboration)

Author: Rod Claar  /  Categories: AI for Scrum Masters Learning Path  /  Rate this article:
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Where AI Helps (and Where It Shouldn’t)

Appropriate Uses

  • Rewrite vague stories into clear user-value language

  • Generate draft acceptance criteria

  • Propose vertical slices

  • Surface edge cases

  • Suggest test scenarios

Not Appropriate

  • Final prioritization decisions

  • Technical architecture decisions

  • Estimation

  • Commitment decisions

You are using AI as a thinking amplifier, not a substitute for collaboration.


DO THIS EXERCISE

Step 1: Select One “Too Big” Story

Example:

“Build a new user dashboard with analytics.”

This is oversized, multi-featured, and vague.


Step 2: Use This Vertical Slice Prompt

Copy and use:


PROMPT TEMPLATE — Vertical Slice Generator

You are an experienced Product Owner and Agile coach.

INPUT
User Story: {paste oversized story}
Constraints: {tech constraints, sprint length, dependencies if known}

TASK
Propose 3 vertical slices that:

  • Deliver user-visible value

  • Can be completed within one sprint

  • Are independently testable

  • Avoid architectural layering splits

For each slice:

  1. Provide a short title

  2. Explain the user value

  3. List 3–5 acceptance criteria

  4. Explain why this is a true vertical slice

Keep responses concise and practical.


Step 3: Example Output (For the Dashboard Story)

Slice 1 — “View Basic Metrics Summary”

User Value:
User can see top 3 KPIs on login.

Acceptance Criteria:

  • Displays revenue, active users, churn

  • Data refreshes on page load

  • Handles empty data state

  • Works on desktop layout

Why Vertical:
End-to-end data retrieval, rendering, and validation.


Slice 2 — “Filter Metrics by Date Range”

User Value:
User can view metrics for last 7, 30, or 90 days.

(With criteria…)


Slice 3 — “Export Dashboard Snapshot as PDF”

User Value:
User can share dashboard externally.

(With criteria…)


Step 4: Bring One Slice to the Team

This is critical.

Do not accept AI output as final.

With the team:

  • Challenge assumptions

  • Improve acceptance criteria

  • Add missing edge cases

  • Refine definition of done

  • Re-estimate

The team must own the rewritten story.


Rewrite Template (With the Team)

Once a slice is selected:

Final Story Format

As a {user}
I want {capability}
So that {measurable benefit}

Acceptance Criteria:

Definition of Done Additions:


Why This Works

AI reduces:

  • Initial ambiguity

  • Story sprawl

  • Unproductive brainstorming loops

The team retains:

  • Ownership

  • Technical judgment

  • Commitment authority

That balance preserves collaboration while increasing throughput.

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