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Drawing from decades of real-world experience in software development, consulting, and agile transformation, I provide industry-leading Scrum certification training that bridges theory with practical application.

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With over three decades in software development and more than 15 years teaching Scrum and Agile practices, I bring real-world insights that go beyond certification preparation.

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20+
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Certified ScrumMaster (CSM)

Learn to facilitate Scrum teams effectively, remove impediments, and drive continuous improvement. This foundational certification prepares you to lead agile teams with confidence and competence.

Perfect for: Team leads, project managers, and aspiring Scrum Masters

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Master the art of maximizing product value, managing backlogs, and collaborating with stakeholders. Develop the skills to prioritize effectively and deliver what customers truly need.

Perfect for: Product managers, business analysts, and product leaders

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Pick from two paths and classes: the traditional CSD learning that includes TDD, ATDD, and Code Quality, or the new AI-Enhanced Scrum: Transforming Agile Development with AI.

Perfect for: Developers on Scrum Teams

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Scrum and Agile aren't just frameworks to memorize—they're mindsets to embody. My teaching approach emphasizes practical application over rote learning, drawing from real implementations I've led across retail, software product development, and consulting environments.

I believe the best learning happens when you understand the "why" behind the practices. Throughout my courses, I share actual challenges I've faced implementing Scrum, the solutions that worked, and the lessons learned from failures. You'll leave not just prepared for certification, but equipped to navigate the messy reality of agile transformation.

Whether you're just starting your Scrum journey or looking to deepen your expertise, my goal is to help you develop the judgment and confidence to adapt agile principles to your unique context—because that's what truly effective Scrum practitioners do.

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Search Results

24 Feb 2026

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

Author: Rod Claar  /  Categories: AI for Scrum Masters Learning Path  / 

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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