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Hands-on Workshop

Ready to Transform Your Scrum Team with AI?

Join the Generative AI for Scrum Teams Workshop

Stop wondering how AI fits into your Agile workflow. In this hands-on workshop, you'll learn exactly how to integrate AI tools into every sprint ceremony, backlog refinement session, and delivery cycle—without disrupting the Scrum framework that already works for your team.

What You'll Master:

  • AI-powered user story creation and refinement techniques
  • Automated test generation and code review strategies
  • Sprint planning acceleration with AI assistance
  • Real-world prompt engineering for development teams
  • Ethical AI integration within Scrum values

Perfect for: Scrum Masters, Product Owners, Development Teams, and Agile Coaches who want to boost productivity while maintaining team collaboration and quality.

Register for the Next Workshop Learn More

Taught by Rod Claar, Certified Scrum Trainer with 30+ years of development experience and specialized AI-Enhanced Scrum methodology.

Search Results

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.

Rod Claar 0 145 Article rating: No rating

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.

Read more

Step 2: Prompts That Produce Better User Stories

Most weak user stories are not caused by bad teams. They are caused by vague inputs.

Rod Claar 0 86 Article rating: No rating

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

Read more

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

AI can accelerate backlog refinement. It can also quietly shift focus from outcomes to output. This step ensures AI strengthens clarity and flow—without diluting product intent.

Rod Claar 0 115 Article rating: No rating

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.

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Step 4: Sprint Planning Acceleration

Sprint Planning often slows down when the team debates wording, scope framing, or sequencing. AI can accelerate preparation—without turning planning into automation. The objective is to generate plan options, not commitments.

Rod Claar 0 114 Article rating: No rating

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.

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