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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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24 Feb 2026

Step 3: Turn outcomes into backlog slices (without giant stories)

Author: Rod Claar  /  Categories: Product Owner Learning Path  /  Rate this article:
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Start With the Outcome

Revisit your measurable outcomes from Step 1.

Example outcome:

  • Increase Sprint goal completion from 60% to 85%

Now ask:

What smallest usable behavior would move this metric?

Not:

  • “Build planning module”

  • “Create reporting dashboard”

Instead:

  • Show backlog readiness score for top 10 items

  • Highlight missing acceptance criteria automatically

  • Flag dependencies across teams

Each slice should enable a real decision.


Use These Slicing Techniques

1. Workflow Slicing
Deliver one step of the workflow end-to-end.

2. Rule Variations
Implement the simplest rule first. Add complexity later.

3. Data Subset
Support one user type or one scenario before expanding.

4. Risk First
Build the part with the highest uncertainty early.


Definition Check

A properly sliced backlog item:

  • Has clear acceptance criteria

  • Produces observable user behavior

  • Can be demonstrated

  • Can be tested

  • Moves at least one measurable outcome

If it takes multiple Sprints, it is still too large.


Practical Heuristic

If the story contains “and,” split it.

Example:

System validates input and generates report
That is two slices.


Small slices reduce cognitive load, improve forecasting accuracy, and surface feedback faster.

That is how outcomes become delivery.

Precision here compounds across every Sprint.

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Author: Rod Claar
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2 Apr 2026

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