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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: Turn backlog items into “buildable slices” (small, testable, valuable)

Author: Rod Claar  /  Categories: Software Developer Learning Path  /  Rate this article:
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What Makes a Slice “Buildable”

A buildable slice:

  • Produces user-visible behavior

  • Can be tested independently

  • Meets the Definition of Done

  • Contributes to a measurable outcome

  • Can be completed within a Sprint

If it requires multiple handoffs or partial completion, it is too large.


Practical Slicing Patterns

Use these techniques deliberately:

1. Workflow Step
Deliver one end-to-end step before the full process.

2. Happy Path First
Implement the simplest scenario before edge cases.

3. Single Rule Variation
Support one business rule before adding complexity.

4. Data Scope
Enable one user type or limited dataset first.

5. Risk-First Slice
Implement the most uncertain part early.


Example

Oversized Story:

Build reporting dashboard for release readiness.

Possible Slices:

  1. Display backlog readiness score for top 10 items

  2. Flag items missing acceptance criteria

  3. Highlight cross-team dependencies

  4. Show Sprint goal completion trend

  5. Export summary as PDF

Each slice is independently demonstrable.


Acceptance Criteria Discipline

Every slice should include:

  • Clear behavioral expectation

  • Explicit inputs and outputs

  • Testable conditions

If acceptance criteria contain ambiguity, refinement is incomplete.


Exercise

  1. Select one oversized backlog item.

  2. Split it into 3–5 buildable slices.

  3. Write acceptance criteria for each slice.

  4. Confirm each slice could be:

    • Built

    • Tested

    • Demonstrated

    • Released

If not, refine further.

Smaller slices reduce variability, improve predictability, and increase learning velocity.

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Author: Rod Claar
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2 Apr 2026

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