Select the search type
  • Site
  • Web
Search

Learning Path

AI for Scrum Product Owners

Built for Product Owners and product leaders who want practical, sprint-ready ways to use AI for discovery, roadmap clarity, and backlog excellence—without losing customer focus.

  • Turn fuzzy ideas into crisp requirements Use AI-assisted discovery prompts to clarify outcomes, assumptions, and constraints—fast.
  • Write better stories with fewer rework loops Generate user stories, acceptance criteria, and examples that align to the Sprint Goal and Definition of Done.
  • Improve prioritization & stakeholder alignment Use AI to synthesize feedback, spot tradeoffs, and communicate value with confidence.

Path Steps

Work through these in order. Each step links to an EasyDNNnews article/video post, with a quick exercise to apply it immediately.

Learn a simple PO-friendly mental model for where AI helps most (discovery, backlog quality, prioritization, and stakeholder communication).

!Do this exercise

List your top 3 “unknowns” for the next release (users, value, constraints). Ask AI to generate 10 clarifying questions for each.

Learn how to turn interviews, notes, and feedback into themes, risks, and opportunities you can act on in a sprint.

!Do this exercise

Paste 10–20 lines of feedback. Ask AI to cluster it into themes + propose 3 experiments you can run next sprint.

Learn how to use AI to produce verifiable criteria and concrete examples (happy path, edge cases, and failure modes).

!Do this exercise

Pick one story. Ask AI for 6 acceptance tests: 2 happy, 2 edge, 2 negative—then remove anything you can’t objectively verify.

Learn a lightweight approach to ranking work using value, risk, and effort—and how to use AI to surface tradeoffs and assumptions.

!Do this exercise

Take your top 10 backlog items. Ask AI to propose a ranked list and explain the assumptions—then adjust the assumptions, not just the order.

Learn how to generate clear status updates that focus on outcomes, decisions needed, risks, and next steps—without noise.

!Do this exercise

Ask AI to draft a 6-sentence stakeholder update: outcome, evidence, what changed, current risk, decision needed, and next checkpoint.


Reminder: To deepen these skills in a real product environment, remember to take the Certified Scrum Product Owner (CSPO) class. The course expands on these techniques and shows how to apply AI responsibly in real Scrum teams.

Path Steps - Free

24 Feb 2026

Step 1: AI Foundations for Product Owners: A Practical Mental Model

This content introduces a practical mental model for how Product Owners should use AI effectively.

Instead of focusing on tools, it emphasizes outcomes. AI delivers the most value in four areas:

  1. Discovery – Clarifying user needs and exposing assumptions.

  2. Backlog Quality – Strengthening acceptance criteria and reducing ambiguity.

  3. Prioritization – Evaluating trade-offs across value, risk, and constraints.

  4. Stakeholder Communication – Translating complexity into clear narratives.

The core message: AI should amplify critical thinking, not replace product judgment.

A practical exercise reinforces this approach:

  • Identify the top three unknowns for the next release (users, value, constraints).

  • Ask AI to generate ten clarifying questions for each unknown.

The objective is to surface blind spots early, improve backlog decisions, and increase the probability of delivering meaningful business outcomes.

Author: Rod Claar
0 Comments
RSS

Path Steps - Members

 
 
✓ Featured Content

Scrum Product Owner Videos

A curated playlist of specific YouTube content.

Search Results

1 Jun 2026

The Prompt is the Program

The Prompt is the Program

Author: Rod Claar  /  Categories: Prompt Engineering  / 

The Prompt is the Program

Clean code starts with clear thinking.

The same is true for AI prompts.

I've been writing code since the early 1990s. C. Then C++. Then Java. Then C#.

Every language taught me the same lesson.

Vague instructions produce broken results.

That's true in code. It's true in AI.

When you write a prompt, you're writing a program. You're telling the AI what to do, what to return, and what to ignore.

Here's what I teach my students:

✅ Be specific about the task ✅ Tell the AI the format you want ✅ Give it context — who you are, what you're building ✅ Add constraints — what it should NOT do

A prompt like "help me with code" is like writing a function with no parameters and no return type.

It might work. But probably not well.

Try this instead:

"You are a C# developer. Write a unit test using xUnit for a method that calculates sales tax. Return only the test method. No explanation."

That's a program. And it works.

Developers already think this way. You just need to apply it to AI.

Want to sharpen your AI skills? 👉 Start here: https://agileaidev.com/resources/ai-tips-and-tricks 👉 Explore courses: https://agileaidev.com/courses

What's one prompt tip that changed how you use AI? Drop it in the comments. ⬇️

#AI #SoftwareDevelopment #ArtificialIntelligence #Agile #AgileCoaching

Print

Number of views (416)      Comments (0)

Search

Calendar

«June 2026»
SunMonTueWedThuFriSat
31123456
78910111213
14151617181920
21222324252627
2829301234
567891011

Upcoming events

Join updates / get new lessons Free

Get notified when new Product Owner lessons, templates, and examples drop—so you can apply AI in your backlog and stakeholder work right away.

Go deeper with the course Paid

Move from “cool prompts” to a repeatable PO workflow: discovery → stories → prioritization → roadmap → stakeholder comms, with proven templates.

Quick setup: Replace the href="#" on “Join Updates” with your email/lead form link, and replace https://example.com/course-sales-page with your course sales page.