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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

28 Aug 2025

Is your company's most valuable asset locked away?

Is your company's most valuable asset locked away?

Author: Rod Claar  /  Categories: AI Tools  /  Rate this article:
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I'm not talking about your patent portfolio or your client list. I'm talking about the collective intelligence sitting dormant in your Google Docs, PDFs, and text files—project reports, market research, meeting notes, and training manuals.

For years, we've treated these documents as a static archive. We search for keywords and hope for the best. But what if you could turn that entire library into an interactive, expert conversationalist?

That's the paradigm shift being driven by tools like Google's NotebookLM.

This isn't just another AI chatbot pulling from the public internet. NotebookLM is a private, personalized AI that is grounded exclusively in the sources you provide. You upload your documents, and it becomes an expert on your information.

For a modern business, the advantages are transformative:

1. 🧠 Annihilate Information Silos:
Imagine your entire knowledge base—from marketing briefs to technical specs—becomes a single, queryable source of truth. A new project manager can ask, "Summarize the key takeaways from our last three product launches," and get an instant, cited answer compiled from multiple reports.

2. 🚀 Supercharge Research & Analysis:
Instead of spending hours manually sifting through competitor analysis reports, your team can ask complex questions. "What are the most common feature requests from enterprise clients in Q2?" NotebookLM can synthesize the information and provide a bulleted list with citations, saving dozens of hours.

3. ✍️ Accelerate High-Quality Content Creation (Text & Video!):
Your marketing team can upload brand guidelines and case studies to draft on-brand blog posts in seconds. But it goes beyond text. Imagine you need to create an internal presentation summarizing a key industry analysis, like Julia McCoy's recent YouTube video on the "$500 Billion AI War." Instead of re-watching and taking notes for an hour, you can upload the transcript. Then, ask NotebookLM:

"Generate a 10-slide presentation outline from this transcript, with a key takeaway and speaker notes for each slide."

You get the structured content for your PowerPoint or video script in minutes, not hours.

4. 📈 Streamline Onboarding & Training:
New hires can "talk" to your company handbook and process documents. Instead of repeatedly asking senior team members basic questions, they can ask NotebookLM, "What are the steps for submitting an expense report?" or "Explain our Q3 strategic goals." This frees up valuable time for everyone.

5. 💡 Enhance Strategic Decision-Making:
By grounding the AI in your financial reports and board meeting minutes, leadership can quickly surface critical insights to make faster, more data-driven decisions without needing a data analyst for every question.

The bottom line: NotebookLM isn't about replacing human thought; it's about augmenting it. It unlocks the latent value trapped in your documents, turning static information into a dynamic competitive advantage. It moves your team from being "data-rich" to "insight-rich."

How could a personalized AI assistant, trained exclusively on your company's knowledge, transform your team's workflow?

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Author: Rod Claar
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