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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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Article rating: No rating

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

16 Apr 2025

Use of AI increases accuracy in predictions of ECB moves, DIW says

Use of AI increases accuracy in predictions of ECB moves, DIW says

Author: SuperUser Account  /  Categories: AI Accuracy  /  Rate this article:
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BERLIN, April 16 (Reuters) - The use of artificial intelligence will increase accuracy when predicting the monetary policy moves of the European Central Bank, a study by the German Institute for Economic Research DIW Berlin said on Wednesday.

Researchers analysed the ECB's communications from January 2019 to March 2025 using a specially trained text analysis model based on AI.

The program takes each sentence of the ECB's statements individually and analyses whether it is a signal for a restrictive, expansionary or neutral monetary policy, DIW expert Kerstin Bernoth said.

In an extended forecasting model - using the text analysis and taking into account inflation, economic policy uncertainty and the previous interest rate course - the accuracy of forecasts for interest rate changes can be increased from around 70% to 80%, the study showed.

"Central banks use language as a monetary policy instrument," said Bernoth, author of the study. "The choice of words in speeches, press releases or interviews is never random, but carefully considered and allows conclusions to be drawn about the future direction of monetary policy."

For the upcoming ECB meeting on Thursday, the forecast model signals a high probability of a further interest rate cut, despite the recent more neutral tone.

Analysts polled by Reuters expect the ECB to cut its key interest rate from 2.5% to 2.25% as tariffs curb trade and uncertainty weighs on consumption and investment.

Reporting by Rene Wagner and Maria Martinez, Editing by Rachel More and Ed Osmond

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Author: Rod Claar
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