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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
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A curated playlist of specific YouTube content.

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18 Apr 2025

Master AI Interactions: 8 Prompt Engineering Tips for Enhanced ChatGPT, Claude, and Gemini Responses

Master AI Interactions: 8 Prompt Engineering Tips for Enhanced ChatGPT, Claude, and Gemini Responses

Author: SuperUser Account  /  Categories: AI Tools  /  Rate this article:
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# Prompt Like a Pro: Secrets to Getting Better AI Responses Every Time

In the ever-evolving landscape of artificial intelligence, tools like ChatGPT, Claude, Gemini, and Copilot have become indispensable for a myriad of tasks—from generating creative content and offering programming assistance to providing customer support and beyond. However, getting the most out of these AI models often hinges on how you interact with them. The art of crafting effective prompts is a skill that can significantly enhance the responses you receive. Here are some simple yet powerful prompt engineering tips that non-technical users can apply instantly.

## 1. Be Specific and Clear

The more specific your prompt, the more accurate and relevant the AI's response will be. Vague prompts can lead to generic or off-target answers. For instance, instead of asking, "Tell me about dogs," try "What are the characteristics and care requirements of a Labrador Retriever?"

### Tip:

- Include key details and context relevant to your query to guide the AI in delivering precise information.

## 2. Use Open-Ended Questions

To encourage detailed and expansive responses, frame your prompts as open-ended questions. This invites the AI to explore the topic more thoroughly rather than providing a simple yes or no answer.

### Tip:

- Instead of "Is climate change real?" ask "How is climate change impacting coastal cities worldwide?"

## 3. Set the Tone and Style

AI models are versatile in adapting to different tones and styles. Whether you need a formal report or a casual conversation, specify the desired tone in your prompt.

### Tip:

- Start your prompt with "In a formal style, explain..." or "Write a casual blog post about..."

## 4. Break Down Complex Queries

If your query involves multiple components, break it down into parts. This helps the AI address each aspect thoroughly rather than getting lost in a complex request.

### Tip:

- Instead of "Tell me about renewable energy and its advantages and disadvantages," try "Explain renewable energy sources. Then, discuss their advantages and disadvantages."

## 5. Use Role-Play Scenarios

Encourage the AI to assume a role to provide more contextually relevant answers. This technique is particularly useful in creative writing and customer support scenarios.

### Tip:

- Prompt with "Imagine you are a travel agent. Recommend a week-long itinerary for a family visiting Paris."

## 6. Iterate and Refine

Don’t hesitate to refine and iterate on your prompts based on the responses you receive. Adjusting your approach can lead to improved results.

### Tip:

- After receiving a response, you might say, "Can you provide more detail on the economic impacts mentioned?"

## 7. Leverage System Instructions

Some AI tools allow you to set specific instructions for the system, guiding how it should respond throughout your interaction. This can be particularly useful for maintaining consistency in longer dialogues.

### Tip:

- Use directives like "Always provide examples when explaining complex topics."

## 8. Provide Examples

If you're looking for a specific type of output, providing an example can guide the AI in understanding your expectations.

### Tip:

- When asking for a summary, you might say, "Summarize the following text like this example I provide..."

By practicing these prompt engineering techniques, non-technical users can unlock the full potential of AI models like ChatGPT, Claude, Gemini, and Copilot. With a little creativity and precision, you'll be able to harness the power of AI to generate responses that are not only accurate but also aligned with your specific needs. Happy prompting!

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