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Generative AI for Scrum Teams

Who it’s for: Scrum Masters, Product Owners, and Agile teams who want to use Generative AI safely to accelerate planning, facilitation, and delivery.

Outcomes

  • Create sprint-ready user stories faster with AI-assisted refinement (without losing clarity).
  • Run more effective Scrum events using repeatable prompt templates and facilitation checklists.
  • Add lightweight guardrails to reduce risk (data leakage, hallucinations, and inconsistent outputs).

Your Learning Path

Follow these steps to master Generative AI for Scrum Teams

  1. 1

    Understanding AI Fundamentals for Scrum

    Learn the core AI concepts every Scrum team member needs to know before diving into practical applications.

    Do this exercise
  2. 2

    AI-Assisted User Story Creation

    Discover how to use AI to draft, refine, and validate user stories that are sprint-ready and stakeholder-approved.

    Do this exercise
  3. 3

    Prompt Templates for Sprint Planning

    Get repeatable prompt templates to streamline sprint planning, capacity forecasting, and backlog refinement.

    Do this exercise
  4. 4

    Facilitating Scrum Events with AI

    Learn how to use AI to prepare agendas, generate retrospective insights, and capture action items efficiently.

  5. 5

    Building AI Guardrails for Your Team

    Implement lightweight policies to prevent data leakage, hallucinations, and ensure consistent, trustworthy AI outputs.

    Do this exercise
  6. 6

    AI for Product Backlog Management

    Use AI to prioritize backlog items, identify dependencies, and align work with strategic product goals.

  7. 7

    Measuring AI Impact on Team Velocity

    Track how AI adoption affects your team's velocity, quality, and overall delivery predictability.

    Do this exercise

Steps - Free

24 Feb 2026

Step 1: Understanding AI Fundamentals for Scrum

Before using AI in backlog refinement, Sprint Planning, or testing, every Scrum team member should understand a few core concepts.

Without shared understanding, misuse is inevitable.

Author: Rod Claar
0 Comments

24 Feb 2026

Step 2: AI for Product Owners: Turn Customer Feedback Into Sprint Experiments

Customer & Stakeholder Discovery Prompts

This content explains how Product Owners can use AI to convert raw customer and stakeholder feedback into actionable sprint work.

Instead of treating interviews and notes as static documentation, the approach reframes them as structured inputs for rapid synthesis.

The model follows four steps:

  1. Input – Gather interviews, support tickets, surveys, and call notes.

  2. Clustering – Use AI to group feedback into meaningful themes.

  3. Risk Framing – Identify usability, adoption, and value risks.

  4. Experiment Design – Translate insights into 2–3 testable sprint experiments.

A practical exercise reinforces the method:

  • Paste 10–20 lines of real feedback into AI.

  • Ask it to cluster themes, surface risks, and propose three experiments for the next sprint.

The core principle: AI accelerates synthesis, enabling continuous learning and faster validation within the Scrum cadence.

Author: Rod Claar
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Steps - Members

 
 
✓ Featured Content

Generative AI Videos

A curated playlist of specific YouTube content.

Search Results

20 Jan 2026

AI-Enhanced Scrum: Transforming Agile Development with AI Feb 25-27

AI-Enhanced Scrum: Transforming Agile Development with AI Feb 25-27

Author: SuperUser Account  /  Categories: Scrum & Agile Training  / 

Event date: 2/25/2026 - 2/27/2026 Export event

Revolutionize Your Agile Development with AI-Enhanced Scrum

Are you ready to supercharge your Scrum practices with the power of Artificial Intelligence? Join this cutting-edge course that bridges the gap between traditional Agile methodologies and modern AI-powered development, featuring comprehensive technical specification generation that transforms your entire development workflow.

What You'll Master:

Transform your entire development pipeline from requirements to deployment with AI-driven processes that create a seamless, integrated development experience. Start with AI-guided requirements gathering, advance through revolutionary UI design generation, and culminate in comprehensive AI-generated technical specifications that synthesize all your project artifacts into actionable implementation guidance. Learn to leverage AI for complete feature development including detailed technical architecture, robust test-driven development practices, and quality assurance processes that ensure consistency across your entire project ecosystem.

Revolutionary Requirements-to-Code Pipeline:

Experience how AI can guide you through an integrated development process where each step builds upon the previous one. Watch as your PRD requirements, UI designs, UML models, and acceptance tests are synthesized by AI into comprehensive technical specifications that provide detailed implementation roadmaps for your development team.

Breakthrough Technical Specification Generation:

Master the art of AI-generated technical specifications that analyze and integrate your PRD requirements, UI designs, UML architecture models, and ATDD scenarios into comprehensive implementation guides. Learn how AI can generate database schemas from class diagrams, API specifications from UI flows, architectural recommendations from system complexity analysis, and detailed code implementation guidelines that ensure consistency across your entire technology stack.

Advanced UI Design Integration:

Continue leveraging cutting-edge non-traditional prompting techniques for UI generation, including role-based prompting, persona-driven design creation, and constraint-based accessibility compliance, now enhanced by technical specification integration that ensures design feasibility and optimal implementation approaches.

Complete Development Ecosystem:

Discover how AI maintains perfect synchronization between your PRD requirements, UI designs, UML models, technical specifications, acceptance tests, and code implementation, creating a living documentation system that evolves with your project while maintaining consistency and traceability throughout the development lifecycle.

Why This Course Matters:

In today's rapidly evolving tech landscape, teams that successfully integrate AI into their complete Scrum workflow—from requirements gathering through technical specification to code deployment—are delivering features faster, with higher quality, and with unprecedented thoroughness in their documentation, architecture planning, and implementation consistency. You'll learn to create AI-generated technical specifications that bridge the gap between high-level design and detailed implementation, ensuring your development team has clear, comprehensive guidance for every aspect of feature development.

Perfect For:
  • Solution Architects seeking AI-powered technical specification generation
  • Product Managers wanting end-to-end AI-enhanced development workflows
  • Technical Leads looking to streamline architecture documentation and implementation guidance
  • UX/UI Designers seeking integration between design and technical implementation
  • Scrum Masters modernizing their practices with comprehensive AI-generated documentation
  • Development teams ready to integrate AI tools across the complete development lifecycle
  • Organizations seeking to maintain quality while accelerating delivery through intelligent automation

Led by an Industry Veteran: Learn from an instructor with decades of software development experience, from the early days of C++ to the latest AI innovations. With expertise spanning custom development, core product development, and years of teaching Scrum, TDD, software design patterns, and system architecture, you'll receive practical insights that only come from real-world implementation experience across the complete software development lifecycle.

Class Price$698.60
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20 May 2026

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10 Nov 2025

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