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Certified Scrum Developer®

Taught by: Rod Claar
Transform your Scrum practice. Capture requirements intelligently. Design interfaces innovatively. Generate comprehensive technical specifications. Enhance your team's capabilities. Visualize your architecture. Deliver exceptional software with AI as your complete dev partner and team member.
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 Oct 01 - 03, 2025 |
 4:00 PM UTC |
 8 hrs/day
$999
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Course details


Location

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In-Person

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435 NE Wasco St, Porland, OR 97232, US


Max number of students: 6

AI-Enhanced Scrum: Transforming Agile Development with AI

With this training, you are ready to become an AI Developer and use the latest AI Tools in just 3 days.

First Class Limited to 6 Students.  This is an in-person class.

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.

Take Your Next Sprint to the Next Level—Register Today!

Transform your Scrum practice. Capture requirements intelligently. Design interfaces innovatively. Generate comprehensive technical specifications. Enhance your team's capabilities. Visualize your architecture. Deliver exceptional software with AI as your complete development partner from conception through deployment.

 

Join us for a dynamic learning experience that not only strengthens your Scrum capabilities but also infuses your development processes with cutting-edge AI innovations, ensuring you and your team deliver greater business value in every Sprint.

The students will be engaged in practice sessions and  therefor should have a PC or MAC loaded with appropriate development platforms and tools.

Completing this course will result in a Certified Scrum Developer certification from the Scrum Alliance and an Artificial Intellegence course certiificate from Effective Agile Development.

  • New Half Now and Half Later Payment Option!: Make sure you select the pay later option. We will send an invoice that is half of the total and pay the remainder before the class starts!
  • New Gold Plan Pricing!: This plan includes up to 8 hours of personalized coaching with the instructor in the first 60 days after the class!

Join us for a dynamic learning experience that not only strengthens your Scrum capabilities but also infuses your development processes with cutting-edge AI innovations, ensuring you and your team deliver greater business value in every Sprint.

Completing this course will result in a Certified Scrum Developer certification from the Scrum Alliance and an Artificial Intelligence course certificate from Effective Agile Development.

  • New Half Now and Half Later Payment Option!: Make sure you select the pay later option. We will send an invoice that is half of the total and pay the remainder before the class starts!
  • New Gold Plan Pricing!: This plan includes up to 8 hours of personalized coaching with the instructor in the first 60 days after the class!

Module 1: Foundations of AI-Enhanced Scrum

  • Traditional Scrum Framework Review
    • Sprint planning, daily standups, retrospectives, and reviews
    • Product backlog management and user story creation
  • AI Integration Points in Scrum
    • Identifying opportunities for AI enhancement
    • Tool selection and team readiness assessment
  • Setting Up Your AI-Enhanced Development Environment

Module 2: AI-Driven Requirements Gathering and Product Definition

  • Interactive PRD Creation with AI
    • AI-guided requirements discovery through intelligent questioning
    • Dynamic question generation based on project type and domain
    • Comprehensive stakeholder perspective gathering through AI interviews
    • Business objective clarification and success metrics definition
  • Using AI to Detail Features from PRD
    • Converting PRD sections into comprehensive feature descriptions
    • AI-assisted user story decomposition and acceptance criteria generation
    • Leveraging AI for edge case identification and scenario planning
  • AI-Generated Technical Specifications
    • Converting business requirements into detailed technical specs using AI
    • Architecture decision documentation with AI assistance
    • API design and data model specification through AI collaboration

Module 3: Visual Design and User Interface Generation

  • UML Visual Modeling with AI Assistance
    • Generating UML class diagrams from PRD and feature descriptions
    • AI-powered sequence diagrams for feature workflows
    • Use case diagrams for stakeholder communication
    • Component and deployment diagrams for system architecture
    • Iterative refinement of UML models through AI feedback
  • AI-Generated User Interface Design with Non-Traditional Prompting
    • Advanced Prompting Techniques for UI Generation
      • Role-based prompting: "Act as a senior UX designer with 10 years experience"
      • Persona-driven design prompts using target user characteristics
      • Constraint-based prompting for accessibility and responsive design
      • Chain-of-thought prompting for design decision reasoning
    • Multi-Modal UI Design Approaches
      • Iterative wireframe refinement through conversational prompting
      • Style guide generation using brand personality prompts
      • Component library creation with design system prompts
      • Responsive layout generation with device-specific constraints
    • Context-Aware Interface Design
      • PRD-informed UI generation with business goal integration
      • User journey-based interface flows from UML use cases
      • Accessibility-first design through inclusive prompting techniques
      • Performance-optimized UI suggestions using technical constraint prompts

Module 4: Acceptance Test Driven Development (ATDD) with AI

  • ATDD Fundamentals in the AI Era
    • Writing executable specifications with AI assistance
    • Collaborative specification workshops enhanced by AI insights
  • AI-Generated Test Scenarios from PRD, UI, and UML Models
    • Converting PRD requirements and UML use cases into comprehensive test scenarios
    • UI interaction test generation from wireframes and design specifications
    • Boundary condition and negative test case identification from class diagrams
    • Performance and security test scenario creation using component diagrams
    • Accessibility and usability test generation from UI designs
    • Traceability from PRD requirements through UI to test cases
  • Living Documentation
    • Maintaining synchronized PRD, UI designs, UML models, tests, and code through AI automation

Module 5: Comprehensive AI-Generated Technical Specifications

  • Synthesizing All Project Artifacts
    • AI-powered analysis of PRD, UI designs, UML models, and ATDD test scenarios
    • Cross-reference validation ensuring consistency across all documentation
    • Gap identification and resolution through AI-assisted analysis
  • AI-Generated System Architecture Specifications
    • Backend Architecture Design
      • Database schema generation from UML class diagrams and PRD data requirements
      • API endpoint specification derived from UI interaction flows and use cases
      • Microservices decomposition based on UML component diagrams
      • Integration patterns and communication protocols
    • Frontend Architecture Specifications
      • Component hierarchy generation from UI designs and wireframes
      • State management architecture based on user interaction flows
      • Performance optimization strategies derived from UML sequence diagrams
      • Responsive design implementation specifications
    • Infrastructure and Deployment Specifications
      • Cloud architecture recommendations based on PRD scalability requirements
      • CI/CD pipeline specifications informed by testing strategies
      • Security implementation details derived from ATDD security scenarios
      • Monitoring and logging requirements based on system complexity analysis
  • Detailed Implementation Guidelines
    • Code Structure and Standards
      • Naming conventions derived from domain language in PRD
      • File organization patterns based on UML package structures
      • Design pattern recommendations from architectural analysis
      • Code quality metrics and standards alignment
    • Data Flow and Processing Specifications
      • Request/response flow documentation from sequence diagrams
      • Data transformation specifications between UI and backend
      • Caching strategies based on performance requirements
      • Error handling and validation rules from ATDD scenarios
    • Integration Specifications
      • Third-party service integration requirements from PRD
      • API versioning and backwards compatibility strategies
      • Authentication and authorization implementation details
      • Cross-platform compatibility requirements from UI specifications
  • Technical Risk Assessment and Mitigation
    • AI-identified potential technical challenges from artifact analysis
    • Performance bottleneck predictions based on system complexity
    • Security vulnerability assessments from architectural review
    • Scalability impact analysis and optimization recommendations

Module 6: Test Driven Development (TDD) for AI-Guided Development

  • TDD as Your AI Development Agent's North Star
    • Writing failing tests that guide AI code generation
    • Using test descriptions to communicate intent to AI tools
    • Red-Green-Refactor cycle with AI pair programming
  • AI Agent Training Through Comprehensive Technical Specifications
    • How detailed technical specs enhance AI code generation accuracy
    • Using technical architecture specifications to provide implementation context
    • Leveraging comprehensive specs for better AI development agent guidance
    • Frontend and backend component generation guided by technical specifications
    • Iterative refinement of AI-generated code through TDD cycles

Module 7: Defect Resolution and Quality Assurance

  • Using TDD to Fix Defects with AI
    • Writing regression tests for bug reproduction
    • AI-assisted root cause analysis using complete technical specification context
    • Referencing comprehensive technical specs for defect impact assessment
    • Architecture-aware defect resolution using system specification knowledge
    • Preventing defect recurrence through comprehensive test coverage
  • Quality Gates in AI-Enhanced Sprints
    • Automated code review with AI tools using complete technical specifications as reference
    • Continuous integration with AI-generated tests
    • Multi-artifact consistency validation (PRD-UI-UML-TechSpec-Code)
    • Automated technical specification compliance checking

Module 8: Sprint Management and Team Dynamics

  • AI-Enhanced Sprint Planning
    • Velocity prediction using technical complexity analysis from specifications
    • Risk assessment using comprehensive technical specification complexity metrics
    • Feature dependency visualization through complete system architecture understanding
    • Sprint goal alignment with technical implementation realities
  • Daily Standups and Progress Tracking
    • AI-generated progress reports against technical specification milestones
    • Implementation complexity tracking using technical specification metrics
    • Automated sprint health monitoring with technical debt assessment
  • Retrospectives and Continuous Improvement
    • AI-facilitated retrospective insights using technical specification learnings
    • Architecture evolution tracking through specification versioning
    • Technical specification refinement based on implementation feedback

Module 9: Practical Workshop and Implementation

  • Hands-on AI-Enhanced Sprint Simulation
    • Interactive PRD creation session with AI interviewer
    • Complete project lifecycle: PRD → UI Design → UML → ATDD → Technical Specs → TDD → code
    • Advanced prompting workshop for comprehensive technical specification generation
    • Team exercises covering the full development pipeline
  • End-to-End Project Demonstration
    • Complete feature development from AI-generated PRD through technical specifications to deployed code
    • Stakeholder communication using the complete artifact suite
    • Technical specification validation and refinement process
  • Tool Integration and Best Practices
    • Popular AI development, PRD, UI design, UML, and technical specification tools integration
    • Automated specification generation and synchronization workflows
    • Advanced prompting libraries and template management for technical documentation
    • Measuring success and ROI of AI-enhanced comprehensive development processes
  • 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

The students will be engaged in practice sessions and  therefor should have a PC or MAC loaded with appropriate development platforms and tools.

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