FoundationPlanned
Getting Started with AI Prompt Engineering
Learn a repeatable method for communicating with generative AI, evaluating results, refining prompts, and building prompts that can be reused across professional tasks.
You will learn to:
- Write prompts using the RCCF framework
- Provide useful context and explicit constraints
- Select appropriate output formats
- Iterate based on observed results
- Validate AI output using the VALID checklist
Designed for: Professionals, managers, trainers, Agile practitioners, developers, and people beginning practical AI use.
DeveloperPlanned
AI-Enhanced Software Development
Use AI across the software development lifecycle while maintaining architectural integrity, testability, security, maintainability, and human accountability.
You will learn to:
- Use AI for analysis, design, coding, and refactoring
- Generate code in small, testable increments
- Review AI-generated code systematically
- Protect architectural boundaries and design intent
- Integrate AI into an Agile engineering workflow
Designed for: Software developers, technical leads, architects, testers, engineering managers, and Agile development teams.
Quality EngineeringPlanned
AI-Assisted Testing and Quality Engineering
Apply AI to test design, boundary analysis, acceptance testing, unit testing, exploratory testing, defect investigation, and quality-risk assessment.
You will learn to:
- Generate test ideas from requirements and examples
- Identify boundary conditions and missing scenarios
- Create draft unit and acceptance tests
- Evaluate tests generated by AI
- Use AI without weakening professional testing judgment
Designed for: Testers, developers, analysts, quality engineers, Product Owners, and technical leaders.
AI ToolingIn Development
AI Skills 101
Learn how reusable AI skills package instructions, workflows, examples, resources, and standards into repeatable capabilities for individual and team use.
You will learn to:
- Explain what an AI skill is and when to use one
- Structure skill instructions and supporting resources
- Convert repeated prompts into reusable workflows
- Test and refine a skill against real tasks
- Share skills responsibly across a team
Designed for: AI practitioners, developers, trainers, consultants, Scrum Teams, and people building repeatable AI workflows.
Advanced AI EngineeringPlanned
Agentic Code Generation
Learn how to assign bounded development work to AI coding agents, provide context, establish verification loops, and control the quality of agent-generated changes.
You will learn to:
- Decompose work into agent-sized engineering tasks
- Provide repositories with effective project context
- Use tests and acceptance criteria as control mechanisms
- Review patches, assumptions, and architectural effects
- Coordinate humans and agents within an Agile workflow
Designed for: Experienced developers, technical leads, architects, engineering managers, and AI-enabled development teams.
AI ArchitecturePlanned
Model Context Protocol Essentials
Understand how Model Context Protocol connects AI systems with tools, files, data sources, and services through standardized, controlled interfaces.
You will learn to:
- Explain MCP clients, servers, tools, and resources
- Connect AI applications to external capabilities
- Design safe and bounded tool interfaces
- Test MCP integrations and failure behavior
- Evaluate security and permission risks
Designed for: Developers, architects, AI engineers, technical consultants, and teams creating integrated AI applications.