Course Outline
Day 1 Overview
Module 1 — Introduction to Claude Code & AI-Enhanced Engineering
• Claude Code versus conventional AI tools
• AI agents within software engineering
• Optimization of productivity and workflows
• AI-assisted development lifecycle
• Risks, constraints, and the role of human oversight
• Live practical demonstrations
Module 2 — Foundations of Prompt Engineering
• Structure of an effective prompt
• Zero-shot versus few-shot prompting
• Iterative prompting strategies
• Fundamentals of prompt chaining
• Structured outputs and formatting
• Prompt validation and quality enhancement
Module 3 — Prompting for Software Development
• Code generation and refactoring
• Debugging with AI support
• Documentation creation
• Pull request reviews
• Understanding legacy code
• Ensuring safe and maintainable AI-generated code
Module 4 — Prompting for Testing & Quality
• Test case generation
• Edge-case analysis
• Designing automation-ready tests
• AI-supported defect analysis
• Creating Gherkin and test scenarios
• Quality verification workflows
Module 5 — Prompting for Agile Collaboration
• User stories and acceptance criteria
• Refining requirements
• Supporting agile communication
• Summarizing for stakeholders
• Assisting with retrospectives
• Preparing for backlog refinement
Module 6 — Responsible AI, Security & Verification
• Hallucinations and AI-related risks
• Confidentiality and secure prompting
• AI governance principles
• Verification checklists
• Awareness of prompt injection
• Responsibilities of human review
Module 7 — Team Prompt Laboratory
• Developing reusable team prompts
• Role-specific AI workflows
• Sharing prompts and peer reviews
• Creating Team Prompt Library v1
• Interactive collaborative exercises
Day 2
Module 1 — Advanced Features of Claude Code
• CLAUDE.md and persistent project context
• Automation of AI workflows
• Best-of-N generation strategies
• Reusable AI commands
• Context engineering methods
• AI-assisted engineering workflows
Module 2 — Advanced Prompt Engineering Strategies
• Chain-of-thought prompting
• Multimodal prompting
• Constraint-based prompting
• Sophisticated prompt chaining
• Managing large contexts
• Conversational engineering workflows
Module 3 — Version Control, Parallel Development & Multi-Agent Workflows
• Git integration strategies
• Parallel AI development workflows
• Worktrees and isolated AI tasks
• Multi-agent orchestration
• Human-in-the-loop checkpoints
• Conflict resolution strategies
Module 4 — Architecture, MCP & Advanced DevOps
• Model Context Protocol (MCP)
• Integrating Claude with external tools
• AI-supported architecture analysis
• Architecture Decision Records (ADR)
• Troubleshooting AI-assisted CI/CD
• Incident postmortems and operational workflows
Module 5 — Scaling Claude Code & Codebase Health
• Token and context management
• AI-friendly project structures
• Long-term codebase maintainability
• Automation of documentation
• Strategies for AI scalability
• Team-wide engineering workflows
Module 6 — Capstone: Defining Your Claude Code Process
• Designing scalable AI-assisted workflows
• Integrating prompts, commands, and context files
• Designing team AI processes
• Cross-role collaboration models
• Creating workflow blueprints
Module 7 — Advanced Team Prompt Laboratory
• Developing advanced prompt libraries
• Complex role-specific workflows
• Validating prompts in real-world scenarios
• Cross-team collaboration exercises
• Team Prompt Library v2
Requirements
Day 1 — Core Foundations
• Fundamental understanding of software delivery processes
• General knowledge of development, testing, or agile workflows
• Access to Claude is advised for hands-on activities
Day 2 — Advanced Concepts
• Completion of Day 1 (or equivalent prior experience)
• Previous exposure to Claude Code and prompt engineering principles
• Basic proficiency in Git
• Familiarity with CI/CD concepts is suggested
Testimonials (2)
Learning how to prompt Claude and use it to digest all of the data I have available.
Mike Hartleroad - Furniture Row
Course - Claude AI for Data Analysis and Business Intelligence
how to engage with the Office environment and set up repetitive tasks