Course Outline
Day 1 Outline
Module 1 — Introduction to Claude Code & AI-Augmented Engineering
• Comparing Claude Code with traditional AI tools
• AI agents in software engineering
• Optimising productivity and workflows
• The AI-assisted development lifecycle
• Risks, limitations, and the need for human oversight
• Live practical demonstrations
Module 2 — Fundamentals of Prompt Engineering
• Anatomy of an effective prompt
• Zero-shot vs few-shot prompting
• Iterative prompting techniques
• Fundamentals of prompt chaining
• Structured outputs and formatting
• Verifying prompts and enhancing quality
Module 3 — Prompting for Software Development
• Code generation and refactoring
• Debugging with AI assistance
• Generating documentation
• Conducting pull request reviews
• Understanding legacy code
• Ensuring safe and maintainable AI-generated code
Module 4 — Prompting for Testing & Quality Assurance
• Generating test cases
• Analysing edge cases
• Designing automation-ready tests
• AI-assisted defect analysis
• Creating Gherkin syntax and test scenarios
• Workflows for quality verification
Module 5 — Prompting for Agile Collaboration
• Drafting user stories and acceptance criteria
• Refining requirements
• Supporting agile communication
• Preparing stakeholder summaries
• Assisting with retrospectives
• Preparing for backlog refinement
Module 6 — Responsible AI, Security & Verification
• Addressing hallucinations and AI risks
• Maintaining confidentiality through secure prompting
• Principles of AI governance
• Verification checklists
• Awareness of prompt injection attacks
• Responsibilities for human review
Module 7 — Team Prompt Lab
• Constructing reusable team prompts
• Developing role-specific AI workflows
• Sharing prompts and conducting peer reviews
• Creating Team Prompt Library v1
• Participating in interactive collaborative exercises
Day 2
Module 1 — Advanced Capabilities of Claude Code
• Using CLAUDE.md for persistent project context
• Automating AI workflows
• Strategies for best-of-N generation
• Developing reusable AI commands
• Techniques for context engineering
• Implementing AI-assisted engineering workflows
Module 2 — Advanced Prompt Engineering Techniques
• Chain-of-thought prompting
• Multimodal prompting
• Constraint-based prompting
• Advanced prompt chaining
• Managing large contexts
• Engineering conversational workflows
Module 3 — Version Control, Parallel Development & Multi-Agent Workflows
• Strategies for Git integration
• Parallel AI development workflows
• Using worktrees for isolated AI tasks
• Orchestrating multi-agent systems
• Incorporating human-in-the-loop checkpoints
• Strategies for conflict management
Module 4 — Architecture, MCP & Advanced DevOps
• Understanding the Model Context Protocol (MCP)
• Integrating Claude with external tools
• Conducting AI-assisted architecture analysis
• Creating Architecture Decision Records (ADR)
• Troubleshooting CI/CD pipelines with AI
• Managing incident postmortems and operational workflows
Module 5 — Scaling Claude Code & Ensuring Codebase Health
• Managing tokens and context
• Structuring projects for AI efficiency
• Ensuring long-term codebase maintainability
• Automating documentation
• Strategies for AI scalability
• Implementing team-wide engineering workflows
Module 6 — Capstone: Defining Your Claude Code Process
• Designing scalable AI-assisted workflows
• Combining prompts, commands, and context files
• Designing team AI processes
• Establishing cross-role collaboration models
• Creating workflow blueprints
Module 7 — Advanced Team Prompt Lab
• Developing advanced prompt libraries
• Handling complex role-specific workflows
• Validating prompts in real-world scenarios
• Participating in cross-team collaboration exercises
• Finalising Team Prompt Library v2
Requirements
Day 1 — Foundation
• Basic knowledge of software delivery processes
• General understanding of development, testing, or agile workflows
• Access to Claude is recommended for hands-on exercises
Day 2 — Advanced
• Completion of Day 1 (or equivalent professional experience)
• Previous exposure to Claude Code and prompt engineering concepts
• Fundamental Git knowledge
• Familiarity with CI/CD concepts is advisable
