Course Outline
Day 1 Outline
Module 1 — Introduction to Claude Code & AI-Assisted Engineering
• Comparing Claude Code with traditional AI tools
• The role of AI agents in software engineering
• Optimising productivity and workflows
• Overview of the AI-assisted development lifecycle
• Understanding risks, limitations, and the need for human oversight
• Live practical demonstrations
Module 2 — Prompt Engineering Fundamentals
• Deconstructing an effective prompt
• Understanding zero-shot versus few-shot prompting
• Techniques for iterative prompting
• Basics of prompt chaining
• Generating structured outputs and formatting
• Verifying prompts and improving quality
Module 3 — Prompting for Software Development
• Code generation and refactoring
• Debugging with AI assistance
• Generating documentation
• Reviewing pull requests
• Comprehending legacy code
• Ensuring safe and maintainable AI-generated code
Module 4 — Prompting for Testing & Quality
• Generating test cases
• Analysing edge cases
• Designing automation-ready tests
• Conducting AI-assisted defect analysis
• Creating Gherkin syntax and test scenarios
• Establishing quality verification workflows
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 and secure prompting
• Principles of AI governance
• Using verification checklists
• Understanding prompt injection threats
• Clarifying human review responsibilities
Module 7 — Team Prompt Lab
• Creating reusable team prompts
• Developing role-specific AI workflows
• Sharing prompts and conducting peer reviews
• Building Team Prompt Library v1
• Participating in interactive collaborative exercises
Day 2
Module 1 — Claude Code Advanced Capabilities
• Utilising CLAUDE.md for persistent project context
• Automating AI workflows
• Implementing best-of-N generation strategies
• Creating reusable AI commands
• Applying context engineering techniques
• Establishing AI-assisted engineering workflows
Module 2 — Advanced Prompt Engineering Techniques
• Implementing chain-of-thought prompting
• Utilising multimodal prompting
• Applying constraint-based prompting
• Mastering advanced prompt chaining
• Managing large contexts
• Designing conversational engineering workflows
Module 3 — Version Control, Parallel Development & Multi-Agent Workflows
• Integrating Git strategies
• Facilitating parallel AI development workflows
• Using worktrees for isolated AI tasks
• Orchestrating multi-agent systems
• Incorporating human-in-the-loop checkpoints
• Managing conflict resolution strategies
Module 4 — Architecture, MCP & Advanced DevOps
• Understanding the Model Context Protocol (MCP)
• Integrating Claude with external tools
‣ Conducting AI-assisted architecture analysis
• Documenting Architecture Decision Records (ADR)
• Performing AI-assisted CI/CD troubleshooting
• Analysing incident postmortems and operational workflows
Module 5 — Scaling Claude Code & Codebase Health
• Managing tokens and context limits
• Structuring AI-friendly projects
• Ensuring long-term codebase maintainability
• Automating documentation
• Implementing AI scalability strategies
• Deploying team-wide engineering workflows
Module 6 — Capstone: Define 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
• Engaging in cross-team collaboration exercises
• Finalising Team Prompt Library v2
Requirements
Day 1 — Foundation
• Basic familiarity with software delivery processes
• General understanding of development, testing, or agile workflows
• Access to Claude recommended for hands-on exercises
Day 2 — Advanced
• Completion of Day 1 (or equivalent experience)
• Prior exposure to Claude Code and prompt engineering concepts
• Basic Git knowledge
• Familiarity with CI/CD concepts is recommended
