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 Duration 14 hours

Course Outline

Day 1 Curriculum

Module 1 — Introduction to Claude Code & AI-Assisted Engineering

• Differentiating Claude Code from conventional AI tools
• The role of AI agents in software engineering
• Optimizing productivity and workflows
• The AI-assisted development lifecycle
• Risks, constraints, and the need for human oversight
• Live practical demonstrations

Module 2 — Prompt Engineering Essentials

• Structure of an effective prompt
• Zero-shot versus few-shot prompting
• Iterative prompting methods
• Fundamentals of prompt chaining
• Structured outputs and formatting
• Verifying prompts and improving quality

Module 3 — Prompting for Software Development

• Code generation and refactoring
• AI-assisted debugging
• Generating documentation
• Reviewing pull requests
• Understanding legacy code
• Ensuring safe and maintainable AI-generated code

Module 4 — Prompting for Testing & Quality Assurance

• Generating test cases
• Analyzing edge cases
• Designing automation-ready tests
• AI-assisted defect analysis
• Creating Gherkin and test scenarios
• Quality validation workflows

Module 5 — Prompting for Agile Collaboration

• Writing user stories and acceptance criteria
• Refining requirements
• Supporting agile communication
• Summarizing information for stakeholders
• Assisting with retrospectives
• Preparing for backlog refinement

Module 6 — Responsible AI, Security & Verification

• Managing hallucinations and AI risks
• Maintaining confidentiality and secure prompting
• Principles of AI governance
• Using verification checklists
• Awareness of prompt injection threats
• Responsibilities of human review

Module 7 — Team Prompt Laboratory

• Creating reusable team prompts
• AI workflows tailored to specific roles
• Sharing prompts and conducting peer reviews
• Building the initial version of the Team Prompt Library
• Interactive collaborative exercises

Day 2

Module 1 — Advanced Capabilities of Claude Code

• Using CLAUDE.md for persistent project context
• Automating AI workflows
• Best-of-N generation strategies
• Creating reusable AI commands
• Techniques for context engineering
• AI-assisted engineering processes

Module 2 — Sophisticated Prompt Engineering Techniques

• Chain-of-thought prompting
• Multimodal prompting
• Constraint-based prompting
• Advanced prompt chaining
• Managing large contexts
• Conversational engineering workflows

Module 3 — Version Control, Parallel Development & Multi-Agent Workflows

• Strategies for Git integration
• Parallel AI development workflows
• Using worktrees and isolated AI tasks
• Orchestrating multiple agents
• Implementing human-in-the-loop checkpoints
• Strategies for managing conflicts

Module 4 — Architecture, MCP & Advanced DevOps

• Model Context Protocol (MCP)
• Integrating Claude with external tools
• AI-assisted architectural analysis
• Architecture Decision Records (ADR)
• AI-assisted CI/CD troubleshooting
• Incident postmortems and operational workflows

Module 5 — Scaling Claude Code & Codebase Health

• Managing tokens and context
• Designing AI-friendly project structures
• Ensuring long-term codebase maintainability
• Automating 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 an advanced prompt library
• Complex role-specific workflows
• Validating prompts in real-world scenarios
• Cross-team collaboration exercises
• Team Prompt Library version 2

Requirements

Day 1 — Foundations

• Fundamental understanding of software delivery processes
• General knowledge of development, testing, or agile workflows
• Access to Claude is advised for practical exercises

Day 2 — Advanced Level

• Completion of Day 1 (or comparable prior experience)
• Previous exposure to Claude Code and prompt engineering principles
• Basic proficiency with Git
• Familiarity with CI/CD concepts is recommended

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