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 Duration 14 hours

Course Outline

Day 1 Curriculum

Module 1 — Overview of Claude Code and AI-Enhanced Engineering

• Comparative analysis of Claude Code against conventional AI utilities
• Application of AI agents in software engineering disciplines
• Optimization of productivity and operational workflows
• Integration of AI assistance across the development lifecycle
• Identification of risks, limitations, and human oversight requirements
• Live technical demonstrations

Module 2 — Core Prompt Engineering Principles

• Structure of effective prompts
• Zero-shot versus few-shot prompting methodologies
• Iterative prompting strategies
• Fundamentals of prompt chaining
• Standardization of output formats and structure
• Validation and quality enhancement of prompts

Module 3 — Prompt Engineering for Software Development

• Code generation and refactoring processes
• AI-assisted debugging techniques
• Automated documentation creation
• Review processes for pull requests
• Interpretation of legacy codebases
• Ensuring safety and maintainability in AI-generated code

Module 4 — Prompt Engineering for Testing and Quality Assurance

• Generation of test cases
• Analysis of edge cases
• Design of tests suitable for automation
• AI-assisted defect analysis
• Creation of Gherkin and test scenarios
• Quality verification protocols

Module 5 — Prompt Engineering for Agile Collaboration

• Formulation of user stories and acceptance criteria
• Refinement of requirements
• Support for agile communication standards
• Preparation of stakeholder summaries
• Assistance in retrospective processes
• Preparation for backlog refinement

Module 6 — Responsible AI, Security, and Verification

• Management of hallucinations and associated AI risks
• Maintenance of confidentiality and secure prompting practices
• Principles of AI governance
• Implementation of verification checklists
• Awareness of prompt injection threats
• Definition of human review responsibilities

Module 7 — Team Prompt Laboratory

• Development of reusable team prompts
• Establishment of role-specific AI workflows
• Peer review and sharing of prompts
• Creation of Team Prompt Library v1
• Interactive collaborative exercises

Day 2

Module 1 — Advanced Capabilities of Claude Code

• Utilization of CLAUDE.md for persistent project context
• Automation of AI workflows
• Best-of-N generation strategies
• Implementation of reusable AI commands
• Context engineering methods
• AI-assisted engineering processes

Module 2 — Advanced Prompt Engineering Techniques

• Chain-of-thought prompting methodologies
• Multimodal prompting approaches
• Constraint-based prompting strategies
• Advanced prompt chaining procedures
• Management of large context windows
• Conversational engineering workflows

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

• Git integration strategies
• Parallel AI development processes
• Use of worktrees and isolated AI tasks
• Orchestration of multi-agent systems
• Implementation of human-in-the-loop checkpoints
• Conflict management strategies

Module 4 — Architecture, MCP, and Advanced DevOps

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

Module 5 — Scaling Claude Code and Codebase Health

• Management of tokens and context
• Development of AI-compatible project structures
• Ensuring long-term codebase maintainability
• Automation of documentation processes
• Strategies for AI scalability
• Organization-wide engineering workflows

Module 6 — Capstone: Defining Your Claude Code Process

• Design of scalable AI-assisted workflows
• Integration of prompts, commands, and context files
• Design of team AI processes
• Models for cross-role collaboration
• Creation of workflow blueprints

Module 7 — Advanced Team Prompt Laboratory

• Development of advanced prompt libraries
• Implementation of complex role-specific workflows
• Validation of prompts in real-world scenarios
• Cross-team collaboration exercises
• Finalization of 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 is recommended for hands-on exercises

Day 2 — Advanced

• Completion of Day 1 or equivalent professional experience
• Prior exposure to Claude Code and prompt engineering concepts
• Basic Git knowledge
• Familiarity with CI/CD concepts is recommended

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