Plan Szkolenia
Day 1 Outline
Module 1 — Introduction to Claude Code & AI-Assisted Engineering
• Claude Code vs traditional AI tools
• AI agents in software engineering
• Productivity and workflow optimisation
• AI-assisted development lifecycle
• Risks, limitations, and human oversight
• Live practical demonstrations
Module 2 — Prompt Engineering Fundamentals
• Anatomy of an effective prompt
• Zero-shot vs few-shot prompting
• Iterative prompting techniques
• Prompt chaining fundamentals
• Structured outputs and formatting
• Prompt verification and quality improvement
Module 3 — Prompting for Software Development
• Code generation and refactoring
• Debugging with AI assistance
• Documentation generation
• Pull request reviews
• Legacy code understanding
• Safe and maintainable AI-generated code
Module 4 — Prompting for Testing & Quality
• Test case generation
• Edge-case analysis
• Automation-ready test design
• AI-assisted defect analysis
• Gherkin and test scenario creation
• Quality verification workflows
Module 5 — Prompting for Agile Collaboration
• User stories and acceptance criteria
• Requirements refinement
• Agile communication support
• Stakeholder summaries
• Retrospective assistance
• Backlog refinement preparation
Module 6 — Responsible AI, Security & Verification
• Hallucinations and AI risks
• Confidentiality and secure prompting
• AI governance principles
• Verification checklists
• Prompt injection awareness
• Human review responsibilities
Module 7 — Team Prompt Lab
• Building reusable team prompts
• Role-specific AI workflows
• Prompt sharing and peer review
• Team Prompt Library v1 creation
• Interactive collaborative exercises
Day 2
Module 1 — Claude Code Advanced Capabilities
• CLAUDE.md and persistent project context
• AI workflow automation
• Best-of-N generation strategies
• Reusable AI commands
• Context engineering techniques
• AI-assisted engineering workflows
Module 2 — Advanced Prompt Engineering Techniques
• Chain-of-thought prompting
• Multimodal prompting
• Constraint-based prompting
• Advanced prompt chaining
• Large-context management
• 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 management strategies
Module 4 — Architecture, MCP & Advanced DevOps
• Model Context Protocol (MCP)
• Claude integrations with external tools
• AI-assisted architecture analysis
• Architecture Decision Records (ADR)
• AI-assisted CI/CD troubleshooting
• Incident postmortems and operational workflows
Module 5 — Scaling Claude Code & Codebase Health
• Token and context management
• AI-friendly project structures
• Long-term codebase maintainability
• Documentation automation
• AI scalability strategies
• Team-wide engineering workflows
Module 6 — Capstone: Define Your Claude Code Process
• Designing scalable AI-assisted workflows
• Combining prompts, commands, and context files
• Team AI process design
• Cross-role collaboration models
• Workflow blueprint creation
Module 7 — Advanced Team Prompt Lab
• Advanced prompt library development
• Complex role-specific workflows
• Real-world prompt validation
• Cross-team collaboration exercises
• Team Prompt Library v2
Wymagania
Day 1 — Foundation
• Basic familiarity with software delivery processes
• General understanding of development, testing, or agile workflows
• Claude access 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
