Course Overview
AI Driven Development has fundamentally transformed how we design, write, and maintain applications. It is no longer just about code completion; it's about setting up a fleet of specialized AI agents to support the entire development cycle.
In this hands-on training, you will master the methodology required to integrate Claude Code into your daily workflow, harnessing the speed and flexibility of a CLI-based agentic workflow.
Learning Objectives
Tooling Ecosystem
Understand the landscape of code generation models and the difference between IDE tools and CLI assistants like Claude Code.
Custom Agent Mastery
Learn how to create and configure custom agents and skills (slash commands) for both the planning and implementation phases.
Legacy Modernization
Understand strategies for refactoring large codebases and bringing legacy systems up to modern standards.
External Integration
Master the use of Model Context Protocol (MCP) to connect AI to tools like Figma, PlayWright, and Context7.
Course Outline
Introduction & Approaches
- Understanding Vibe Coding and AI-native development
- Tool integration vs. standalone CLI tools such as Claude Code
Core Principles
- Setting up instruction and context files (CLAUDE.md)
- Working with custom agents (slash commands) for plan and implementation
- AI-driven unit test generation strategies
Agentic AI Workflows
- Automating documentation as you code
- Integrating SonarQube and ArchUnit with LLMs
- Refactoring patterns for large codebases
MCP & External Systems
- Design-to-code workflows with Figma
- Automated test generation with PlayWright
- Keeping code in sync with library versions via Context7
Spec Driven Development
- Mapping software specs to automated generation
- Using Spec Driven Development frameworks
Certificate Obtained and Conferred by
Certificate of Completion from Zenika
Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Zenika.
Your Trainer

Michael Isvy
Michael is Head of Engineering with broad experience leading teams that build large-scale software systems and modern engineering platforms. He is especially interested in how AI-augmented development workflows can help teams work more effectively on complex codebases while preserving quality, maintainability and sound architecture.
- Shares practical perspectives on AI-assisted development at scale
- Interested in developer productivity, code quality and architectural integrity
- Helps teams apply modern engineering practices to real delivery environments
What to Prepare
A short technical setup is required before the session. Detailed instructions will be sent to confirmed participants in advance — no preparation is needed at the point of registration.
Fees
| Participant | Standard Fee | Special Rate |
|---|---|---|
| Per participant (per pax) | $1,250 | $900 |

