The Claude Code Expert Workshop

About the Course:

You know how to run Claude Code. Now learn how to run it at production scale across a real .NET engineering workflow. This expert workshop picks up where the Beginners Workshop leaves off and covers the advanced capabilities that separate developers who occasionally prompt an AI tool from engineers who systematically embed it into every phase of their work.  

The morning sessions cover the internals of Claude Code's slash-command system, how to write reusable skills that encode team-specific conventions, and how to compose subagents for multi-step tasks that a single prompt cannot reliably complete. You will also work through Claude Code's Git integration, including automated commit message generation, branch-level code review, and CI/CD hooks that run Claude Code inside a GitHub Actions workflow.  

The afternoon focuses on the MCP (Model Context Protocol) ecosystem: connecting Claude Code to external tools and data sources via MCP servers, working through the official GitHub MCP server lab, and applying Claude Code to the full SDLC, architecture design sessions, design document generation, feature construction, and refactoring legacy .NET code. You will leave with advanced techniques and a practical framework for deploying Claude Code as a genuine team-level productivity multiplier.

Course Objectives:

Upon completing this workshop, participants will be able to:

• Architect multi-step workflows using Claude Code slash commands, custom skills, and subagents
• Write reusable Claude Code skills that encode project-specific conventions and team standards
• Configure and use Claude Code's hook system to automate validation steps during agentic runs
• Integrate Claude Code with Git for automated commit messages, branch reviews, and code history analysis
• Connect Claude Code to external services using MCP servers and work through the GitHub MCP server lab
• Use Claude Code for architecture design sessions, design document drafting, and design-to-code translation
• Apply Claude Code to feature construction, refactoring, and test generation across an ASP.NET Core codebase
• Integrate Claude Code into a GitHub Actions CI/CD pipeline for automated code review and release notes
• Diagnose and avoid common failure modes in advanced Claude Code workflows

Who is the Target Audience?

• Developers who have completed the Claude Code Beginners Workshop or have equivalent hands-on experience
• Senior .NET engineers who have used Claude Code informally and want to build a disciplined, team-scale workflow
• Technical leads and engineering managers designing AI adoption strategies for .NET development teams
• DevOps and platform engineers looking to embed Claude Code into CI/CD pipelines and developer toolchains
• Principal and staff engineers leading AI-powered modernization of legacy .NET codebases
• AI platform engineers building internal developer tooling and automation workflows
• Engineering enablement teams are responsible for organization-wide AI tooling adoption and best practices
• Enterprise architects evaluating how agentic AI fits into large-scale .NET modernization programs
• Solutions architects designing AI-assisted SDLC workflows for distributed engineering organizations
• Engineering directors overseeing developer productivity and AI transformation initiatives
• Software consultants implementing AI-assisted development practices for enterprise clients
• Cloud and infrastructure engineers integrating AI agents into deployment, observability, and release workflows
• Site Reliability Engineers (SREs) interested in AI-assisted operational tooling and automated remediation workflows
• Developer experience (DevEx) engineers creating standardized AI workflows for internal engineering teams
• Internal tooling teams building reusable automation around GitHub, CI/CD, and AI coding systems
• Staff-level engineers responsible for scaling engineering standards across multiple repositories and teams
• Technical program leaders managing AI adoption initiatives within software engineering departments
• Architects and senior developers leading migration projects from legacy .NET Framework systems to modern ASP.NET Core platforms
• Engineering teams implementing AI-assisted code review, automated documentation, and release engineering workflows
• Security-conscious development teams exploring controlled and auditable AI-assisted development patterns
• AI governance and engineering standards committees defining responsible AI coding workflows inside enterprises
• Organizations piloting Model Context Protocol (MCP) integrations with internal tools, APIs, and knowledge systems
• Teams building reusable engineering workflows using hooks, subagents, and custom Claude Code skills
• Developers interested in orchestrating multi-agent development workflows for large or complex repositories
• GitHub Actions power users seeking AI-enhanced automation for CI/CD and release pipelines
• Platform modernization teams are integrating AI tooling into existing enterprise development ecosystems
• Technical innovation groups researching practical applications of agentic coding systems in software delivery
• Engineering productivity specialists measuring and optimizing AI-assisted developer workflows
• Advanced VS Code and JetBrains users looking to integrate AI deeply into IDE-centric workflows
• Teams managing large monorepos that require AI-assisted repository exploration and architecture comprehension
• API and backend platform teams building reusable internal frameworks and engineering templates
• Architects and engineering leads standardizing prompt engineering and context-engineering practices across teams
• Organizations building internal AI coding standards, governance policies, and reusable skill libraries
• Developers interested in design-to-code workflows using AI-assisted architecture and documentation generation
• Teams exploring AI-assisted technical debt reduction and legacy refactoring strategies
• Advanced Git users seeking automated review, commit generation, and branch-analysis workflows with AI agents
• Companies evaluating AI-native engineering practices as part of digital transformation initiatives
• Engineering teams experimenting with autonomous or semi-autonomous software delivery workflows
• Technical educators and corporate trainers teaching advanced AI-assisted software engineering practices
• Innovation labs and R&D engineering teams are prototyping an AI-driven development lifecycle automation
• Developers building internal MCP servers or integrating Claude Code with proprietary enterprise systems
• Cross-functional engineering teams combining development, DevOps, and architecture workflows into unified AI-assisted pipelines
• Teams seeking repeatable enterprise-grade AI workflows rather than ad hoc prompting practices
• Software engineering professionals preparing for staff-plus or AI engineering leadership roles
• Organizations are establishing internal centers of excellence for AI-assisted software development

Basic Knowledge:

• Completion of the Claude Code Beginners Workshop or equivalent hands-on Claude Code experience
• working knowledge of C#, .NET, and Git

Required Accounts:

• Anthropic Console account at console.anthropic.com, API access via paid plan or Claude Pro/Max subscription. Estimated workshop spend: under $5.
• GitHub account with permission to create repositories and install GitHub Apps (required for the MCP server lab).

System Requirements:

• Visual Studio 2022 (latest stable), VS Code (latest), or JetBrains Rider. The Claude Code VS Code extension will be installed during the workshop.
• Windows 10/11 (64-bit), macOS 12 Monterey or later, or Ubuntu 20.04+ / Debian 10+. Windows users should install WSL2 before the workshop.
• RAM: 16 GB minimum; 32 GB recommended if running Docker Desktop alongside your IDE.
• Disk Space: 20 GB free minimum for SDK, tooling, Docker images, and the workshop repository.
• Local administrator rights required to install Claude Code and other tooling.
• A stable broadband internet connection is required throughout. All API calls and lab exercises

Instructor Note:

• The GitHub MCP server lab requires a GitHub account with permission to install GitHub Apps. Participants should have Claude Code installed and authenticated before the session begins. A pre-workshop guide will be distributed one week in advance.