What You'll Learn
A focused hands-on workshop on applying AI-assisted development practices in day-to-day software engineering and DevOps workflows. The course covers how to use GitHub Copilot effectively, how Model Context Protocol (MCP) servers extend workflows, and how teams can use AI safely for implementation, debugging, automation, and documentation.
Curriculum Highlights
- Foundations of AI-assisted development and where it fits in real engineering teams
- GitHub Copilot workflows for code generation, refactoring, debugging, and test creation
- Prompting techniques for better code suggestions and more reliable task execution
- Copilot for DevOps tasks: Dockerfiles, Kubernetes manifests, CI/CD pipelines, Terraform, and scripts
- Using Copilot inside VS Code for repo exploration, fixes, reviews, and developer productivity
- MCP fundamentals: what MCP is, how servers work, and how tools are exposed to AI agents
- Practical MCP use cases for documentation lookup, internal tooling, and operational workflows
- Safe usage patterns: validation, review, security, privacy, and guardrails for enterprise teams
- Real-world scenarios: incident debugging, pipeline troubleshooting, infrastructure changes, and runbook generation
- Live exercises on speeding up development and DevOps tasks with AI assistance
Who Is This For
Developers, DevOps engineers, platform engineers, and engineering teams who want to use GitHub Copilot productively and understand how MCP-based tooling can improve delivery workflows without compromising review quality.
Format
Available as a live 8-hour workshop for corporate teams or focused 1-on-1 mentoring. Best delivered as an interactive session with guided demos and hands-on exercises.