Transform Your Development Workflow with GitHub Copilot and Advanced AI Tools Master the future of software engineering through a comprehensive training class designed for modern development teams.

• Duration: Five half-days of 4 hours each (20 hours total). Note that hours are shown in the Central time zone.
• Delivery: Remote (instructor in California; students distributed, class size 6–15)
• Audience: Software developers who are familiar with GitHub and Copilot novices

Who Should Attend

Software developers, technical leads, and engineering managers ready to leverage AI for accelerated development, legacy system modernization, and greenfield project creation. You should have some experience using ChatGPT, Claude, or a similar LLM, plus some familiarity with GitHub Copilot and software development fundamentals.

What You'll Learn

The first three days of AI-Assisted Software Development with Code and GitHub Copilot build a hands-on foundation for developers ready to work smarter with AI.

Day one opens with the big picture — why AI is transforming software development — then moves quickly into GitHub Copilot in VS Code, vibe coding, AI-assisted pull request workflows, and multi-model comparisons. The instructor puts a strong emphasis on AI guardrails throughout the day, covering instruction files, scoped vs. non-scoped instructions, and the distinction between organizational and repository-level configurations.

Day two expands into LLM concepts, GitHub Copilot for teams, safety best practices, and advanced context and model selection techniques. You'll explore prompt files, instruction file creation, and AI-assisted documentation and code analysis, giving you the frameworks to integrate AI responsibly across your entire workflow.

Day three focuses on test automation and code quality — including feature flags, test suites, and testing in production — before moving into the heart of AI customization: comparing development approaches, building custom VS Code Copilot agents, working with GitHub Copilot Skills, and connecting Model Context Protocol (MCP) servers.

Day four puts AI to work on real-world legacy codebases. You'll start with practitioner resources and a grounded understanding of legacy code before learning how to apply AI safely in brownfield environments. A structured AI implementation workflow guides you through writing effective prompts for technical debt, running conformance and gap analyses, and building a prioritized backlog — all with Copilot's assistance. The day wraps with hands-on work addressing technical debt and a multi-model implementation comparison to help you identify the most effective solutions.

Day five centers on Specification Driven Software Development — a structured, AI-first methodology for building new applications from the ground up. You'll start with a getting-started checklist and business requirements, then move through architecture specification using CQRS, technology stack instruction files, and vertical slicing. From there, you'll develop implementation plans with dependency analysis, craft implementation prompts with built-in verification steps, and complete a full basic vertical slice workflow — leaving you with a repeatable, production-ready approach to greenfield development with AI.

Why This Training Matters

The AI development era is happening now. Developers using AI tools report 30–50% productivity gains, but only when used correctly. This training teaches you to harness AI as a force multiplier while avoiding common pitfalls that lead to poor code quality and technical debt.

You'll gain:

• Immediate productivity improvements through proper AI tool usage
• Enterprise-ready governance frameworks for team adoption
• Risk management strategies for production environments
• Template libraries and workflows for ongoing success

Cost Matrix

What's the Tech Stack for this Class?

• IDE: VS Code with the GitHub Copilot Extension
• SCC: GitHub
• Coding languages: C#, TypeScript, Vue.js
• Installation instructions: See this blog.

NOTE: The emphasis is on AI assistance and how to use AI effectively to generate code. The techniques are implementable in any tech stack. You are expected to have a bit of familiarity with VS Code and enough experience with GitHub to be able to clone a repository, but ask if you need help.

Training 5+ developers? Let's customize it.

Our AI-assisted development techniques work with any tech stack—but they're even more powerful when taught using your actual tools and project types. We'll tailor the class to your team's real-world needs.

Reach out to discuss a custom program.