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AI-Assisted Software Development from Code to Copilot

Revolutionize your software development with GitHub Copilot in this comprehensive remote training for developers, technical leads, and engineering managers. Over five half-day sessions, you will gain hands-on experience mastering AI-assisted coding fundamentals and safe legacy code modernization. Learn to implement enterprise governance, enhance code quality, and boost productivity through practical AI workflows, automated testing, and prompt engineering techniques. Whether you’re looking to modernize existing systems or deliver new features, this class equips you with essential strategies and templates to harness AI effectively while managing risk and technical debt. Register for this course to transform your team’s software engineering approach and stay ahead in the AI-powered development revolution.

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Sign up today and save $ 300!  Only $ 1,300!
(Early bird price is only good until 04/27/2026)

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 Development Fundamentals lay a practical foundation for developers ready to work smarter with AI. Day one dives straight into hands-on coding — setting up tools, building a real C# project using GitHub Copilot, and mastering TDD, CI/CD pipelines, and AI instruction files. Day two broadens the picture with deeper coverage of LLM concepts, prompt engineering, documentation generation, and AI-driven testing strategies, giving you the frameworks to integrate AI responsibly across your entire development workflow. By day three, you're building custom AI agents, defining skills, and connecting Model Context Protocol (MCP) servers — putting you in control of a fully tailored, AI-powered development environment.

Legacy Code Transformation Day four puts AI to work on real-world legacy codebases. You'll learn how to safely assess and protect brownfield code, use AI to identify technical debt — from outdated patterns and security vulnerabilities to missing tests and architectural drift — and build a prioritized backlog in about an hour. Hands-on exercises walk you through implementing fixes, managing pull requests, and comparing AI model outputs to find the most effective solutions.

Greenfield Development The final day brings it all together with an AI-first approach to greenfield development. You'll follow a structured workflow — from generating business requirements and building tech stack instruction files to architecting with vertical slices and implementing features with AI-generated prompts. Live coding exercises walk you through the full cycle: implementation, pull requests, and AI-assisted code review — leaving you with a repeatable, production-ready methodology for building new applications with AI from the ground up.

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 Price grid

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.

At a Glance:

Monday, May 18, 2026 - 10:00AM to Friday, May 22, 2026 - 3:30PM (all times US Central Time)
Price: $1,600
Sign up today and save $ 300!  Only $ 1,300!
(Early bird price is only good until 04/27/2026)

Agenda:

Monday, May 18, 2026

AI Assisted Software Development

  • What's the Big Deal About AI?
  • The AI Revolution in Software Development

Intro to Copilot

  • Hands-On with GitHub Copilot in VS Code

AI Assistance in Action

  • Vibe Coding: Collaborative AI Development
  • AI-Assisted Pull Request Workflows
  • Multi-Model Implementation Comparison
  • Evergreen Software Core Principles

Adding AI Guardrails

  • Adding AI Guardrails
  • Instruction Files
  • Scoped vs Non‑Scoped Instructions
  • Instruction File applyTo Patterns
  • Core Instruction Files
  • Organizational vs. Repository Instruction Files

Tuesday, May 19, 2026

LLMs

  • Large Language Models

Copilot for Teams

  • GitHub Copilot for Teams

Safety Measures and Best Practices

  • Safety Measures and Best Practices

Models and Context

  • Model Selection and Comparison
  • Advanced Context Techniques

Guardrails and Prompt Files

  • Scoped vs Non‑Scoped Instructions
  • Prompt Files
  • Creating Instruction Files from Prompts

AI Assisted Documentation

  • Documentation Generation and Code Analysis
  • Code Explanation and Analysis

Wednesday, May 20, 2026

Test Automation and Code Quality

  • Test Automation and Code Quality
  • Creating Robust Testing Frameworks
  • Feature Flags and Test Suites
  • Testing in Production

Instructions vs Prompts vs Custom Agents

  • Comparing AI Development Approaches

Custom Agents

  • VS Code Copilot Agents Overview
  • Custom Agents Overview
  • Custom Agent Best Practices
  • Controlling Copilot Instruction Files

Skills

  • GitHub Copilot Skills: A Practical Introduction

MCP

  • Model Context Protocol Servers

Thursday, May 21, 2026

AI Practitioner Resources

  • AI Practitioner Resources

Brownfield Software Development

  • Understanding Legacy Code
  • Safe Brownfield Coding

AI Implementation Workflow

  • AI Implementation Workflow
  • Effective Prompts for Technical Debt

Building a Backlog

  • Conformance and Gap Analysis
  • Building a Technical Debt Backlog
  • Implementation Plan Prioritization

Addressing Technical Debt

  • Addressing Technical Debt with Copilot

Multi-Implementation Comparison

  • Multi-Model Implementation Comparison

Friday, May 22, 2026

Specification Driven Software Development

  • Getting Started Checklist
  • Starting with Requirements

Architecture Specification

  • CQRS Architecture

Technology Specification

  • Technology Stack Instruction Files

Implementation Specification

  • Vertical Slicing Architecture Introduction

Implementation Planning

  • Vertical Slice Implementation Plans
  • Dependency Analysis and Planning

Implementation Prompts

  • Implementation Prompts and Verification

Vertical Slice Implementation

  • Basic Vertical Slice Workflow