Course :: AI-Assist Coding and Programming workshop

• 2 days

Target Audience

• Developers
• Architects
• Tester/QA Engineers
• Technical Leads

Objectives

• Design effective prompts to guide AI for accurate code generation
• Apply specification-driven and model-driven approaches for software creation
• Use AI assistants (Claude code, GitHub Copilot, Cursor) effectively for planning, coding, and testing
• Integrate AI workflows into IDE and CLI environments for real-world projects

Software requirements

• VSCode and GitHub copilot chat
• Cursor
• Claude code
• Git

Outline

Day 1: AI Foundations, Prompt Engineering & Specification-Driven Development

• Introduction to AI-Assisted Software Development
  • AI in modern software engineering
  • Evolution from autocomplete to intelligent code agents
  • Strengths and limits of AI assistants
  • Best practices for safe and secure use (data privacy, model bias, confidentiality)
• Prompt Engineering for Developers
  • Learn to communicate effectively with AI for programming tasks
  • Structure of a good prompt (context, intent, constraints, output format)
  • Practical workshop
    • Generate boilerplate code from prompt
    • Refine prompts to improve accuracy and performance
    • Debugging via prompt iteration
• Example use cases workshop
  • Web application
  • REST API
• Specification-Driven Development
  • Build software directly from precise functional and technical specs
  • What is Specification-Driven Development (SDD)
  • Using structured formats: Gherkin, YAML, or Markdown specs
  • List of methods and tools
    • IDE instructions and rules
      • GitHub Copilot chat in VS Code
      • Claude Code
      • Cursor IDE
    • Breakthrough Method for Agile Ai Driven Development (BMAD)
    • GitHub Spec-kit
    • Optionals => Kiro, Trae
  • Workshop
    • Create specification
    • Use AI to generate task, code and test cases from specs
    • Refine specs and re-generate until acceptance criteria are met

Day 2: Model-Driven Development

• Model-Driven Development (MDD) with AI
  • Learn how to design, visualize, and generate code from models
  • Introduction to Model-Driven Development (MDD)
    • Conceptual model
    • Domain model
    • Code
  • List of Models
    • API specification with OpenAPI/Swagger
    • Mermaid diagrams (Flow chart, Sequence diagram, Swimlane, State transition)
    • ER diagram with DBML(Database Markup Language)
    • Design for User Interface
  • Generate code from models
• Workshop with mini-project
  • Build, test, and document a simple AI-generated from scratch using
    • Prompt engineering
    • Specification-driven design
    • Model-driven code generation
    • AI-assisted planning, coding, and testing