Vibe Coding: AI-Assisted Development

Vibe Coding: AI-Assisted Development

Duration: 1 Day

Description

AI coding assistants have changed how software gets written, and using them well is now a core developer skill. This practical course teaches developers to get the most from AI-assisted development tools: how to prompt for code effectively, generate and refine implementations, write tests, debug, and review AI-generated code critically. Equal attention goes to the risks, including security, correctness, and over-reliance, so participants leave able to move faster with AI while keeping quality and judgment firmly in their own hands.
Class time is divided between instructor-led discussion (35 percent) and hands-on coding (65 percent).

Audience

Developers of any level who want to use AI coding assistants effectively and responsibly. A practical elective for anyone who writes code.

Objectives

  • Use AI coding assistants effectively in a real workflow
  • Prompt for code, refactoring, and explanations
  • Generate tests and use AI to debug
  • Review and verify AI-generated code critically
  • Recognize security, correctness, and IP risks
  • Balance speed with quality and developer judgment

Prerequisites

Participants should be able to write and read code. The following will help:

  • Working knowledge of at least one programming language
  • Familiarity with a code editor and version control

Course Outline

  • Module 1 – Course Introduction
    • Welcome and objectives
    • How AI-assisted development changes the workflow
    • Promise and pitfalls
  • Module 2 – Working with AI Assistants
    • Prompting for code effectively
    • Generating, refining, and explaining code
    • In-editor workflows and chat-based help
    • Hands-on exercise: build a feature with AI assistance
  • Module 3 – Testing and Debugging
    • Generating and strengthening tests
    • AI-assisted debugging and triage
    • Documentation and code comprehension
    • Hands-on exercise: test and debug with AI
  • Module 4 – Reviewing AI Code Critically
    • Reading and verifying generated code
    • Security and correctness risks
    • Licensing and IP considerations
    • Avoiding over-reliance
  • Module 5 – Course Wrap-Up
    • Key takeaways
    • Building good habits
    • Resources for continued learning