Description

Vibe coding: point your AI buddy at a problem and let it churn out thousands of lines of code.

That’s a recipe for disaster—like using autocomplete to write your entire next email.

Instead, treat AI assistants as tools. You plan, take small steps, stay in control, get feedback, and learn. Done well, you’ll do in hours what once took days. From whipping up a proof of concept to breathing new life into a decade-old codebase, Uberto shows how professionals harness AI to deliver consistent, accurate results.

You’ll learn the small, controlled steps to take, the instructions that set guardrails, the prompts that work, and the workflows that maximize value while minimizing costs—for individuals and for teams.

Don’t just read about it—watch it. Companion videos show these practices in action as Uberto builds both simple and complex applications, handling real-world problems as they arise. See how a professional configures and guides AI tools to get the job done.

How do the best developers amplify their abilities with AI? It’s not magic. It’s process.

• Go beyond vibe coding to quickly prototype games and apps with AI while keeping control of the process.

• Build effective rulesets that keep your AI assistant focused so you can build solid, real-world applications.

• Accelerate learning by using AI to explore unfamiliar technologies and frameworks with confidence.

• Make working on legacy codebases more interesting and productive by letting AI handle boilerplate, refactors, and documentation—so you can focus on design.

• Collaborate smarter as a team with AI integrated into onboarding, reviews, and daily workflows.

Contents and Extracts

Table of Contents

• Foreword
• Preface
  • Why This Book
  • Who This Book Is For
  • How This Book Is Structured
  • Online Resources
  • What’s Next?
• Going with the Vibe
  • Vibe Coding a Game
  • Improving Your Prompts
  • Writing a More Complex Game with AI
  • What Went Wrong
  • Using Specifications to Drive Assistants
  • What We Learned
• Building Securely and Predictably
  • Keep the Edge
  • One Prompt, One Commit
  • An AI with Good Habits
  • Building an Application Following Rules
  • Results and Reflections
  • What We Learned
• Learning by Coding
  • The Inception
  • Shaping the Idea
  • Walking Skeleton
  • Modeling the Domain
  • Developing the Search UI
  • Show PDFs
  • What We Learned
• Working on a Large Codebase
  • Managing Technical Debt
  • Understanding Legacy Code
  • Enhancing Big Code Projects with AI
  • Is It All Worth It?
  • Cheat Sheet for the AI Powered Developer
  • What We Learned
• Collaborating Inside an AI-Powered Team
  • Adopting AI
  • Team Organization
  • Security Risks
  • What We Learned
• Demystifying Large Language Models
  • Attention Is All You Need
  • What Are Large Language Models?
  • Vector Databases
  • Considerations