Patterns of Application Development Using AI
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Patterns of Application Development Using AI

About the Book

"Patterns of Application Development Using AI" is a groundbreaking book that explores the intersection of artificial intelligence (AI) and application development. In this book, Obie Fernandez, a renowned software developer and co-founder of AI-powered consultant platform Olympia, shares his invaluable insights and experiences from a year-long journey of building an AI-powered application.

Through a compelling combination of narrative chapters and practical pattern references, Obie presents a comprehensive guide to leveraging the power of large language models (LLMs) in application development. He introduces innovative patterns such as the "Multitude of Workers," "Self-Healing Data," and "Contextual Content Generation," which empower developers to build intelligent, adaptive, and user-centric applications.

Unlike other books on AI that focus on theoretical concepts or delve into the intricacies of machine learning algorithms, this book takes a pragmatic approach. It provides concrete examples, real-world use cases, and actionable advice on how to integrate AI components and functions into application architectures. Obie shares his successes, challenges, and lessons learned, offering a unique perspective on the practical application of AI in software development.

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  • Categories

    • Artificial Intelligence
    • Software Architecture
    • Ruby on Rails
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About the Author

Obie Fernandez
Obie Fernandez

Obie Fernandez began his career as a professional programmer in the early ’90s. From Java to Ruby, Lean Startup, Serverless, and now AI, Obie’s expertise and forward-thinking attitude has consistently placed him on the bleeding edge of innovation. As the author of "The Rails Way," his contributions to the Ruby on Rails community are widely recognized and respected. Obie’s role as CTO on the founding team of Andela, along with successful entrepreneurial exits, underscores his leadership and business acumen. His latest venture, Olympia, provides AI-powered virtual staffing startup. Obie’s creativity extends into the world of electronic music production and DJ’ing. He has found success in the techno, trance, and progressive house genres, playing at large EDM festivals, and releasing music on reputable labels since 2018. 

Table of Contents

  • Preface
    • About the Book
    • About the Code Examples
    • What I Don’t Cover
    • Who This Book Is For
    • Building a Common Vocabulary
    • Getting Involved
    • Acknowledgments
    • What’s with the illustrations?
    • About Lean Publishing
    • About The Author
  • Introduction
    • Thoughts on Software Architecture
    • What is a Large Language Model?
    • Thinking About Performance
    • Experimenting With Different LLM Models
  • Part 1: Fundamental Approaches & Techniques
  • Narrow The Path
    • How The Path Gets “Narrowed”
    • Prompt Engineering
    • Prompt Distillation
    • The Art of Vagueness: Leveraging LLM’s Generalization Capabilities
    • Raw Versus Instruct-Tuned Models
    • Why Anthropomorphism Dominates Prompt Engineering
    • Separating Instructions from Data: A Crucial Principle
  • Retrieval Augmented Generation (RAG)
    • What is Retrieval Augmented Generation?
    • How Does RAG Work?
    • Why Use RAG in Your Applications?
    • Implementing RAG in Your Application
    • Real-World Examples of RAG
    • Intelligent Query Optimization (IQO)
    • Reranking
  • Multitude of Workers
    • AI Workers As Independent Reusable Components
    • Account Management
    • E-commerce Applications
    • Healthcare Applications
    • AI Worker as a Process Manager
    • Integrating AI Workers Into Your Application Architecture
    • Composability and Orchestration of AI Workers
    • Combining Traditional NLP with LLMs
  • Using Tools
    • What is Tool Use?
    • The Potential of Tool Use
    • The Tool Use Workflow
    • Best Practices for Tool Use
    • Composing and Chaining Tools
    • Future Directions
  • Self Healing Data
    • Practical Case Study: Fixing Broken JSON
  • Contextual Content Generation
    • Key Benefits
    • Implementation
    • Generating Copy for User Interfaces
    • The Importance of User Testing and Feedback
  • Intelligent Workflow Orchestration
    • Business Need
    • Key Benefits
    • Key Patterns
    • Implementing Intelligent Workflow Orchestration in Practice
    • Monitoring and Logging
    • Scalability and Performance Considerations
    • Testing and Validation of Workflows
  • Testing and Validation
    • Defining Clear Expectations
    • Creating Comprehensive Test Cases
    • Handling Edge Cases and Unexpected Behaviors
    • The Null Hypothesis Problem
    • Monitoring and Logging
    • Collaboration and Feedback Loop
  • Generative UI: Personalized Experiences At Scale
    • Defining Generative UI
    • Example
    • The Shift to Outcome-Oriented Design
    • Challenges and Considerations
    • Future Outlook and Opportunities
  • Part 2: The Patterns
  • Prompt Engineering Patterns
    • Prompt Object
    • Prompt Template
    • Prompt Chaining
    • Prompt Rewriter
    • Feedback Loop
    • Query Analyzer
    • Query Rewriter
    • Ventriloquist
  • Discrete Components
    • Predicate
    • Function Dispatcher
    • API Bridge
    • Result Interpreter
    • Virtual Machine
    • Specification and Testing
  • Intelligent Error Handling
    • Contextual Error Diagnosis
    • Intelligent Error Reporting
    • Predictive Error Prevention
    • Self-Healing Error Recovery
    • Personalized Error Communication
    • Adaptive Error Handling Workflow
    • Human In The Loop (HITL)
    • Escalation Pattern
    • Passive Information Radiation Pattern
    • Collaborative Decision-Making Pattern
    • Continuous Learning Pattern
  • Notes

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