AI-Powered Developer: Build software with ChatGPT and Copilot

AI-Powered Developer
Copyright
dedication
contents
front matter
   preface
   acknowledgments
   about this book
      Who should read this book?
      How this book is organized: A roadmap
      About the code
      liveBook discussion forum
   about the author
   about the cover illustration
Part 1. The foundation
1 Understanding large language models
   1.1 Accelerating your development
   1.2 A developer’s introduction to LLMs
   1.3 When to use and when to avoid generative AI
   Summary
2 Getting started with large language models
   2.1 A foray into ChatGPT
      2.1.1 Navigating nuances with GPT-4
      2.1.2 Charting paths with GPT-3.5
      2.1.3 Navigating the AI seas: From the shores of GPT-3.5 to the horizons of GPT-4
   2.2 Let Copilot take control
   2.3 Let CodeWhisperer speak loudly
   2.4 Comparing ChatGPT, Copilot, and CodeWhisperer
   Summary
Part 2. The input
3 Designing software with ChatGPT
   3.1 Introducing our project, the information technology asset management system
   3.2 Asking ChatGPT to help with our system design
   3.3 Documenting your architecture
   Summary
4 Building software with GitHub Copilot
   4.1 Laying the foundation
      4.1.1 Expressing our domain model
      4.1.2 Favoring immutability
      4.1.3 Decorating our favorite classes
      4.1.4 Adapting a strategy for depreciation
   4.2 Weaving patterns, patterns, patterns
      4.2.1 Paying a visit to our department
      4.2.2 Creating objects in a factory (pattern)
      4.2.3 Instructing the system on how to build
      4.2.4 Observing changes
   4.3 Plugging in ports and adapters
      4.3.1 Hexagonal architecture in review
      4.3.2 Driving our application
      4.3.3 Accessing our data and persisting our changes
      4.3.4 Centralizing (and externalizing) our data access
   Summary
5 Managing data with GitHub Copilot and Copilot Chat
   5.1 Amassing our dataset
   5.2 Monitoring our assets in real time with Kafka
   5.3 Analyzing, learning, and tracking with Apache Spark
   Summary
Part 3. The feedback
6 Testing, assessing, and explaining with large language models
   6.1 Testing, testing … one, two, three types
      6.1.1 Unit testing
      6.1.2 Integration testing
      6.1.3 Behavior testing
   6.2 Assessing quality
   6.3 Hunting for bugs
   6.4 Covering code
   6.5 Transliterating code—from code to descriptions
   6.6 Translating from one language to another
   Summary
Part 4. Into the world
7 Coding infrastructure and managing deployments
   7.1 Building a Docker image and “deploying” it locally
   7.2 Standing up infrastructure by copiloting Terraform
   7.3 Moving a Docker image around (the hard way)
   7.4 Moving a Docker image around (the easy way)
   7.5 Deploying our application onto AWS Elastic Kubernetes Service
   7.6 Setting up a continuous integration/continuous deployment pipeline in GitHub Actions
   Summary
8 Secure application development with ChatGPT
   8.1 Modeling threats with ChatGPT
      8.1.1 Why it matters in today’s development landscape
      8.1.2 How ChatGPT can aid in threat modeling
      8.1.3 Case study: Simulating threat modeling with ChatGPT
   8.2 Scrutinizing application design and identifying potential vulnerabilities
      8.2.1 Evaluating design problems
      8.2.2 Recognizing common vulnerabilities
   8.3 Applying security best practices
      8.3.1 Setting the security mindset
      8.3.2 Continuous security testing
   8.4 Encrypting data at rest and transit
      8.4.1 The importance of data encryption
      8.4.2 Data encryption at rest
      8.4.3 Data encryption in transit
   Summary
9 GPT-ing on the go
   9.1 Motivating theory
   9.2 Hosting your own LLM
      9.2.1 Baselining with ChatGPT
      9.2.2 Asking Llama 2 to spit out an answer
      9.2.3 Democratizing answers with GPT-4All
   Summary
Appendix A. Setting up ChatGPT
   A.1 Creating a ChatGPT account
   A.2 Creating a ChatGPT account with your email address
Appendix B. Setting up GitHub Copilot
   B.1 Installing the Copilot extension into Visual Studio Code
   B.2 Installing the Copilot plug-in in PyCharm
   B.3 Taking your first flight with Copilot
Appendix C. Setting up AWS CodeWhisperer
   C.1 Installing the CodeWhisperer extension into VS Code
   C.2 Installing the CodeWhisperer plug-in in PyCharm
   C.3 Uttering your first words with CodeWhisperer
index