Generative Development Framework
GDF.ai
  • Intro to GDF-FSE
    • Generative AI, Large Language Models, ChatGPT?
    • Knowledge Areas
    • Access a Chat Based LLM
    • Why GDF?
    • Expectations
  • Limitations
  • Prompting
    • Prompt Patterns
    • Prompt Context
    • Prompt Stores
    • Prompt Operators
    • Prompt Chaining
  • Security
    • Protecting Data
    • Protecting Application Security
    • Protecting Intellectual Property
    • Protection Stores
    • AI Security Assessments and Penetration Testing
    • Social Engineering Testing with AI
  • Subject Knowledge Areas
    • Ideation
      • Identifying a Problem Statement
      • Plan and Prioritize Features
      • Develop User Stories
      • Requirement Gathering
      • Ideation Prompting
      • Ideation Template
    • Specification
      • Specifying Languages
      • Specifying Libraries
      • Specifying Project Structures
      • Specify Schemas
      • Specifying Elements
      • Specifying API Specs
    • Generation
      • Generating UI Elements
      • Generating Mock Data
      • Generating Schemas
      • Generating Parsers
      • Generating Databases
      • Generate Functions
      • Generate APIs
      • Generate Diagrams
      • Generating Documentation
    • Transformation
      • Converting Languages
      • Converting Libraries
    • Replacement
      • Replacing Functions
      • Replacing Data Types
    • Integration
      • Connecting UI Components
      • Connecting UI to Backend
      • Connecting Multiple Services Together
      • Connecting Cloud Infrastructure (AWS)
    • Separation
      • Abstraction
      • Model View Controller (MVC)
    • Consolidation
      • Combining UI Elements
      • Deduplicating Code Fragments
    • Templating
      • Layouts
      • Schemas
      • Project Structures
      • Content Management Systems
    • Visualization
      • General Styling
      • Visual Referencing
      • Visual Variations
    • Verification
      • Test Classes
      • Logging and Monitoring
      • Automated Testing
      • Synthetic Monitoring
    • Implementation
      • Infrastructure
      • DevOps / Deployment
    • Optimization
      • General Optimization
      • Performance Monitoring
      • Code Review
  • Guidance
    • Business Process
    • Regulatory Guidance
  • Generative Pipelines
  • Troubleshooting
    • Client Side Troubleshooting
    • Server Side Troubleshooting
    • Troubleshooting with AI
    • Documentation
    • Infrastructure Engineering
  • Terminology
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  • Knowledge Areas
  • Example Prompts:

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  1. Intro to GDF-FSE

Knowledge Areas

What are the GDF knowledge areas?

PreviousGenerative AI, Large Language Models, ChatGPT?NextAccess a Chat Based LLM

Last updated 3 months ago

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Like any tool or application, knowing how to efficiently use it can drastically affect productivity. Take an image creation application for example, just about anybody can bring it up, start clicking on brushes, and draw a picture. But a vision, expertise in layers, transformations, cutting, selection, and doing it all efficiently is what allows artists to create works of art productively.

When we think about AI generated content, we want to consider the GDF knowledge domains:

Knowledge Areas

These knowledge areas do not have any secret meanings, they are very literal. I believe the best way to think about them in the context of software development is by putting “Using AI for code” in front.

For example:

Using AI for code ideation

Below are detailed prompt examples examples with references to a fictional application I will be be building throughout the documentation, which will be a bicycle rental application.

Example Prompts:

    • What would I need to build a bicycle rental application?

    • What languages are used to build a mobile application?

    • What languages are used to build a web application?

    • Are there any languages that would allow me to build on both web and mobile at the same time?

    • What is react?

    • What is swift?

    • What is kotlin?

    • What are the main parts of an app layout?

    • What libraries are used to build an app interface in react?

    • What software do I need to create a react app on my computer?

    • How do I run a react app on my computer?

    • How to install react in visual studio code?

    • How to install node.js?

    • Create a code sample in react that renders a navigation bar relevant to things a bicycle renting customer might want to do?

    • Create a code sample in react that renders a home page layout to rent a bicycle.

    • Use Chakra UI as the UI library in the code above instead of material-ui.

    • Use NextJS router for routing

    • Convert the navigation bar into a drawer navigation

    • Convert the code sample to NextJS

    • Convert the code to angular js.

    • Replace the navigation items in the NavBar component with the following items

    • Replace the body with some example components for a bicycle renting application

    • Create a code sample that would get a list of bicycles and their locations

    • Import the above code sample into Home component we created earlier to load in the bicycle data.

    • Create new react components using chakra ui for the components you created in the body earlier

    • Separate the navigation items into a separate file with a callout to get the data.

    • Merge the NavBar component and Logo component into a single NavBar component

    • Consolidate the processing of the bicycle data with the function to transform the date into hh:mm MM/DD.

    • create a layout in next.js for header, body, and footer. use this layout to create a contact page.

    • Change the styling of the nav bar to be more like an apple navbar.

    • Make the navigation dynamic and mobile friendly.

    • How do I upload a react app on the web?

    • How do I point a domain name to a react app?

    • Remove any unnecessary comments from the code.

    • Optimize the parsing of the data to be less redundant.

If you are unfamiliar with programming, many of the prompts below may be difficult to understand. By the end of this course you should have a better understanding of these and have the right troubleshooting knowledge to resolve any issues you may run into.

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Security Management
Prompting
Subject Knowledge Areas
Ideation
Specification
Generation
Transformation
Replacement
Integration
Separation
Consolidation
Templating
Visualization
Verification
Implementation
Optimization
Generative Pipelines
terms
Ideation
Generation
Specification
Transformation
Replacement
Integration
Separation
Consolidation
Templating
Visualization
Implementation
Optimization