How to Use ChatGPT to Write 10X Code - My Workflow (Tutorial)

The Impact of Chat GPT on Developers

In this section, the speaker discusses how chat GPT has changed the way developers build code and how it will impact their future.

The Future of Developers

• Chat GPT has forever changed the way developers build code.

• There will be two types of developers in the future: those who learn to leverage AI and those who don't.

• The bar to become a 10x engineer has dropped tremendously with the use of AI.

Leveraging AI for Productivity

In this section, the speaker explains how to leverage AI to increase productivity as a developer.

Changing Mindset from Builder to Conductor

• To achieve hyper-productivity, you need to change your mindset from being a builder to being a conductor.

• Copilot and Chachi PT can help increase productivity by using AI assistance.

Basic Understanding Needed

• A basic understanding of coding is needed, starting with Python.

• Syntax in Python is similar to reading English.

Understanding File Structure and Context

In this section, the speaker explains why it's important to understand file structure and context when using chat GPT for coding.

Importance of File Structure Knowledge

• It's important to have an understanding of file structure for each language used.

• Naming files and methods well helps compress context for chat GPT inference.

Token Limits Explained

• Tokens are portions of words that limit prompt length.

• GPT 3.5 has about 4,000 tokens while GPT 4 has up to 32,000 tokens.

Building a Chatbot Using OpenAI API

In this section, the speaker explains how to build a chatbot using GPT 3.5 Turbo and Python.

High-Level Plan for Chatbot

• The goal is to build a chatbot that can answer questions from the command line.

• GPT 3.5 Turbo will be used because it's cheap and fast.

• OpenAI API with the Open AI package will be used.

Creating Chatbot Using Visual Studio Code

• Visual Studio Code is used to create the chatbot from scratch.

• The first step is installing the Open AI package.

Changing Directories in Terminal

• Use "ls" command to see all files and directories in current location.

• Use "cd" command to change directories in terminal.

Setting up the Project

In this section, the speaker explains how to set up a new directory and create three files: chatgpt.py, .m file, and requirements.txt.

Creating a New Directory and Files

• To set up the project, create a new directory and navigate to it using the explore button.

• Create three files in the directory: chatgpt.py, .m file, and requirements.txt.

Adding Dependencies

• Add dependencies to the requirements.txt file by copying them from the script.

Adding API Key

• Add OpenAI API key to the .m file by creating a new secret key and pasting it into the file.

Writing Code for ChatGPT

In this section, the speaker explains how to write code for ChatGPT.

Creating Outline of Code

• Copy function from ChatGPT script and paste it into chatgpt.py.

• Replace existing method with copied function in chatgpt.py.

Debugging with ChatGPT

• Update model engine GPT 3.5 turbo in chatgpt.py by copying format from GPT 3.5 Turbo API Docs.

• Paste updated format into chatgpt.py to correct usage for GPT 3.5 Turbo engine.

Setting up Chat GPT CLI

In this section, the speaker sets up Chat GPT CLI and explains how to maintain conversation history.

Setting up Chat GPT CLI

• To set up Chat GPT CLI, import the modules, load the .m file, load the API key, and get OpenAI ready.

• Use two functions to make it work.

• Run the python file by clicking on the play button in the top right corner.

• Type an example prompt such as "write me a 10 word poem about AI" and hit enter.

Maintaining Conversation History

• Copy and paste the whole thing to maintain conversation history.

• Give guidance to Chat GPT when it gets things wrong.

• Prompt it and have a conversation with it about how to accomplish something.

• Chat GPT will keep context pretty well throughout the history of your conversation.

Debugging with Chat GPT CLI

In this section, the speaker walks through an example of debugging with Chat GPT CLI.

Debugging with Chat GPT CLI

• Cause some bugs in your code intentionally.

• Copy error output from Visual Studio Code into chat window for debugging purposes.

• If you notice that you're getting incorrect suggestions over and over again or suggestions with code, test out what works best for you.

• With 3.5 version of chat gpt you might have to provide additional context more often than with 4.0 version.

Extending the Code with ChatGPT

In this section, the speaker discusses how to extend code using ChatGPT and asks for suggestions on what features to add. They receive several suggestions, including conversational context management, multi-user support, rich media support, personalization, timed responses that simulate typing, sentiment analysis, language translation, voice interface integration with external API.

Adding Timed Responses that Simulate Typing

• To implement timed responses that simulate typing using ChatGPT:

• Use the time.sleep function to add a delay before displaying the chatbot's response.

• Import time and random.

• Add the simulate_typing_character method at the top of the code.

• Add the display_response method after simulate_typing_character.

• Copy and paste the main function at the bottom of the code.

Iterating with ChatGPT

• As your code base becomes bigger and more complex, it will be more difficult to provide all the context to ChatGPT. This is okay.

• Take parts of your code that you think are necessary for providing context and paste them back into ChatGPT when necessary.

• The more you use ChatGPT as a coding partner, you'll figure out where its limits are and get better at coding with it over time.

GitHub Copilot X

• The speaker is excited about GitHub Copilot X which combines GitHub Copilot with ChatGPTn1.

• This tool is expected to solve many of the context issues when it's launched.