🚧 Work in Progress 🚧

Day 1 resulted in getting VSCode installed, along with installing and configuring some key VS Code extensions. A key outcome of that exercise was seeing the incredible power the interactive Jupyter notebook embedded in VSCode, which let’s us instantly verify the output of each line of our code. As we will see during our debugging adventures to come, this is an additional productivity multiplier (on top of the rocket fuel that using AI to help us code).

There are more VSCode extensions and Python libraries to come, but we are intentionally being “incremental” here, taking our time to maximize our focus on AI tools and running code while minimizing the time we spend on configuration and administrative cruft. So let’s see what we can do so far.

Today: OpenAI API

The first AI API we explore is from OpenAI. (NOTE: If your favorite is Google/Deep Mind, Anthropic, or another BigLLM firm, don’t worry. We will get there.)

• Topic 1
• Topic 2
• Topic 3
• Topic 4
• Topic 5

Day 2 Recap

A few sentences here to recap key takeaways from today’ topics.

Resources

Dig deeper into the topics we covered today:

• OpenAI API Docs - The details you need for working with OpenAI’s (rapidly evolving) API
• Resource 2 - Repeat the pattern above (see the .mdx source) for each resource.
• Resource 3 - Repeat the pattern above (see the .mdx source) for each resource.
• Resource 4 - Repeat the pattern above (see the .mdx source) for each resource.
• Day 2 GitHub Repo - Our GitHub repo with today’s code.