APIs API‐docs stacks using AI - terrytaylorbonn/auxdrone GitHub Wiki

1 The API sandbox uses AI (Copilot, ChatGPT) as much as possible (it just makes sense)
2 AI answers specific questions and gives recommendations for my actual code
3 The near term emergence of true AI "copilots"

1 The API sandbox uses AI (Copilot, ChatGPT) as much as possible

The sandbox has experienced a bit of “mission creep”. Originally it was going to focus on API docs. But then I realized I could build APIs, API-docs, and stacks with the help of AI (Copilot, ChatGPT). And I realized that perhaps AI (LLMs) should be a key focus itself.

Example deployment describes how I set up a very basic demo full stack demo (frontend, backend, database; deployed the FE/BE to Render) with extensive use of Copilot (Gdrive doc #238 describes my setup steps; search “COP[“ for copilot prompts).

2 AI answers specific questions and gives recommendations for my actual code

I write tech and API docs that show clearly how to use a product (no TDLR). But docs do not

answer a specific question posed by a reader or
show exactly how to modify the reader's specific code.

Copilot does. Most interesting was just how enjoyable and fast-paced it is to "chat" with Copilot while coding/debugging. You gradually start to realize you are talking with a (very capable) librarian who can navigate the entire online library of mankind's knowledge. At lightspeed and for a ridiculously low cost.

For example, in doc #238 I ask Copilot "is there yet another way to post?”. Copilot analyzes my code and gives me the code to change/insert.

3 The near term emergence of true AI "copilots"

AI SW copilots will be able to do 2 things in the future:

3.1 Near-term

The copilot will take over low-level SW tasks. You simple describe what you need, and the copilot implements it (accurately).

3.2 Long-term

The man-machine interface will evolve. The copilot will accurately interpret non-typing input (verbal, eye movement, etc).

Below: The latest tech for robot tracking of human input.