[Vespasian]

It is better and has become a valuable resource to me (via the API).

Currently it suffers from being very expensive (I blew through my 30€ monthly budget in a few hours of intensive use for coding).

Also it still is very confidently wrong in sometimes subtle but fundamental ways.

My recent example is this:

I had success with developing rust proc macros with it. I don't know much about them but as a developer I can read the generated code just fine.

Yesterday I wanted to code a macro that adds an attribute to fields in an existing struct. It's actually not possible to do that but gpt-4 send me down a wrong track by "fixing" it's bugs when asked to without getting anywhere.

Asking it whether this is even possible is unreliable because in such niche cases it'll flip flop between answers.

Copilot has become a valuable tool and I've learned a lot by using both versions of GPT

[CubsFan1060]

Can you talk a bit about how you use the API for coding? I have API access, but I'm not entirely sure how to use it to great effect. How does it fit into your workflow?

[Vespasian]

Mostly for use cases which are isolated and with a technology I'm not very familiar (like rust proc macros) and which are hard to Google.

I'll give it a system prompt in the spirit of "you assist experts with developing software. Be brief and assume expertise".

I've found it to work well for smaller, contained problems or one off scripts where the alternative would have been to do it manually or not at all. Getting there 80% allows me to start them in the first place.

Another random example: Recently I needed a script to transfer some secrets from one k8s cluster to several others. It took about 3 minutes with GPT 4 and solved the problem within one iteration. There is probably a one liner in bash to do it but I don't know it of the top of my head;)

Copilot massively improved the quality of my logging and commenting