[times_trw]

No. I've completed projects that have been on the back burner for years in hours. They weren't on the back burner for lack of interest but mainly for lack of expertise in a specific stupid area.

It's not an exaggeration to say that I now do two weeks of programming a night. Of course a lot of times the result gets thrown away because the fundamental idea was flawed in a non-obvious way. But learning that is also worth while.

[Klathmon]

It's revolutionized our in house tooling at work.

No longer do I need to give PR feedback more than a couple times, because we can just ask chatgpt to come up with a lint rule that detects and sometimes auto-fixes the issue. I use it to write or change Jenkins jobs, scaffold out tests, diagram ideas from a monologue brain dump, write alerting and monitoring code, write and clean up documentation.

Most recently I wanted to get some "end of year" stats for the teams, normally it would never have happened because I don't have half a day to dedicate to relearning the git commands, and how to count the lines of code and attribute changes to teams and script the whole process to work across 20 repos.

20 minutes later with chatgpt I had results I could share within the company.

It's just allowed me to skip almost all of the boring and time consuming parts of handling small things like that, and instead turns me into a code reviewer who makes a few changes to make it good enough then pushes it out

[datameta]

Does your company have any considerations for feeding chatGPT source code? Would it not be safer to use a local LLM?

[Klathmon]

Not any more than feeding source code to Github. (I personally feel "source code" is very rarely the "secret sauce" of a company anyway). But where I work we not only have the blessing of the company, we are encouraged to use it because they've clearly seen the benefits it brings.

A local LLM would be preferrable all things equal, but in my experience for this kind of stuff, GPT-4 is just so much better than anything else available, let alone any local LLMs.

[kolinko]

It's safe if you use the OpenAI API, or you have an enterprise chatgpt account - they have the same privacy guarantees as other cloud providers there.

[lifeisstillgood]

Wait what?

ChatGPT does diagrams for you? Writes documentation?

[Klathmon]

Absolutely!

I found a plugin a while back called "AI Diagrams" that generates whimsical.com diagrams for me. Combined with the "speech to text" systems in chatgpt means I can just start babbling about some topic and let it write it all down, collect it into documentation, and even spit out a few diagrams from it.

I generally have to spend like 10 minutes cleaning them up and rearranging them to look a bit more sane, but it's been a godsend!

Similarly I sometimes paste a bunch of code in and tell it to write some starter docs for this code, then I can go from there and clean it up manually, or just tell it what changes need to be made. (technically I tend to use editor plugins these days not copy+paste, but the idea is the same)

Other times I'll paste in docs and have it reformat them into something better. Like I recently took our ~3 year old README in a monorepo that goes over all the build and lint commands and had it rearrange everything into sets of markdown tables which displayed the data in a much easier to understand format.

[Shocka1]

Same here - I feel as though it's turned me into a super programmer. One of my favorite uses is converting a C# model with a bunch of properties into a SQL table along with their corresponding stored procedures. I used to have boilerplate code and would have to copy/paste every property, along with their SQL datatypes. One model might take me 10 to 20 minutes to get translated to a table, and the stored procedures would take me another 20 minutes. Now it's all done in 5 minutes tops, and I'm not having to nitpick datatype issues I may have screwed up in the manual process.