Ask HN: Who's regularly using LLMs at work?

For those of you that are, what do you do and what are you using them for?

Coding. Often the grunt work of iterating "what if this" and I get my code and try it, do some more "what if that" and go from there. Not rocket science but the sort of nit picky toil that I'd rather not expend brain on.

I found it really useful for debugging errors. Missing an argument in a graphics call was always an easy fix. As I could rerun my code immediately and get feedback. I’d also use it for “give me a strawman document for …” and I’d then do the hard work by hand to fill it in. I never trusted text output but always worked over significantly. One thing I really enjoyed doing: I had to listen to a three hour presentation on IT governance. I captured the audio, converted to text, and then had copilot or gpt summarize and put together an outline. The audio was really not organized and there was no way I’d make it thru three hrs of note taking. I still spent some time going over the summary and filled in my content. I have a homeless friend who got an unfair parking ticket. I wrote up a short note and used a LLM to grind down the city’s parking enforcement to get the fee dismissed. So it’s good for responding to dumb organizational requests. I see a lot of people passing off auto generated work and it so often shows. To me it signals they are not to serious about what they are doing. I do find if I use it, I can quickly do things mindlessly and not fully understand what I did. I need to balance that as I like to do the work and stretch my brain and sometimes that does not happen.

- I use them to create a vendor order each week. They take my voice and transcribe it into a list to text my sales reps.

- I use them to OCR PDFs from my bank

- I use them as a search/replace tool on CSVs

- I use them to replace Google searches

- I use them to code

- I'm trying to use them to view (still frames from) cameras periodically

I'll think of more uses, I'm sure. My work is very low tech and simple.

I work in cloud consulting with a focus on app development. But I can do almost any vertical except Big Data/ML (learning that now). I use LLMs in every step of the process.

Anytime we talk to the client on a call we use Gong for text transcription (https://help.gong.io/docs/see-a-call-transcript). After the call is transcribed, it summarizes the call, gives you items to follow up and has chapters as the conversation topic changes.

Once I get all of the documentation, statements of work, any artifacts that we come up with, etc, I use Google’s NotebookLM. I put all of the artifacts in it including transcripts before I came in the project. You can then ask it questions and it will give you answers either with citations to your sources that you included.

I use ChatGPT along with NotebookLM to write the assessments and requirement docs along with a project plan. I’ve been doing this type of writing for awhile before LLMs were a thing so I do a lot of prompt iteration and editing so it sounds like me and not “AI Slop” (https://news.ycombinator.com/item?id=42909042).

After the project is signed, I then become a tech lead.

ChatGPT has been well trained on the AWS SDK for various languages, Terraform , the CDK etc. I use it to write scripts and Lambdas involving AWS. I don’t get a chance to do as much hands on coding as I use to between working with sales and as a tech lead.

I once used it to create a simple Hello World API. I was demonstrating to a Java shop how to deploy APIs to Lambda, ECS (AWS’s Docker orchestration service) and EC2 via Ci/CD. I was upfront with then about not knowing Java. I am a c#/Node/Python guy.

All of the tools I mentioned are specifically approved by my company and we use GSuite as our corporate standard and I think we added the pro version of NotebookLM to each seat a couple of weeks ago.