Obviously, such impact wouldn’t be instantaneous, but I’ve wondered how companies are thinking about this in terms of headcount planning.
From conversations with friends it seems that a common approach is attrition with non-replacement. Companies are using ChatGPT and similar tools to increase productivity, but don’t want to fire a lot of people due to the negative impact on morale on those that remain—and the fact, I assume, it’s not yet clear how much of a productivity gain will occur where, so they don’t even know exactly who to fire yet.
I was wondering what others on HN are seeing. How are your companies approaching this? Is attrition with non-replacement a common strategy? If so, what might that mean for the future job market and unemployment rate?
I’ve got a degree in CS, but haven’t programmed professionally in 15 years.
These new tools have allowed me to create something even larger teams would struggle with on my own in a matter of months.
I’m astonished at the progress I’m able to make without much assistance.
There is often something I’ll need to sit and debug or figure out the name for if I want to ask Google or the LLM helping me code, but that’s about it.
As far as I’m concerned, that means I haven’t needed to hire at least 2-3 full time engineers, be fully bootstrapped, and profitable from day 1 at launch.
Maybe I’ll hire people in the future, but so far the LLMs have replaced engineers, copywriters, designers, and customer support roles. I can handle it all on my own or have the LLM (in the case of customer support) do a decent enough job that I don’t even have to do it anymore.
I do agree that I’m creating something from whole cloth here so it’s not technically replacement as I haven’t let anyone go, but I’m going with the spirit of the question here.
I’ve used tools like https://www.replo.app/ to replicate Ecommerce stores and use LLMs to rewrite copy though. That’s automating a huge amount of work.
I’m using LLMs to help me code backend coding tasks that I need done for backend services and API generation and interfacing.
ChatGPT Plus (GPT-4) with Langchain to have my own custom data and be able to query my own help docs for support.
Leonardo.ai for some images for marketing and ads.
ChatGPT-4 and StableDiffusion API (users bring their own API key) for content generation if desired.
ChatGPT Plus (GPT-4) with Langchain to have my own custom data and be able to query my own help docs for support.
Leonardo.ai for some images for marketing and ads.
ChatGPT-4 and StableDiffusion API (users bring their own API key) for content generation if desired.
For example - I've been writing a presentation on image processing and needed a whole bunch of examples. OpenCV has a ton of blog posts, documentation, stack overflow content for it to have learnt from. So it's been great. I can just ask it for some python code to demonstrate some particular algorithm and it can give me really helpful code and suggestions.
I'm also working on a Rails app at work, again, very mainstream, lots of source material for it to have learnt and generalised from. It's a fantastic pair programmer to talk to about how to approach things. And to be honest, I could not use things like ActiveAdmin without it.
Also, I can't stress enough, if you are using 3.5 and not 4 then you really can't comment on how good ChatGPT is.
And because I've got a lot of experience I can "smell" when things are not right.
If I was a junior or fresh developer, I'm not sure I'd be able to do this. But also, as a junior developer, would I know if a senior developer actually knew what s/he was doing?
I think my peers have started to rely on it too much, so much of my time is battling ideas that hold absolutely no water
Basically right now it's a fairly accurate assistant that you can communicate with via text only. I just don't know how many jobs can be replaced with that.
