If you have, I don’t think you are like majority of devs (maybe not on HN, but in real life).
You sound lucky to have true, novel problems to solve each day. I’m with many here commenting that this is quite powerful stuff, especially when my day-to-day is writing simple CRUD apps, or transforming data from one format to another within an API, or configuring some new bit of infra or CI/CD.
I’d love to be challenged in some new way, and have access to truly fascinating problems that require novel solutions. But most enterprises aren’t really like that nor do that need that from majority of engineers.
But I still don’t know if I am thrilled by the prospect of being called in to make their monkeypatched, GPT generated project work.
You mean, like almost every outsourcing company pops over? So the type of code that infests companies who hired some sweatshop to do ‘some simple crud’? What’s the difference? Can you see the difference? Besides the gpt code will be far better commented as comments come for almost free with gpt while humans hate writing them.
I’ve seen GPT 3 and 4 hallucinate the most amazing commentary about their own output. Maybe we will get dependable, out of process, guidance at some point about how factual the model thinks it is on an output per output basis but until that point you should trust every LOC and comment exactly the same as code gifted to you by an adversary.
My modest 2¢
After validation.
After getting the changes to disk, documented, actually compiling, etc…
But the biggest problem is that transferring the nuance that is external to the code base is typically really tiresome and lengthy grunt work and again token cap.
I agree with GP - day 2 dev me outclasses it, which means it isn't replacing anyone.
I do agree that there is no boring crud; that’s why gpt or no code tools are not good for full solutions (yet), but it’ll get there I am sure.
Please elaborate.
And, if true, this would be a major news story that Vox or any number of major newspapers would love to write about - so have you approached the media about this? If not, why not?
And you know what? We went from having actual no- or low-code tools (UI builders, forms in Access and FoxPro etc.) to zero no-code tools worth a damn [1]. There was a brief dream of Yahoo! Pipes in mid-to-late 2000s, but it's dead as well.
[1] Except some applications like Unreal Blueprints and similar node-based tools in audio and graphical software
Once you create a general purpose no-code option, it is so complicated and sprawling that the mental burden to understand it is just as great (if not greater) as just using plain old code again. Or conversely, it is so constraining (for the sake of "simplicity") that it can't do anything useful.
They've been promising those since the early 2000's, but I'm still employed.
Some stuff has been automated by Zapier, IFTTT and the like, but most of the systems I'm integrating with don't have public APIs.
Obviously it's a cheeky example, but this would not be the first time in history a previously well-established career was upended in a (relatively) short amount of time. I'm a FAANG dev, I've got skin in the game too and I'm trying to be optimistic, but I can't help but be at least a little worried. From Wikipedia -
"In 1890 there were 13,800 companies in the United States in the business of building carriages pulled by horses. By 1920, only 90 such companies remained."
I don't think we'll be out of the job entirely, but I can definitely imagine the bar being raised and the compensation stagnating as we now have to justify the time and cost of our work compared to the near-free, near-instantaneous output of an LLM.
All that being said, if you've been working since the 2000s, you've got nearly a 20 year head-start on me, so perhaps it makes sense for me to be a bit more worried.
It's same for me. I can learn how to tile my bathroom or repair my car, but i just don't feel like and am happy to pay someone else.
I think all of us here conflate simple with easy. It's simple in theory yes - you get some JSON from service X, maybe tweak service Y that talks to X and then feed it into some front end. In practice even very experienced engineers can take days writing or changing a simple end point or some front end because unclear requirements/bugs/micro service hell/unclear existing code/etc etc.
If it was that easy the pace and quality would have been much higher than what I'm seeing in tech companies.
The hard part here isn’t really the coding - but understanding the business logic and getting it out of the customer what they need.
Often the customer hasn’t even got a good enough grasp on their own business to be able to formulate what they need.
In the short term this ai tools will make the programming part easier but the planning part is still hard.
I also wanted to add about the myriad of incoming data formats that need to be processed and the myriad of data exports that one has to implement for most of those "boring" CRUD apps.
If one hasn't written code that includes comments like "Special case, California does it this way" or "Alberta needs an .xml export, not an .xsl one", with a link to a .pdf spec that points to somewhere on the internet, then he/she hasn't got to know what it really means to write a true and "boring" CRUD app.
I point chatgpt at the general problem and ask about the tech. Check it's answers, drill into specifics. As more questions, get it to write a prototype. (obviously with different parameters to prod- I don't trust open ai not to harvest from my interactions)- ok, now I have proof of concept, if it does the thing I want to do, then go to the engineers and say - hey I want to "X", here is RFC and rough code, .. any problems? if not, how long to push a localised version?
I guess you might call this scripting or prototyping not "real coding" but, damn it's useful not have to fill my head with python etc. Or bore/waste a guy earning 150k for a half day plus to get the basics, then never get my prototype.. because, priority, resources, etc
