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Comment by geodel | Hacker News Reader

Agree. It is just like 2 totally separate groups are arguing.

One very tiny slice of speciality/ rare industries where code is critical but overall small part of project costs. I can see if code / software is 5% of overall cost even heavy use of AI for code part is not moving the needle. So people in this group can feel confident in their indispensability.

Second group is much larger and peddling CRUD / JS Frontends and other copy/paste junk. But as per industry classification they are just part of same Coder/Developer/IT Engineer group. And their bleak prospects is not some future scenario, it is playing out right now with tons of them getting laid off. And whole lot of people with IT degrees, certifications are not finding any jobs in this field.

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After hearing various similarly sounding opinions about CRUD being easy for LLMs, I started tracking how well LLMs handle a standard CRUD Django app I'm familiar with at https://github.com/marcindulak/learning-api-styles-gen-ai-ex....

So far it appears that LLMs still require constant hand-holding, even for a small educational CRUD app.

We've had reasonable effectiveness for CRUD. It's mainly the UI toolkits we use, but the plumbing it can do quite well. It's not 100% vibecoding but certainly a significant accelerator for parts of the job.

I agree with the 2 separate groups theory, but I don't buy that the group that produces "copy/paste junk" is the much larger group. I think in most mega-corps, there is a huge existing code base, there are huge organizational challenges, and there is huge hierarchy with most people not being the junior juniors. 90+% of the work is "not coding." Probably way, way more if we include the middle managers. At startups, there is a lot of "copy/paste junk" but also often a decent amount of push the boundary new stuff. I don't know. I've been in the industry for 8 years now and it's been really rare to see the actual coding being the bottleneck or even the thing that takes the majority of the time.

What makes you feel that a complex frontend would be easier for AI than a non-CRUD backend system?

Hubris.

I don't mean this as a snarky jab. It's coming for anything software. I've used AI to accomplish front end development and reverse engineer proprietary USB hardware dongles in C, then rewriting the C into Rust to get easy desktop GUIs around it. Backend APIs, systems programming, embedded programming, they all seem equally threatened it's just a matter of time. Front end is easy to see in the AI web front ends but everything else is still easy pickings.

> I've used AI to accomplish front end development and reverse engineer proprietary USB hardware dongles in C, then rewriting the C into Rust to get easy desktop GUIs around it. Backend

That is not hard. It’s just tedious and very slow to do manually. The hard part would be about designing a usb dongle and ensuring that the associated software has good UX. The reason you don’t see kernel devs REing devices is not because it’s impossible or that it requires expert knowledge. It’s because it’s like counting sands on the beach.

Whether something is tedious depends on the person and situation. If you're already an expert, you may find a lot of work that goes into your 4th USB device (especially if it's based on yet another chip and bespoke SDK) quite tedious, since lot of it is based on standard requirements/designs that you can't change.

You may also find re-ing stuff not tedious, due to what may be motivating you.

In any case, any work will have some things you just know how to do, or what to do, but previously (before LLM agents) no easy way to plow through them without pressing a lot of keyboard keys over long period of time.

I 100% agree it's coming for everything. I'm just curious what the arguments would be for why frontend would be easier.

As a manager of a full stack team, we've found AI falls short a lot more on front end. It has its weak points on both front and back, but the problems with backend are quite easy to feed back into it -- needs more performance, needs to pass this security audit, needs to deal with xyz system. The problems with frontend are more like this is ugly, it's clunky to use, people don't like it. People without years of frontend experience tend to lack the vocabulary required to get AI to fix it, period, and it ends up going around in loops.

You are describing the toy projects that had us all amazed end of last year. Large, maintainable software that can serve paying customers is in a completely different galaxy.

There's rather a big difference between reverse engineering already working code and forward(?) engineering working code from nothing so that confidence seems misplaced.

It is irrelevant that complex frontend would be easy for AI or not. To me 1) how many unique complex frontends are needed out of total frontends that millions of sites out there need. 2) Will there be increase in need of such frontend engineers so other displaced folks can land a job there.

I think it will be far fewer to have any positive impact on IT engineers' overall job prospects.

But that's equally true for any type of system. Frontend isn't inherently easier than other systems, so i was just wondering why you singled it out. To me AI just seems better at backends and database design

OK, my examples seemed like biased against frontend which was not the intention.

The thrust was overall job prospects for people in software field. It is not that frontend is easy but it is definitely easy to get into. Considering there are far more frontend developers then say C++ system engineers or database designers so in sheer numbers they will be affect more.

Ah okay that's fair. In my country boot camps aren't a thing so frontend devs are rare and good frontend devs even more, so I think it depends on where in the world you are. We got an abundance of java devs here that i fear more for

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