[gdorsi]

It really depends on what kind and of job you do.

If it's not something very common LLMs could end up generating random code.

Also if you work on something performance critical, you can get inspiration from LLMs, but they often don't write fast code.

[keithnz]

not my experience, they write fast code, and if you ask them to optimize, can pull all kinds of tricks out of the bag. Even with some of the niche stuff I work on, they seem really good.

[mchaver]

Without telling us what kind of code you are talking about it is hard to compare. I would say that is true for CRUD web code because there is so much out there that the LLMs can reference.

[keithnz]

I work on all sorts as we have an IoT product offering.... embedded bare metal systems, web, backend IoT servers, Gateways, APIs, Import/Export Systems, Integrations with Manufacturing systems, accounting systems, Automatic Test Equipment. I've been coding for nearly 50 years now, so pretty experienced. What peoples comments seem to imply to me is that they haven't really gone full agentic coding, where you hone your context, your tools, and how you iterate and test with an AI agent. Where any mistakes an AI makes you make sure it can't do it again, you have it setup so your AI code reviews are honed to focus on the things you care about etc.

[gdorsi]

Software development is a quite vast discipline.

In my experience performance of LLMs can be surprisingly good on things that are not mainstream, like database engineering, and surprisingly bad at mainstream categories approached in an unconventional way.

That said, I'm amazed that you have 50 years of experience and still able to have the mental flexibility to adapt to new development paradigms.

As you imply, this stuff isn't simple to pick up, and is completely different on how we have done our job without AI.

[cbm-vic-20]

> I'm amazed that you have 50 years of experience and still able to have the mental flexibility to adapt to new development paradigms.

This is the root of age discrimination in technology fields.

[gdorsi]

Sorry, I now realize that it could be read like this.

Just to clarify, I meant to share admiration toward a fellow engineer.

I do not think that age implies any hard assumption, usually brings cultural diversity which is good.

[keithnz]

gdorsi , it's not that hard to swap really, because the goal, designing systems, just got easier. I feel AI lets you be a system engineer way better as you can quickly iterate. I have the same kinds of goals in mind, just can do it a heck of a lot quicker.

[keithnz]

hubertdinsk, can't reply directly... but yes lots of niche things, especially in the embedded side, automatic test side. We have a lot of hardware, we control a lot of things, sense a lot of things. There's nothing inherently complicated about it such that AI can't code, in fact you feed AI technical data sheets its insanely useful when writing code against that hardware. It's going to pick up on all the weird nuances. It's great for protocols, especially proprietary ones. Anything with spec sheets are good.

[hubertdinsk]

there's no magic anywhere. At the end of the day the result is 0 and 1 onto memory.

The approach to get there is the differentiate factor. If you are to tell a probabilistic tool to be 99.9999999% correct it would just be silly.

[hubertdinsk]

so not niche at all. You described a bit of everything.

Niche is more like "ISO26262 compliant, response time under 50ms, measured with a oscilloscope with at least 40MHz bandwidth, failure rate less than 10^-7, proven with maths and soak tests". It gets more niche the closer you get to hardware.

Next word prediction will get you laughed out of the room.