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AI’s impact on engineering jobs may be different than expected

semiengineering.com

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Re: AI’s impact on engineering jobs may be different than expected

#171

Post by instig007 »

jimbo808 wrote: post #163
skydhash wrote: post #157

Earlier quoted context omitted.

The effort to set up e2e tests can be more than just writing the thing. Especially for UI as computers just does not interpret things as humans do (spatial relation, overflow, low to no contrast between elements).

Also, the assumption that you can do ___ thing (tests, some dumb agent framework, some prompting trick), and suddenly magically all of the problems with LLMs vanish, is very wrong and very common.

> Also, the assumption that you can do ___ thing

...

3. profit

4. bro down

Re: AI’s impact on engineering jobs may be different than expected

#172

Post by torginus »

FloorEgg wrote: post #158
shmel wrote: post #133

Earlier quoted context omitted.

> Have we? It feels like a lot of stuff in my life is unnecessarily expensive or hard to afford. We have, yes. If you notice things to be too expensive it's a result of class warfare. Have you noticed how many people got _obscenely rich_ in the last 25 years? Yes, that's where money saved by technology went to.

Are you sure it's class warfare? It may result in class warfare but I am skeptical that's the root cause. My guess is it has more to do with the education system, monetary policy and fiscal policy.

2 well identifiable classes in western societies are landlords vs renters, where the latter is paying a huge chunk of their income to be able to use an appreciating asset of the former.

This class thing is especially identifiable in Europe, where assets such as real estate generally are not cheaper than in the US (with the exception of a few super expensive places), yet salaries are much lower.

Taxes tend to be super high on wages but not on assets. One can very easily find themselves in a situation where even owning a modest amount of wealth, their asset appreciation outdoes what they can get as labor income.

Re: AI’s impact on engineering jobs may be different than expected

#173

Post by torginus »

jimbo808 wrote: post #38
xXSLAYERXx wrote: post #10

Senior dev here 15 years experience just turned 50 have family blah blah. I've been contracting for the last two years. The org is just starting to use Claude. I've been delegating - well copy pasting - into chatgpt which has to be the laziest way to leverage AI. I've been so successful (meaning haven't had to do anything really except argue with chatgpt when it goes off on some tangent) with this approach that I can…

I have read this same comment so many times in various forms. I know many of them are shill accounts/bots, but many are real. I think there are a few things at play that make people feel this way. Even if you're in a CRUD shop with low standards for reliability/scale/performance/efficiency, a person who isn't an experienced engineer could not make the LLM do your job. LLMs have a perfect combination of traits that ca…

I just wanna make the point that I've grown to dislike the term 'CRUD' especially as a disparaging remark against some software. Every web application I've worked on featured a database, that you could usually query or change through a web interface, but that was an easy and small part of the whole thing it did.

Is a webshop a CRUD app? Is an employee shift tracking site? I could go on, but I feel 'CRUD' app is about as meaningful a moniker as 'desktop app'

Re: AI’s impact on engineering jobs may be different than expected

#174

Post by phkahler »

blackguardx wrote: post #126
estimator7292 wrote: post #124

Earlier quoted context omitted.

In my humble opinion, every corporate EDA exec can suck farts through a bendy straw. Altium has to be some of the worst software in existence.

Altium isn't great, but you must not have tried the others...

KiCAD or Horizon EDA?

Re: AI’s impact on engineering jobs may be different than expected

#175

Post by datsci_est_2015 »

xXSLAYERXx wrote: post #10

Senior dev here 15 years experience just turned 50 have family blah blah. I've been contracting for the last two years. The org is just starting to use Claude. I've been delegating - well copy pasting - into chatgpt which has to be the laziest way to leverage AI. I've been so successful (meaning haven't had to do anything really except argue with chatgpt when it goes off on some tangent) with this approach that I can…

How does code review usually go for you? Our org’s bottleneck is often code review, which is how we reduce bus factor and other risks. Getting to the pull request faster doesn’t really save us that much time.

Re: AI’s impact on engineering jobs may be different than expected

#176

Post by abracadaniel »

eitally wrote: post #60
jimbo808 wrote: post #38

Earlier quoted context omitted.

I have read this same comment so many times in various forms. I know many of them are shill accounts/bots, but many are real. I think there are a few things at play that make people feel this way. Even if you're in a CRUD shop with low standards for reliability/scale/performance/efficiency, a person who isn't an experienced engineer could not make the LLM do your job. LLMs have a perfect combination of traits that ca…

There are exceptions to what I'm about to say, but it is largely the rule. The thing a lot of people who haven't lived it don't seem to recognize is that enterprise software is usually buggy and brittle, and that's both expected and accepted because most IT organizations have never paid for top technical talent. If you're creating apps for back office use, or even supply chain and sometimes customer facing stuff, fre…

A potential difference I see is that when internal tools break, you generally have people with a full mental model of the tool who can take manual intervention. Of course, that fails when you lay off the only people with that knowledge, which leads to the cycle of “let’s just rewrite it, the old code is awful”. With AI it seems like your starting point is that failure mode of a lack of knowledge and a mental model of the tool.

Re: AI’s impact on engineering jobs may be different than expected

#177

Post by ares623 »

direwolf20 wrote: post #154
bigfishrunning wrote: post #153

Earlier quoted context omitted.

You are either being disengenuous or you are horribly misinformed. The models that we currently call "AI" aren't intelligent in any sense -- they are statistical predictors of text. AGI is a replacement acronym used to refer to what we used to call AI -- a machine capable of thought.

Every time AI research achieves something, that thing is no longer called AI. AI research brought us recommendation engines, spelling correctors, OCR, voice recognition, voice synthesis, content recognition, and so on. Now that they exist in the present instead of the future, none of these are considered AI.

That's entirely the industry's fault though. They used AI to market those tools. And they continue to do so now.

Re: AI’s impact on engineering jobs may be different than expected

#178

Post by keeda »

simonw wrote: post #19
Swizec wrote: post #9

The main thing to understand about the impact of AI tools: Somehow the more senior you are [in the field of use], the better results you get. You can run faster and get more done! If you're good, you get great results faster. If you're bad, you get bad results faster. You still gotta understand what you're doing. GeLLMan Amnesia is real.

Right: these things amplify existing skills. The more skill you have, the bigger the effect after it gets amplified.

Interestingly, this observation holds even when you scale AI use up from individuals to organizations, only at that level it amplifies your organization's overal development trajectory. The DORA 2025 and the DX developer survey reports find that teams with strong quality control practices enjoy higher velocity, whereas teams with weak or no processes suffer elevated issues and outages.

It makes sense considering that these practices could be thought of as "institutionalized skills."

Re: AI’s impact on engineering jobs may be different than expected

#179

Post by i2km »

firasd wrote: post #15

It's puzzling to me that all this theorizing doesn't just look at the actual effects of AI. It's very non-intuitive For example the fact that AI can code as well as Torvalds doesn't displace his economic value. On the contrary he pays for a subscription so he can vibe code! The actual work AI has displaced is stuff like: freelance translation, graphic illustration, 'content writing' (writing seo optimized pages for G…

Re displacing freelance translation, yes - it can displace the 95% of cases where 95% accuracy is enough. Like you mention though, for diplomatic translations, court proceedings, pacemaker manuals etc you're still going to need a human at least checking every line since the cost of any mistake is so high

Re: AI’s impact on engineering jobs may be different than expected

#180

Post by directevolve »

warmedcookie wrote: post #118

Let's presume / speculate for a moment that companies will only need 1 developer to do the job of 10 developers because of AI. That would also mean 10 developers can do the job of 100 developers. A company that cuts developers to save money whose moat is not big enough may quickly find themselves out-competed by a company that sees this as an opportunity to overtake their competitor. They will have to hire more devel…

Will the modal developer of 2030 be much like a dev today?

Writing software was a craft. You learned to take a problem and turn it into precise, reliable rules in a special syntax.

If AI takes off, we'll see a new field emerging of AI-oriented architecture and project management. The skills will be different.

How do you deploy a massive compute budget effectively to steer software design when agents are writing the code and you're the only one responsible for the entire project because the company fired all the other engineers (or never hired them) to spend the money on AI instead?

Are there ways of factoring a software project that mitigate the problems of AI? For example, since AI has a hard time in high-context, novel situations but can crank out massive volumes of code almost for free, can you afford to spend more time factoring the project into low-context, heavily documented components that the AI can stitch together easily?

How do you get sufficient reliability in the critical components?

How do you manage a software project when no human understands the code base?

How do you insure and mitigate the risks of AI-designed products? Can you use insurance and lower prices if AI-designed software is riskier? Can we quantify and put a dollar value on the risk of AI-designed software compared to human-designed?

What would be the most useful tools for making large AI-generated codebases inspectable?

When I think about these questions, a lot of them sound like things an manager or analyst might do. They don't sound like the "craft of code." Even if 1 developer in 2030 can do the work of 10 today, that doesn't mean the typical dev today is going to turn into that 10x engineer. It might just be a very different skillset.

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