Back in the XP days if you let your computer for too much time on the hands of an illiterate relative, they would eventually install something and turn Internet Explorer into this https://i.redd.it/z7qq51usb7n91.jpg.
Now the security implications are even greater, and we won't even have funny screenshots to share in the future.
It is my experience that most of these business domain experts snore the moment you talk about anything related to the difficulties of creating software.
Until a few months ago, domain experts who ciuldn't code would "make do" with some sort of Microsoft Excel Spreadsheet From Hell (MESFH), an unholy beast that would usually start small and then always grow up to become a shadow ERP (at best) or even the actual ERP (at worst).
The best part, of course, is that this mostly works, most of the time, for most busineses.
Now, the same domain experts -who still cannot code- will do the exact same thing, but AI will make the spreadsheet more stable (actual data modelling), more resilient (backup infra), more powerful (connect from/to anything), more ergonomic (actual views/UI), and generally more easy to iterate upon (constructive yet adversarial approach to conflicting change requests).
We have monthly presentations at my job and the business folk are really leaning into AI. The biggest win so far are them being able to generate new user experiences and get them into figma by themselves. They're able to test a design, get it into figma, generate some code, and get it in front of users without a developer or designer at all. It's not perfect but the tests show what we need to focus on vs what falls flat when put in front of users. It's very impressive and I'm proud of them.
Super interesting. I don't know why, but something about this comment made something click for me, as an "AI fatigued" engineer.
From the view you describe, it seems AI just lets you experiment faster, when all you want to do is experiment. You find product market fit easier, you empower designers more, etc. Much easier to iterate and find easy wins from alternative designs - as long as your fundamentals work!
Only problem is that you are experimenting in public, so the massive wave of new AI generated features come to the public from everywhere at once. Hence the widespread backlash.
Not to mention, the core job function when you are experimenting is different from what defines a lot of hard technical progress: creating new technologies, or foundational work that others build on, is naturally harder and slower than building e.g. CRUD services on top of an existing stack. Deep domain expertise matters for selling, deep programming expertise matters for stability. I don't know, curious where the line will end up getting drawn.
Yeah, the examples I've seen really focus on experimentation which my employers's platform is designed around. We are constantly testing changes in design and copy and hoping that we get small incremental increases in user attention. AI is really suited for these small changes and it allows us developers to build platforms specific stuff instead of working on baby tweaks. We already had a pretty good system where astute business people could tweak HTML and CSS but now their lives are even easier and they can focus on their actual job which is increasing customer sign ups and attention
Yeah, I think the issue has more to do with the curiosity level of the participant rather than whether they are a business domain expert or a software engineering expert.
There’s a requisite curiosity necessary to cross the discomfort boundary into how the sausage is made.
When I see these types of posts I wonder what those people do all day long that is so important, to the point they can't dedicate 30 minutes to plan and execute some chores.
to be fair, i distinctly remember reading a newspaper article asking what was wrong with taking the time to use the card catalog at the library. There were trying to understand the popularity of google.com
And canvases and paint have existed for even longer, but it needs someone skilled to make use of it.
Stable Diffusion enabled the average lazy depraved person to create these images with zero effort, and there's a lot of these people in the world apparently.
So? At the end of the day, regardless of how skilled one has to be to use it, a tool is not considered morally responsible for how it is used. Nor is the maker of that tool considered morally responsible for how it is used, except in the rare case where the tool only has immoral uses. And that isn't the case here.
> ... "Software Engineer," as a protected term. You can't just call yourself a software engineer.
In my irrelevant opinion, this is good. To me at least, the word engineer represents someone with a big, heavy responsibility on their hands.
I never liked being called an engineer and only have it on my resume because that's the keyword recruiters search on linkedin nowadays. One reason is that I don't have formal education. The other is that, in almost 15 years of experience, I witnessed very few occasions of software receiving proper care to the extent that I could call it "engineering".
I worked for a relatively large company (around 400 employees there are programmers). The people who embraced LLM-generated code clearly share one trait: they are feature pushers who love to say "yes!" to management. You see, management is always right, and these programmers are always so eager to put their requirements, however incomplete, into a Copilot session and open a pull request as fast as possible.
The worst case I remember happened a few months ago when a staff (!) engineer gave a presentation about benchmarks they had done between Java and Kotlin concurrency tools and how to write concurrent code. There was a very large and strange difference in performance favoring Kotlin that didn't make sense. When I dug into their code, it was clear everything had been generated by a LLM (lots of comments with emojis, for example) and the Java code was just wrong.
The competent programmers I've seen there use LLMs to generate some shell scripts, small python automations or to explore ideas. Most of the time they are unimpressed by these tools.
"Researchers Extract Nearly Entire Harry Potter Book From Commercial LLMs"
https://www.aitechsuite.com/ai-news/ai-shock-researchers-ext...
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