This assumes that a significant portion of the average white collar worker’s job is amenable to automation.

But most white collar workers I know spend most their time either talking to each other, or thinking real hard about what to say the next time they get together to talk. If that’s generally true then it would suggest that there isn’t much white collar work that LLMs, which are now widely regarded as exceptionally poor communicators, can do particularly well.

You're missing the biggest suggestion from the GP's post: that the key to LLM success is verifiability.

Software has high verifiability through compilers, linters, static analysis, leak/memory corruption detection tools, or the very least, running the program to see if it crashes.

Math (as has been making the headlines recently) has high verifiability through automated theorem provers. Notably some of the non-mechanized math results from LLMs have been demonstrated to be wrong (and presumably many more are being checked; these aren't exactly easy to understand proofs).

Game playing (chess, go, Star Craft, etc.) is similarly verifiable: you get your score and you always know how you did in the end (even if not in the moment).

Making assumptions about LLMs in non-veriable domains is making a claim about LLMs that doesn't match their current capabilities. Maybe they'll get there and maybe they won't; I can speculate as well as you can but we're both guessing, so I'm not sure how much value the speculation has.

> I think LLM's will prove to be useful in any domain where most work happens in front of a computer.

A lot of that work entails work with very little margin for error and hallucinations.

Yeah, I think it's at the level of self-driving Excel.

Now, Excel also makes mistakes while trying to get clever - remember the biologists who had to rename several genes to prevent Excel treating them as dates - but it's also a ubiquitous business tool. And you can combine them. But equally Excel hasn't replaced every white collar job.

Yes, but BI is not a good example of industry.

It's like Software, its value is to be a complement and/or an abstraction of existing businesses. All of that sits on the very basics of the essence of civilization, which is how much things we can get off the soil and what how quickly and effective we can transform it.

Not to be anti-tech, but every new advancement, no matter how next-level, has to sell more of the same goods and services people have been using since the dawn of civilization, and those goods and services need to solve the mundane problems people have been getting since millenia.

I worry about this. Dumping data and getting a report on which actions are based prolly isn’t giving real data.

I say that because I have Claude review code and then review the review and it will point out all the things it got wrong the first time. And I end up having to review it myself. Don’t get me wrong, I’m burning tokens all day and love the legit productivity gains but I don’t see how this replaces everybody in tech for a while.

>He loves being able to just dump in a bucket of seemingly unrelated data, and getting actionable BI from it.

Sorry, just don't trust accurate LLM data analysis even from the latest claude model. Have had some embarrassing bloopers over the last year. It is just better to code a deterministic tool to do the data analysis.

I don't doubt it. Earlier today I got an estimate for the revenue, profit margin, and headcount for a potential supplier of a hardware component to a product I'm working on. It would've taken a couple hours of really tedious work for me to do that with Google translate, a search engine, and various market research sites. The result is I know more what I can expect from that vendor in terms of customization and support.

But those are the kinds of estimates that I can eyeball and be more than 80% certain they are plausible. That won't cut it in a lot of domains.

marketing is one of those domains, if everyone gets better, no gets better in the end

I hope he validates the output, the number of times colleagues have done exactly that and gotten the wrong output is.. well, not an insignificant amount.

Not saying it can't be done, but my recommendation is still "ask your LLM to make a tool that process the data, do not process it via the LLM itself".

> He loves being able to just dump in a bucket of seemingly unrelated data, and getting actionable BI from it.

* what he perceives to be actionable BI.

> BI

Business intelligence

> and getting actionable BI from it.

I’ve always had doubts about the validity of this “actionable BI,” even before it was slop, serving, mostly to serve leadership’s biases and justify their preferred ideas.

If accuracy was never that valuable to begin with then this should not be a problem.

For most businesses, it’s going to be business as usual. By the time businesses see the benefits of AI, their competitors that actually leveraged AI will have pulled too far ahead.

If the original company has distribution, they can likely catch up, but the gap we see between AI-first companies and the companies not utilizing AI will broaden exponentially in the coming years.

And I'm sure the business logic has been validated and tested, the hosting and execution medium has been secured, and hooking up to a curated and vetted internal package manager mirror so as not to get hit with 0-days during a shai hulud-esque attack, and of course the executable is being scanned for vulnerabilities, and as the app needs to evolve in the future it will be able to do so with no problems whatsoever.

If her company has any brains, they'll tell her to stick to her job and not waste time on untested software developed by somebody who has no clue what they are doing.

Yes maybe the long term impact will be there won’t be a technology sector (at least not so dominant as it is now). Instead companies in other industries will have larger technology functions with teams of agents.

So, someone made use of a software creation tool to create software, quickly.

Does that software directly utilize ai?

We've heard of "Shadow IT" now we have "Shadow SWE" and "Shadow CI/CD".

It used to be that someone wanted unfettered Internet access, and they were disgruntled with the company's firewall or proxy policy, and so they brought in a modem, and hooked it up to their desktop PC, and started dialing out on some analog line that the company didn't even know they had. Then it's all fine for 3 years until some malware gets discovered, and then IT discovers who-all had unauthorized lines that weren't being scanned or filtered at the company firewall. Same thing happens with WiFi APs today, of course.

I was working for a company that really offered no in-house software or tools to run. But my new supervisor was asking me to closely track my time. So I signed up for some SaaS that would let me log activities and track my timeslices, so I could show a graph or table later on and see what I was doing. I used it for a few weeks. It was real effective. But what I realized down the line, was that all the notes I was typing into this 3rd-party SaaS, were revealing company confidential information. And ultimately, I felt very uncomfortable about revealing what I was doing, on an unannounced and private project, and without authorization or even notifying my employer's IT department. So I shut it all down, and I had to do it with pen and paper, but that felt secure enough.

So if people are going to feel empowered by vibe coding their own bespoke apps, I hope their IT department comes down like a ton of bricks, and tells them to knock it off. Because it is not worth the tech debt, support costs, and ultimately the massive security problems and infoleaks. If your employer won't give you what you need in these terms, then maybe it's just not important to them in the first place.

I really love these stories - as a contractor who fixes the badly implemented shadow IT crap

aaaand let me guess? have they assessed whether this tool needs backups? monitoring? resilience? patching? obviously in 5 years time the author would have left leaving NO documentation on a mission critical 'small' app - likely hosted with a shit ton of other mission critical crap

It's MS Access all over again, my future rates are looking good

seriously it's like going back to the 90's

Hasn't this already arrived in the form of decision models like Jev?

This is entirely untrue. Go ask ChatGPT a complex tax question and decide if you need to call your accountant and spend $500 to verify the answer.

"t’s pretty well established already that robots can do a lot of the physical labor that humans do. "

lol

Isn't the point that there aren't many other fields that check these checkboxes? Software is very unique in that it is so easily verifiable and there is a glut of training data.

lots of high quality training data

This seems correct and in fields of knowledge people guard their secre, or it is not easy to extract/document knowledge, or it isn't publicly available.

Is their output code?

the current dynamic is still an engineer manually auditing and signing off on code.

why wouldn’t that work for other high trust industries (law, medicine, government, etc.)

No, most white collar work is ultimately keeping groups of humans in alignment, working on the same thing without stepping all over each other, and working on something that generates value and isn't a total waste of time/money.

The PPTs and emails are just means to an end. But at least you're able to sound all cool and edgy on the internet.

most white collar work is make-believe work i order to make management heirarchy feel powerful.