"The only reason to reduce headcount is to remove people who already weren’t providing much value."

I wish corporations really acted this rationally.

At least where I live hospitals fired most secretaries and assistants to doctors a long time ago. The end result? High-paid doctors spending significant portion of their time on administrative and bureaucratic tasks that were previously handled by those secretaries, preventing them from seeing as many patients as they otherwise would. Cost savings may look good on spreadsheet, but really the overall efficiency of the system suffered.

Funny the original post doesn’t mention AI replacing the coding part of his job.

There seems to be a running theme of “okay but what about” in every discussion that involves AI replacing jobs. Meanwhile a little time goes by and “poof” AI is handling it.

I want to be be optimistic. But it’s hard to ignore what I’m doing and seeing. As far as I can tell, we haven’t hit serious unemployment yet because of momentum and slow adoption.

I’m not replying to argue, I hope you are right. But I look around and can’t shake the feeling of Wile E. Coyote hanging in midair waiting for gravity to kick in.

> The only reason to reduce headcount is to remove people who already weren’t providing much value.

There were many secretaries up until the late 20th century that took dictation, either writing notes of what they were told or from a recording, then they typed it out and distributed memos. At first, there were many people typing, then later mimeograph machines took away some of those jobs, then copying machines made that faster, then printers reduced the need for the manual copying, then email reduced the need to print something out, and now instant messaging reduces email clutter and keep messages shorter.

All along that timeline there were fewer and fewer people involved, all for the valuable task of communication. While they may not have held these people in high esteem, they were critical for getting things done and scaling.

I’m not saying LLMs are perfect or will replace every job. They make mistakes, and they always will; it’s part of what they are. But, as useful as people are today, the roles we serve in will go away and be replaced by something else, even if it’s just to indicate at various times during the day what is or isn’t pleasing.

This is a very insightful take. People forget that there is competition between corporations and nations that drives an arms race. The humans at risk of job displacement are the ones who lack the skill and experience to oversee the robots. But if one company/nation has a workforce that is effectively 1000x, then the next company/nation needs to compete. The companies/countries that retire their humans and try to automate everything will be out-competed by companies/countries that use humans and robots together to maximum effect.

> most companies will still have more work to do than resources to assign to those tasks

This is very important yet rarely talked about. Having worked in a well-run group on a very successful product I could see that no matter how many people would be on a project there was alway too much work. And always too many projects. I am no longer with the company but I can see some of the ideas talked about back then being launched now, many years later. For a complex product there is always more to do and AI would simply accelerate development.

Yip, the famous example here being John Maynard Keynes, of Keynesian economics. [1] He predicted a 15 hour work week following productivity gains that we have long since surpassed. And not only did he think we'd have a 15 hour work week, he felt that it'd be mostly voluntary - with people working that much only to give themselves a sense of purpose and accomplishment.

Instead our productivity went way above anything he could imagine, yet there was no radical shift in labor. We just instead started making billionaires by the thousand, and soon enough we can add trillionaires. He underestimated how many people were willing to designate the pursuit of wealth as the meaning of life itself.

[1] - https://en.wikipedia.org/wiki/Keynesian_economics

I feel like this sort of misses the point. I didn't think the primary thrust of his article was so much about the specific details of AI, or what kind of tasks AI can now surpass humans on. I think it was more of a general analysis (and very well written IMO) that even when new technologies advance in a slow, linear progression, the point at which they overtake an earlier technology (or "horses" in this case), happens very quickly - it's the tipping point at which the old tech surpasses the new. For some reason I thought of Hemingway's old adage "How did you go bankrupt? - Slowly at first, then all at once."

I agree with all the limitations you've written about the current state of AI and LLMs. But the fact is that the tech behind AI and LLMs never really gets worse. I also agree that just scaling and more compute will probably be a dead end, but that doesn't mean that I don't think that progress will still happen even when/if those barriers are broadly realized.

Unless you really believe human brains have some sort of "secret special sauce" (and, FWIW, I think it's possible - the ability of consciousness/sentience to arise from "dumb matter" is something that I don't think scientists have adequately explained or even really theorized), the steady progress of AI should, eventually, surpass human capabilities, and when it does, it will happen "all at once".

If there’s more work than resources, then is that low value work or is there a reason the business is unable to increase resources? AI as a race to the bottom may be productive but not sure it will be societally good.

Most of corporate people dont provide direct value…

> 1. Even if LLMs made everyone 10x as productive, most companies will still have more work to do than resources to assign to those tasks. The only reason to reduce headcount is to remove people who already weren’t providing much value.

They have more work to do until they don't.

The number of bank tellers went up for a while after the invention of the ATM, but then it went down, because all the demand was saturated.

We still need food, farming hasn't stopped being a thing, nevertheless we went from 80-95% of us working in agriculture and fishing to about 1-5%, and even with just those percentages working in that sector we have more people over-eating than under-eating.

As this transition happened, people were unemployed, they did move to cities to find work, there were real social problems caused by this. It happened at the same time that cottage industries were getting automated, hand looms becoming power-looms, weaving becoming programmable with punch cards. This is why communism was invented when it was invented, why it became popular when it did.

And now we have fast-fashion, with clothes so fragile that they might not last one wash, and yet still spend a lower percentage of our incomes on clothes than the pre-industrial age did. Even when demand is boosted by having clothes that don't last, we still make enough to supply demand.

Lumberjacks still exist despite chainsaws, and are so efficient with them that the problem is we may run out of rainforests.

Are there any switchboard operators around any more, in the original sense? If I read this right, the BLS groups them together with "Answering Service", and I'm not sure how this other group then differs from a customer support line: https://www.bls.gov/oes/2023/may/oes432011.htm

> 2. Writing code continues to be a very late step of the overall software development process. Even if all my code was written for me, instantly, just the way I would want it written, I still have a full-time job.

This would be absolutely correct — I've made the analogy to Amdahl's law myself previously — if LLMs didn't also do so many of the other things. I mean, the linked blog post is about answering new-starter questions, which is also not the only thing people get paid to do.

Now, don't get me wrong, I accept the limitations of all the current models. I'm currently fairly skeptical that the line will continue to go up as it has been for very much longer… but "very much longer" in this case is 1-2 years, room for 2-4 doublings on the METR metric.

Also, I expect LLMs to be worse at project management than at writing code, because code quality can be improved by self-play and reading compiler errors, whereas PM has slower feedback. So I do expect "manage the AI" to be a job for much longer than "write code by hand".

But at the same time, you absolutely can use an LLM to be a PM. I bet all the PMs will be able to supply anecdotes about LLMs screwing up just like all the rest of us can, but it's still a job task that this generation of AI is still automating at the same time as all the other bits.

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