Posted by signa11 4 days ago
While I sympathize with your loss, this was always going to prevent you from holding down a job, even as a pre-LLM "coder." The majority of us have to work on systems, not just single files or cleanly isolated programs we can hold in our head.
I'm lucky though - as a hybrid engineer/manager, I've been able to lean away from the former and into the latter.
And I've come to notice that humans doing agentic work seem to need more emotional support per unit effort than those doing traditional engineering.
So there are opportunities there. I don't want to spend a second longer than I have to prompting machines - there is zero dopamine loop in that for me, I get more doing housework and at least that makes my wife happy - but I'm happy to support a few other humans engaged in that kind of work.
It's sad though. I used to love dreaming intricate machines into existence and then watching them come to "life", or at least actually start working. That dream seems dead for now, I hope it comes back but I won't hold my breath.
I'm less pessimistic than the author though. There is always room for people who know what they are talking about. Take a deep breath.
In the short term, I have seen a lot of managers and other higher-ups talk about how we do not need to worry about low-level details anymore. In their minds, we are now all designers and architects, so we do not think about the small implementation details that ultimately do matter for performance and reliability.
People who know what they are talking about worry about all of the details from the big picture down to the small scales. We can still operate using abstractions like designers and architects, but we must know enough to choose the right abstractions that account for the concrete details properly. I've discussed this point earlier this year [1] using the tree swing diagram [2].
But what will their day to day look like? Meetings?
Previously, I'd have to work days undisturbed to get important stuff out of the door. There was effort involved to reach an elegant solution that fit business need.
Now I'm a meat bag pressing enter on a "recommended" option Claude already figured out was the best approach.
And how long can that last? We’re expensive meat bags…
If you are constantly thinking claudes approach is the best then perhaps you were not that good of an engineer to start with.
I'm very interested in systems as well, but being less sure about the future (on whether this is something I really need to think about, or whether I'll get opportunities to work much at this level), I started reading about such topics a fair bit less.
It doesn't yet know when I brushed my teeth last, what specific foods in what quantities give me heartburn/indigestion, what that funky smell from my running shoes might be.
It can write pretty good code on a recursive loop when its provided a clear target. It can write better code when it has someone who understand architecture guiding it. It can review code reasonably well as well.
ChatGPT tied to robotics might even be able to do more interesting things!
It does pretty poor on highly specific knowledge where a RAG better supports -- something like Agent Search at GCP or AI Search at Cloudflare. But it can synthesize.
In effect, we've built an amazing library registry and need to up our librarian skills and the skills of people or systems that can use the information the librarian and their system can find.
Knowledge has been available just by asking Google for decades now. The LLM makes it easier but it's a difference of degree not of kind
Until the models are 100% reliable knowledge will be required in order to quickly spot issues and work efficiently with the model to address them.
I do wonder though about the optimizations within it, what could be the most optimal way to achieve such room (ie. knowing which questions to ask)
Yes, learning and tinkering is still really the greatest way to achieve that
but I think what I am talking about can be better simplified with the analogy of a gym: previously what used to be necessary (manual work/labour) but when most people got into information work, even then there was/is a need for it (physical work), then we saw the evolution of machines specifically designed to optimize for it and we got machines specifically designed for this training, which helped push people's body to their absolute limits.
I do wonder if an hyper-optimized environment of learning and for asking questions (or more so knowing the know how on which questions to ask), this whole process might be optimized for it and what that process might would look like is a source of curiosity to me.
A relevant video which talks about similar topics: Bodybuilding for the mind: https://www.youtube.com/watch?v=o0DtxUJ6rAc
I'm not sure how it plays out in 5 or 10 years, but that's how it is now.
> I don’t see myself as a programmer who is also an expert in a niche area; I see myself as exclusively a low-level coder,
> If anyone can point an LLM at slow code and it automatically finds a hot loop and uses a trick it found somewhere on the 'net to vectorize it, there is little point in hiring someone with a focus on that.
We're no longer in an age where this kind of aggressive specialization makes a lot of sense. And, honestly, that's a good thing. The best thing is to have T-shaped knowledge. Go deep in a few areas, shallow in many.
> A human being should be able to change a diaper, plan an invasion, butcher a hog, conn a ship, design a building, write a sonnet, balance accounts, build a wall, set a bone, comfort the dying, take orders, give orders, cooperate, act alone, solve equations, analyze a new problem, pitch manure, program a computer, cook a tasty meal, fight efficiently, die gallantly. Specialization is for insects.
-Robert A. Heinlein
I’m working intensively with LLMs to find out what they can and cannot do and for all the capabilities in there they remain terrible at compressing functionality into few concepts and as a result they produce incoherent (read Fred Brooks on coherent design!), failure-prone products. In other words: I expect that there will be good demand for people who refuse to let code grow beyond something they can keep in their head, even though the means by which one accomplishes this might be different than what you do now.
Hope that there is some solace in this.
It is tempting to extrapolate the fast progress and conclude that everything will be automated soon, but it still appears to me that LLMs have a “spikey profile”: while very good in some areas, they fail completely in many others, with no evidence that this is only a matter of time.
Part of the all-encompassing thief-of-joy grey goo is definitely the oafish, tactless footsoldiers.
Thanks for making me feel old
What I think we're likely to witness here, or at least what AI investors ultimately are hoping to see happen, is the displacement of code as we know it (often already sorely lacking in quality and craft) not by more of the same varieties of code, but a massive profusion of shittier, more homogenous code. It won't have to win by being better; it'll be able to do that by being cheaper alone. And we're frankly kidding ourselves if we think that doesn't mean a profound deskilling and potentially deprofessionalization across the whole class.
I agree but it's also better. On average for most programming tasks I think humans are as "defeated" as coders as we are as chess players.
The machines will not only be as good or better than you at the DB design, the business logic, the performance critical algorithms, the UX, the performance tweaks, the accessibility standards, security holes, browser compatibilities, laws and regulations and whatever else you need to make the whole solution.
It will also write user manuals in any language, and rewrite them when needed even on a friday evening. It absolutely will not stop, ever, until you are DE...wait, I mean DONE!
So the situation for coders is even worse than it was for the weavers. The machine delivers not only cheaper and faster, but also better. :-/
If the job involves mostly working on a computer, it will be probably gone in 10-20 years.
It's a catch-22 for the companies as well, since white collar work is presumably done because a company has customers, and most of their customers are white collar workers. At least in the US and Europe.
I don't think comparing it to the industrial revolution is appropriate, as the political and social conditions were completely different. I think you can compare the disruption that is introduced by artificial intelligence more with the deindustrialization of regions such as the Ruhrgebiet in Germany.
I'm trying to reinvent myself now and learn the other sides of the projects; how to monetize, how to promote my projects, how to "finish them", etc. I understand that's also changing radically since many people are trying the same thing, and with LLMs the market is changing in unpredictable ways, but that's also exciting! I can get so many more things done now that before I just didn't have the time or focus to finish.