The other 3 you literally just get for free as models improve. The "state of the art" of "prompting" changes literally every week. It was loops, then graphs, now its harnesses (and self automating harnesses)? Why are these not just obviated by better models? These are barely skills, and are imo, just the tech equivalent of tabloids advertising 5 minute exercises or pills to get rid of stubborn belly fat. No amount of prompt engineering or graphs or loops could get your previous version of GPT to perform like Fable, and yet somehow Fable can do all of that and more without any random built in "ai engineering skills."

The labor chart for SWEs will look like a slope up as productivity with AI increases, and then past a certain point where AI is like 99% good enough, employment will fall off a cliff. We are already seeing this with junior hiring, and who is to say that AI will magically only ever be as capable as a junior engineer?

maybe they became taxi drivers. But that too will be gone soon.

Can't beat capitalism + technological innovation.

Im mostly speaking about software engineering, but the "juniors" I've seen be hired now are basically the equivalent of mid (maybe even low senior) levels of yesteryear. AI is most certainly raising the bar.

(1) (digital) AGI is a real concept, and will be achieved imminently

(2) AGI will be world (and possibly more) changing.

(3) Anthropic will be the one to do that, or at least capture a large part of it

If you buy into all of these, which I'm assuming a lot of SV does at this point, then its kind of a no brainer to go to OpenAI or Anthropic. And optics wise it seems like Anthropic is "winning" right now, so thats the lab with the talent flow.

If Anthropic actually creates a singleton, contributing to that is way more impactful than being CTO at some random company (though I may disagree that said singleton would treat equity holders any differently).

And how many people do you need for this? There are many roles where people are literally hired for their programming/engineering skill. Modern LLMs _largely_ commoditize that skillset.

There are not that many novel things to do, and even if there are, you don't need too many people to do them as LLMs give you more and more leverage over execution details.

Just look at the writing on the wall, there will be no need for senior SWEs of any type within 1-2 years anyway, and shortly after that we won't need Staff SWEs, etc. People here are way too myopic. AI is progressing very fast. We went from hiring juniors in droves 3-4 years ago to basically proclaiming the death of junior SWEs. Who is to say this won't continue up the ladder?

AI will be good enough to replace all SWEs in any capacity - there is no point in "investing" in rebuilding this ladder when you can just invest in more GPUs (in the case of oai/ant/meta/google/etc). or just pay those aforementioned companies more in tokens if you are a smaller outfit. The cost effectiveness of those tokens will only get better over time, until they are competitive in cost : intelligence when compared to any human SWE.

"Models can code well now but they cant do high level architecture" is just a logical fallacy. Its literally only true in this particular moment in time. But if they can code well, whose to say they wont architect well? And at that point, what do SWEs do? If anything, SWEs are in the critical path of automation for these AI labs anyway, so theres a very strong incentive to automate us out vs other professions, and it'll happen soon. All these random 1-off datapoints of "Fable 5 can't do X very idiosyncratic thing" are completely missing the point. 6 months ago, even attempting that problem with any "tool" would be totally intractable, and now it _just_ writes a slightly subpar solution. You can do some basic extrapolation here, its not that complicated.

Your best bet is to just chose a different career, or, if you still want to be in the software industry, be more enterprising.

The only people who care about code elegance are the people looking at the code, which is orders of magnitude fewer people than those who are _using_ the artifacts of what the code actually represents.

I genuinely don't believe that they sat down in a board room and said "yeah lets specifically release this now before an IPO so we can juice it!" They haven't even announced an IPO date. So is every blog on capabilities before that date just "pumping up the value of the stock before the IPO?"

Places are still hiring juniors, but now the bar for them is just much much higher, because a large portion of the junior level work (i.e, execution on implementation details), is pretty much 80-90% done by some senior + AI at this point, whether people believe it or not. This was certainly the case at the FAANG I was at.

I don't know why this "COVID overhiring" rhetoric is still a talking point. Covid was over 5 years ago at this point, those "overhires" have already left or have been flushed out from all these layoffs. Are you telling me the "COVID" overhiring resulted in such a huge surplus that, 5-6 years later, they are still on the market?

Also filing an S-1 doesn't actually indicate that they intend to go public "immediately," it just gives them the option to go public (probably in the near future).

I dont understand why people here require that every tech ceo to be some professional programmer or engineer. I don't think you _need_ to be that deep in it as the CEO. There are plenty of leaders at OpenAI that already fit the bill.

Sam is good at getting funding, seeing the bigger picture, and rallying towards a cause. That is the job of a CEO. It doesn't matter (imo) that he doesn't know how many parameters the next release will have. All that matters is he knows the impact of the new release and knows who to defer to for actual technical decisions.

So its ironic that these same people are talking about "taste" when they ostensibly have very little.

In a hypothetical world where maybe some AI agents or assistants do the vast majority of random tasks for you, does it matter how pleasing the doordash website looks to you? If anything, it should look "good" to an ai agent so that its easier to navigate. And maybe "looking good" just amounts to exposing some public API to do various things.

UIs are wrappers around APIs. Agents only need to use APIs.

Having read the article, I think I see the author's argument (*). I think "taste" here in an engineering context basically just comes down to an innate feeling of what engineering or product directions are right or wrong. I think this is different from the type of "taste" most people here are talking about, though I'm sure product "taste" specifically is somewhat correlated with your overall "taste." Engineering "taste" seems more correlated with experience building systems and/or strong intuitions about the fundamentals. I think this is a little different from the totally subjective, "vibes based taste" that you might think of in the context of design or art.

Now where I disagree is that

1. "taste" is a defensible moat

2. "taste" is "ai-proof" to some extent

"Taste" is only defensible to the extent that knowing what to do and cutting off the _right_ cruft is essential to moving faster. Moving faster and out executing is the real "moat" there. And obviously any cognitive task, including something as nebulous as "taste," can in theory be done by a sufficiently good AI. Clarity of thought when communicating with AI is, imo, not "taste."

Talking specifically about engineering - the article talks about product constraints and tradeoffs. I'd argue that these are actually _data_ problems, and once you solve those, tradeoffs and solving for constraints go from being a judgement call to being a "correct" solution. That is to say, if you provide more information to your AI about your business context, the less judgement _you_ as the implementer need to give. This thinking is in line with what other people here have already said (real moats are data, distribution, execution speed).

I think there's something a bit more interesting to say about the user empathy part, since it could be difficult for LLMs to truly put themselves in users shows when designing some interactive surfaces. But I'm sure that can be "solved" too, or at least, it can be done with far less human labor than it already takes.

In general though, tech people are some of the least tasteful people, so its always funny to see posts like this.