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.

I mean, some of those people undoubtedly like Rush ... make of that what you will.

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.

Maybe, but you still need humans to make that call. The software is still built for humans no matter how much indirection you add.

There is a conceivable day where that is no longer true, but when you have reached that point it is no longer AI.

Yes, if it's not redundant software. The ultimate utility is to a human. Sure, at some point humans stopped writing assembly language and employed a compiler instead, so the abstraction level and interfaces change, but it's all still there to serve humans.

To use your example, do you think humans will want to interact with AI agents using a chat interface only? For most tasks humans use computers today, that would be very unwieldy. So the UI will migrate from the website to the AI agent interface. It all transforms, becoming more powerful (hopefully!), but won't go away. And just how the advent of compilers led to an increase of programmers in the world, so will AI agents. This is connected with Javon's paradox as well.

A little guy who lives in your phone and who's really good at APIs. (And, by that point, hopefully good at keeping track of things, too!)

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.

This paper was released a year ago and was probably part of how google got to 1m context before other labs.

Yes - this means software engineers are likely the first to go, along with other high paying computer jobs.

I know ten people who work across Accounting and Finance in high-level positions who have all told me that in the past few months, the LLM-steam has wore off and they aren't seeing any material benefits.

Nope. Grab a random person off the street and ask them to write Enterprise software using an AI. Good luck with that.

The job will change but it still requires a lot of deep knowledge about software development to be effective with AI.

These are the people getting mortgages and sending kids to private school and whatnot. If their spending power suddenly drops to 0, its probably going to be pretty bad. I wonder what the housing market would look like in these cases.

As soon as a person enters the loop you add a manual sync point that probably doesn't need to be there. I think this is why you are increasingly seeing companies tell their people to be "on the loop" or "out of the loop" with their AI. The less syncing with a person, the better. And I think once this experiment runs its course, we will probably find out that human social interaction matters much less than we thought it did, especially for super transactional things like a corporate job where most of your work is done on a computer.