It is too bad Erik Naggum did not live to see the AI era.

All the snark contained within aside, I'm reminded of that ranting blog post from the person sick of AI that made the rounds a little ways back, which had one huge, cogent point within: that the same companies that can barely manage to ship and maintain their current software are not magically going to overcome that organizational problem set by virtue of using LLMs. Once they add that in, then they're just going to have late-released, poorly made software that happens to have an LLM in it somewhere.

I believe you mean this one: https://ludic.mataroa.blog/blog/i-will-fucking-piledrive-you...

Some things should be bronzed so we don’t ever lose them and this is one of them.

Correct. Also love the dramatic reading someone commissioned.

> Once they add that in, then they're just going to have late-released, poorly made software that happens to have an LLM in it somewhere.

Hell, you can even predict where by looking at the lowest-paid people in the organization. Work that isn't valued today won't start being valued tomorrow.

But see the company selling the AI "solution" made money, which is the entire point.

Making money is the Silicon Valley Bro equivalent of mathematical proof.

Sorry, not making money— I meant attracting investment.

AI tech is generally undertested and experimental, yet marketed as solid and reliable.

Speaking as someone who is very critical of the general "raise infinite money and grow grow grow" approach to startups (it's a big part of why my company is bootstrapped [1]), I think there's a really important difference between making money and raising money.

Raising money is about convincing investors that you can solve someone else's problem. Or even more abstractly, about convincing investors that you can convince other investors that you can convince other investors that you can solve someone else's problem. That's enough layers of indirection that signaling games start to overtake concrete value a lot of the time, and that's what gets you your Theranoses and your FTXes and the like. You get into "the market can remain irrational longer than you can remain solvent", or its corollary, "the market can remain irrational long enough for you to exit before it wakes up".

But making money means you are solving a problem for your customer, or at least, that your customer thinks you're solving a problem with no additional layers of indirection. And if we take "making money" to mean "making a profit", it also means you're solving their problem at less cost than the amount they're willing to pay to solve it. You are actually creating net value, at least within a sphere limited to you and your customer (externalities, of course, are a whole other thing, but those are just as operative in non-profitable companies).

I think this is one of the worst things about the way business has done today. Doing business, sustainably and profitably, is an excellent way to keep yourself honest and force your theories to actually hold up in a competitive market. It's a good thing for you and for your users. But business has become so much about gathering sufficient capital to do wildly anticompetitive things and/or buy yourself preferential treatment that we're losing that regulating force of honesty.

[1] see my HN profile for more on that if you care

Incidentally, this just led me to the first case I've found of a wide variety of AIs actually generating the same answer consistently. They almost always said a close synonym for "now I have a solution".

For some AIs, if you ask them to complete it for "Java" and/or "Regexes" first, then they give realistic answers for "AI". But others (mostly, online commercial ones) are just relentlessly positive even then.

Prompting to complete it for "Python" usually remains positive though.

You have 4 problems because the AI made two more of them up!