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Comment by john_strinlai | Hacker News Reader

whats being described is in no way unique to ai.

"In other words, Levie’s theory posits, CEOs don’t really understand processes well enough to know what really can and can’t be automated. But that lack of knowledge doesn’t stop them from acting on their beliefs."

i have been in the workforce for a long time. this "theory" has been theorized since as far back as i can remember. its the premise of undercover boss. its the punchline of many r/maliciouscompliance writing exercises.

the higher up the company you go, the more disconnected you are from the workers on the front line, the less you understand about their needs, and the more likely you are to push for something without understanding the totality of the impact of the decision.

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What's unique to AI is that CEOs now have a robot that supports that disconnect. Our CEO recently announced that he has now started doing frontend programming, by which he meant that he had told ChatGPT to output some HTML. No doubt it also told him how smart and clever his ideas were and what a great engineer he was.

This kind of thing only increases the disconnect between what CEOs think employees do and what they actually do.

maybe the html part is unique to ai, i suppose.

but a c-suite picking up some tool, making a toy example, then declaring “well doing X is super easy, roll it out” (or “change the kpi”, etc.) is something i have seen dozens of times.

HTML is not relevant here. I think the problem is that LLMs are qualitatively different.

"No code" tools are usually just tools. They have the pitfalls you describe, but they aren't ego stroking machines like LLMs.

LLMs not only share the same pitfalls, they also encourage you to make the dumbest things. They will make this CEO believe they are the smartest engineer in the world, "you're building exactly the right product", "you're asking precisely the right questions", etc. Ego stroking when leading you to the abyss is very dangerous.

LLMs roleplay as smart human engineers who constantly tell you you're the smartest being in the multiverse.

As an aside, I see you're referring to Al as merely LLMs, which I appreciate and applaud.

I am thinking of calling them just 'LMs' for short, as they come in varying sizes.

Or even AlMs, just to troll the Al moniker, and how they give alms to the rich.

>something i have seen dozens of times

Me too. But I think AI might be a much more powerful delusion generator.

Some people have surrounded themselves by yes-men instead of LLMs, and it seems to me that it comes to the same thing.

Partially yes, but I think there's a substantial difference: LLMs are like always-on Yes Men that also roleplay as very competent engineers. So if your assistant Joe Sycophant always tells you how great you are, you might become inured to it; deep down you know Joe is just a shmuck. Also, Joe needs to sleep and you might drive him into burning out.

LLMs, however, roleplay as alway available, very capable, very detail-oriented engineers who also happen to be sycophants. And, unlike Joe above, they have no self-preservation and their jobs are not on the line if they royally fuck up. Much more dangerous, in my opinion.

The whole is greater than the sum of its parts. Often you need to disregard the detail and minutiae of existing processes to set a better course. The goal is not to avoid short or even medium term pain or even unintended consequences at a department level, but rather to steer the company in a new direction. Processes should adapt or be thrown out to achieve the new direction.

This is not too dissimilar when you realize a software architecture is holding you back. You don’t try to “save” all the existing functions, modules, layers, etc. but instead are happy to discard or replace them given your top-down vantage point of the system and where it needs to head.

You still need to manage that change to varying degrees. For every organization which can shift on a whim, there are many more which require mitigation. Normally, there are a lot of things carried forward for internal or external reasons. Developers tend to discount the amount of effort from other actors in the system because they don't understand all of their priorities and which map neatly versus not.

And then you go out of business because you were busy rewriting Netscape Navigator while Microsoft was churning out new versions of Internet Explorer.

> whats being described is in no way unique to ai.

Exactly. For decades we've talked about "reality distortion fields" of various CEOs. I'm worked with CEOs that had them.

AI just supercharges the reality distortion field.

Or you answer to somebody else, which is how perpetually cannabilizing next quarters numbers to appease short term shareholders becomes more important than cost savings and using your labor pool time to solve actual problems.

Or when the sales teams bonuses are more important than the margins of the business.

There’s lots of reasons the “wrong work” gets pushed down and it’s not exclusively because “they aren’t listening” as much as “they are listening to someone else who matters more.”

> Or you answer to somebody else, which is how perpetually cannabilizing next quarters numbers to appease short term shareholders becomes more important than cost savings and using your labor pool time to solve actual problems.

If CEOs were actually wrecking their companies in order to get a fake short term boost, they'd be shortly out of business. If a person was sure a CEO was doing that, they'd be making money shorting the stock.

Github? Windows? Ibm? Intel? Boeing?

Github and Windows aren't companies.

A more productive view would be looking at an index of tech companies - try QQQ.

There is a great deal of ruin within a nation - and a company.

Well - the premise is that they will indeed shortly be out of business, because their increasingly slop-coded infra will collapse within the next year or so.

Or if it doesn't, token inflation will kill their profitability.

A lot of people are putting big money on both sides of those predictions, and they can't all be wrong.

Shorting stocks has a very high "you must be at least this right" bar in order to make money. And given the uncapped nature of losses - the market can remain irrational longer than you can remain solvent - you need to also be really correct about how high it'll go before you're right, and also, you're borrowing these shares you've sold, so you're on the hook for the borrow fee and also on the hook for paying dividends paid out to those shares you're borrowing but not holding. Plus you have to pay for the margin loans you're using.

That's a very high set of both static and scaling costs that eat away any profit you made by being nominally correct. Combined with the risk profile... you can't "just" go short a stock.

And yes, you can hedge losses with options or construct complicated options positions to try to hone in on a specific price movement you're anticpating. Now you have to deal with entering and exiting a complicated multi-instrument position without price slippage, AND you have theta decay and volatility-related price movements also eating away at the core money you're making by being nominally right.

Have people made money? Yes, for sure. There's also a lot of dead bodies and people who barely broke even despite theoretically having been right.

It doesn’t wreck the companies though. It just costs more money and tike to accomplish the same task. It’s inefficient.

I have had higher ups that actually understand the products, work flow and have a great grasp on things. Slow to understand things but make well educated and deliberate moves. These folks are are VERY rare however.

It's the same as any other bad information entering the decision loop. In this case they were promised "AI" can do things it cannot. They're having trouble rectifying what they were told versus what they experience.

It's not unique to AI. It's common to many other organizationally risky and dangerous scenarios.

lol just reminds me of the SNL sketch about Kylo Ren undercover boss https://www.youtube.com/watch?v=FaOSCASqLsE

It doesn’t have to be this way.

It’s a by product of tax policies and lax anti-monopoly policies that allows incompetence to thrive. If a company gets too big to fail, then it stops calibrating for competency.

The most effective military leaders in history had a deep understanding of fighting war because they came up through the system and the cost of failure was their death.

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