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Comment by 99954bb63ccc | Hacker News Reader

I feel like individually, if you sat down with literally any reasonable person on the planet they would arrive at and/or agree with the tenor here.

I'd be curious to hear from people well versed in group psychology/dynamics and/or just a lot of leadership/people experience: what leads people to this type of thinking once they get in a group setting? It just... seems endemic at this point.

Obviously nobody here is going to know what I do or don't know, but I'm just increasingly curious what I am not understanding about this type of thing. It seems so obvious, yet that makes me ever more suspect that I'm oversimplifying it, or just totally ignorant about the problem in general.

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It's because the average organization has lots of people who don't care about their own productivity and won't adopt new tools or processes unless forced to. This is true of most new tech - lots of workers had to be forced into using computers - but AI also has some other bumps to cross like lots of people who tried early models and then wrote them off, not realizing how fast they'd improve. And most orgs have no infrastructure or processes for allocating individuals token budgets, and most employees have no experience of properly deploying budgets.

Roll it all together and saying "just use it dammit" has some obvious advantages:

1. It's clear.

2. It's simple.

3. It eliminates all excuses employees might come up with for not using it.

The people at the top of these companies aren't stupid. They might have miscalculated how many tokens people can actually use, but that's very hard to calculate because usage is opaque and tools/processes change on a nearly weekly basis. They will eventually build out processes, tools, social conventions and performance metrics that take into account efficiency of token usage. But this is hard! Most managers aren't really assessed on the precise productivity of their teams, for instance, because productivity is often poorly defined.

> what leads people to this type of thinking once they get in a group setting

Game theory! The downside of being brave vastly outweighs the upside. For the C-suite, there is no cost to herdlike-behavior, regardless of the outcome. However, there is a very high personal downside to being a maverick, and your board later discovers you made the wrong choice against the grain. The upside of being maverick and right is very limited.

Once a behavior has become mainstream, hopping on the bandwagon is no longer individually attributable to decision-makers, but is seen (and reported) as a macro-economic phenomenon: Nadella, Zuckerberg and Bezos didn't overhire - the American tech industry overhired.

we are going through our second AI transformation, the first one didn't work that well because the tools were shit.

Whats happening now and whos driving it is interesting. The CEO has a license for this new tool (think one of the top 4, Qwen Claude, Gemini, openAI) and really likes it. So much so that they (non coder) are making lots of little single page web apps.

The COO is bollocks deep in AI, and is saying that we cannot buy any SaaS products anymore. We must make it ourselves.

The engineering manager has seen this as an opportunity to build out a brand for engineering (its a small department in a medium sized company) by delivering quickly what the large year long efforts cant.

This has formed a slopnexus where PoCs are spun up left right and centre, but there isn't much time or thought going in to making them sustainable.

What started out as a (simple ish) asset management tool, neatly scoped into a deliverable PoC has morphed into a 5 product as one monster.

Its a mess that will either lead to burn out or disaster.

Just...wow. That sounds awful, and I'm sorry for you, but I believe many other companies will or are already following that same path.

And myself being an infrastructure guy that needs to maintain all these PoCs that are now suddenly critical for production, it's the perfect nightmare.

And mind you, that dynamic always existed to a certain degree (laptop on a desk that runs some ugly Python script that does half the work of the BizOps team? Check. GCP account attached to the GSuite running a random instance for finance when the company is 101% on AWS? Check. Spreadsheet with macros that sends emails via Outlook as a mailing list manager? Check.) but at least when you discovered that you could scold them and tell them that we need to migrate this to a proper system because security. But nowadays with vibe-coded internal apps...it's a challenge.

It would be fine if my boss actually followed the docs, or just pointed his agent at the docs.

Whats more annoying is that he changes AI provider lots, so we can never inject rules/skills to make sure he uses the right pathway from the start.

There is probably some opportunity here for a centralized, internal only LLM proxy which injects AGENT.md and skills and permits switching backend providers.

Won’t be canned for going with the herd. I think it’s that simple, even if the herd is running off a cliff.

> what leads people to this type of thinking once they get in a group setting? It just... seems endemic at this point.

Large and fascinating topic I'm researching, very relevant for agentic AI and ML too. One way that groups can fail is that they just don't work to dampen / vote out individual errors properly (see PAC learning, Condorcet). Other kinds of errors only occur in groups, and can occur even when constituents individually aren't actually wrong. Some related stuff is:

https://en.wikipedia.org/wiki/Condorcet's_jury_theorem https://en.wikipedia.org/wiki/Group_polarization https://en.wikipedia.org/wiki/Availability_cascade https://en.wikipedia.org/wiki/Information_cascade

The last is probably the most relevant here and made worse by the negative effects of hierarchy. To quote one section:

> The negative effects of informational cascades sometimes become a legal concern and laws have been enacted to neutralize them. Ward Farnsworth, a law professor, analyzed the legal aspects of informational cascades and gave several examples in his book The Legal Analyst: in many military courts, the officers voting to decide a case vote in reverse rank order (the officer of the lowest rank votes first), and he suggested it may be done so the lower-ranked officers would not be tempted by the cascade to vote with the more senior officers, who are believed to have more accurate judgement;

For token-maxxing, our "senior officers" are just executives, and line workers aren't going to vote. Who is the senior officer for those senior officers? It's not shareholders! It's really the executives of even bigger companies, because that is the actually applicable promotion ladder. It's all kind of obvious, but also a genuinely better explanation than "monkey see monkey do". These are just the simpler things, and there's more gnarly dilemmas in https://en.wikipedia.org/wiki/Common_knowledge_(logic)

Wow, amazing answer! I have a lot of reading and then thinking to do, but if you are documenting your research anywhere, I'd greatly appreciate somewhere to follow it.

Thank you so much! This is why I love HN.

This is a consequence of elements of monopoly power existing in your organization. When you don't have to compete for income you honestly forget how. Then the company becomes a cargo cult of bad ideas driven by managers struggling to differentiate themselves.

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