Comment by dangus
3 hours ago
I really don’t understand on the customer side of B2B why so many companies actively encouraged AI tooling costs.
I can understand it from the side of the companies selling tokens and AI hardware. I don’t understand the race to spend more on internal tools.
I’ve been sitting around waiting for my company to buy a number of necessary bits of tools. They cheap out on every solution imaginable. Datadog is too expensive, let’s buy a cheap solution that costs us months of setup time. Configuration management is too expensive, let’s use the free version with no audit trail or dashboard.
But everyone…in the entire company…gets multiple AI tool subscriptions.
I don’t remember investors being this stupid at any other point. I don’t recall investors pressuring my company to use blockchain or NFTs.
The logic is quite simple. Management thinks that AI can improve productivity, but knows that there will be some resistance and some learning curve. So they force people to use it so that people can 1. develop their skills and workflow and 2. find out where it is useful 3. find out what needs to be improved to make it useful.
As a more obvious example consider that cars were just invented and the post office management thinks that they could improve performance of letter carriers. But right now cars are slow, break down a lot and there isn't much infrastructure for them. Lots of letter carriers will (rightly) think that it is a waste of time because they need to get in, stop, park between every house and they break down so often it isn't worth it and half of their route is unsuitable for a car anyways. But if cars are forced for a while they will find out what routes work well for cars and which don't, improve the cars and related infrastructure to make cars more effective and other improvements to unlock more productivity.
So yes, right now management is wasting money on cars and gas for no increased productivity. And yes, measuring how much gas each employee uses and encouraging to use more is obviously stupid in isolation. But the idea is to force adoption to iron out the kinks and find out where it can improve productivity. It is basically funding a research project.
IMO, the root of all of this is the almost total inability for most managers, and most eng orgs to measure individual engineer output in any useful way. And in particular in a way that lets you reliably compare engineers to each other.
Despite decades of the industry telling itself that we "pay for performance" or whatever, that has never been the case because we can't really measure performance very well. Where I have seen it done ok (not great, just ok), it was massively labor intensive and did not last, and was only done fully when considering promotion.
So, as you observe, now we have some new technique that managers are sure will increase performance by 50+%, if only people would use it. They can't just raise their expectations of performance by 50%, because they can't measure performance to within 50%! So, they measure the thing they can: token consumption.
That would be sensible if you were a car maker and not in the business of delivering posts. You’re tanking your core business, just to do what the developer of the tool should be doing (ensuring the usefulness and reliability of the tool).
I’m all for a trial run, but it needs to be done like any research experiment. With a goal and measurements along the way. Not by going blind and hurting your workers/customers.
How will companies like Uber continue to fund the “research” when the budget ends up burning 3x faster than predicted without being able to observe measurable gains?
Nothing that C-execs and management advocates for has made any sense for a long time now. If this is the first you're starting to question it all, I must ask what rock you're sleeping under because I desperately need a really good nap...
I knew they were stupid, I just didn’t know it got way down to this level
Strategy - just doing what your friends on the golf course are doing.
The number of times I have been told "oh I talked to so and so and they are having SUCH a good time using X" and then three years later "oh I talked to so and so and they got rid of X as soon as they could, we should switch!"
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I surely remember everyone does SOA, everyone does NoSQL, everyone does Hadoop, everyone does microservices, everyone does kubernetes,....
Not with the same pressure as everyone in the company (literally everyone, regardless of the job role) has to burn AI tokens, and attend forced AI workshops, still it is always running after the next new shinny.
Nobody wanted to admit that they had no idea how "AI" was going to help but nobody wanted to get left off the hype train...so they tasked their engineers to figure something out...by just asking them to spend as much as possible (As I explain this it just sounds stupider and stupider). Of course, spending willy-nilly is not a good way to find a profitable (or smart) idea, but that's a problem for future company bottom line.