And it's going to cost a whole lot more once the investments dry up and they're going to have to actually pay for all the data centers under construction.

i saw a post that was something like "youd think the cocaine class would understand why the first hit is free"

Impossible. It would require C-suites:

1. having a brain
2. realize that they fucked up
3. accept it without having a brain aneurysm
4. making decisions to prevent that in the future

Two trillion valuation, where are you going?

Might as well just stop using AI agents that that point.

Wouldn't that be terrible...

I just want to put "$29 per month" into perspective:

Imagine a white collar employee earning $100K per year. $100K / 250 working days is $400 per day. Payroll tax and benefits can easily add +50% to that, so it's not a stretch to guess that our hypothetical employee costs the employer $600 per day.

$29 per 20 working days is about 1/4 of 1% of that cost.

Might as well just stop using AI agents that that point.

I don't work at Accenture, but at a group that had a similar journey from adoption to scaling back to only the included tokens and I would say that is precisely the idea: giving up on 'Agentic' use of AI, but still have enough for some acceleration.

From what I gather, in our group the findings were:

• Obviously, it was costing a heavy chunk of change and then even more expensive when rates were hiked
• There was no good way for them to even know what productive end the spend went toward, they know which employee expended a bunch of tokens, but no idea what they would have used it on
• Despite a crank of volume of stuff, they weren't seeing any business value of the stuff. Requests still took about the same time to fulfill, etc
• The most eager AI producers got ahead of their skis, and their stuff was useless because nothing and no one could reliably fix/tweak it after a certain point.
• All the scary 'AI will ruin IT security' that the AI companies themselves have been expressing likely didn't help either.
• Perhaps the most uncomfartable of all, they found out that however good or bad an AI project turns out to be, management can't tell the diference until it is too late. Being able to 'manage' the content has always been flawed, but the AI dials it up to eleven by 'looking' just right as a demo to someone that understands neither the customer nor the process of creating the work, but blows up in their faces in delivery. Kind of like how so many technology article writers breathlessly talked about the photoshop clone, despite many of them never having touched the relevant software, then heavy users reporting that it is actually shit, but the people writing about it have no context to know, but felt compelled to talk about it anyway. Those are management in the fields using AI.

So only if it can be recharged to a customer

How many companies allow their employees to also be employed by their competitors?

Your idea of an AI being like an employee only if there's an AI company that will agree to an exclusive contract or at the very least respect data ownership and respect privacy. Is there an AI company that's like that?

@prime_number_314159
Maybe their business model does not depend on productivity. If the rate they charge for a developer with AI and without AI is approximately the same, they rather sell two people than making one more productive.
@FirmDistribution

Definitely. We do this at my job. But a server big enough to provide a comparable service would cost at least $30k. And you likely need more than one. And you still need someone to maintain it.

Not at the moment. It's definitely cheaper to buy LLMs as a service than running an in-house server hall. Anthropic and OpenAI are running at a loss, you know.

Now, risking to lose your data to the service provider is another thing.

Look at it this way, if I pay Open AI $1k a month, their people make sure it works they month. If I let Joe from finance spend $10k on computer parts, Joe needs to ensure that it runs or I need to hire someone who is knowledgeable on local models. If I'm a simple firm, $12k a year might be cheaper because someone else makes sure it works and I can fire Joe when the fancy autocorrect loses a bunch of clients by falsifying work. Then I don't have to spend even bigger bucks hiring a new Joe because no one knows how to work the damn server he replaced the break room with.

The Haiku 5.5 model is actually quite inexpensive. I've used it to implement multiple features this month and have only spent $4 of my $20 monthly budget.

I spent $200 in one session the other day, watching the clanker design, implement, and review the change. Still have no idea what I did but my name is on the commit

Good.

If my productivity (and therefore my job) were measured not by results but by amount of tokens I use, you can bet I'm gonna burn tokens for absolutely everything during my work shift. Even if it's just asking the chatbot what time is it every second.