alt Hacker NewsThere are a surprising number of articles like this along the lines of, "we started using AI tools and ended up spending millions per year".
On what planet do people start paying for things without keeping an eye on the costs and no-one notices until you have spent a crazy amount? I don't understand. You are either paying a fixed amount which you are happy about in-advance or you are PAYG in which case you would ballpark how much it costs.
Otherwise it reads a bit like a fake problem, because it didn't really happen, you just foresaw it (as you should) and added a few guide rails.
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Something underlying a lot of this is that pricing models for enterprise coding tools have changed from seat-based to consumption-based pretty quickly, as AI usage has exploded. For months, engineers were able to use unlimited AI for no marginal cost, but that's changed quickly.
In addition, we're seeing people applying AI to more and more use cases, so token growth is very significant. Paired with consumption pricing, it's brought this problem to the forefront very quickly for lots of companies.
The issue is the growth rates can cause costs to drastically change quickly. If you have 1,000 employees and the average is spending $100/month you're at a $1.2M run rate. But suddenly a new model comes out that's twice as expensive, there are some changes to the harness (we found randomly Claude Code and other harnesses will make changes that drastically impact efficiency), and then maybe you have some organic user growth as well and BOOM suddenly you're at a $10M run rate within 60 days. And it's now impossible to forecast future growth.
It is true that this problem can be mostly managed by the techniques we mention here. Those are actually pretty difficult to set up at scale, so many companies (including us) we only really did this in earnest once we started to see those large cost oscillations.
The main reason we shared this here is to maybe help other companies get infrastructure in place before massive cost swings rather than after.
Weirdly a lot of the come from company that sell Ai credits in some capacity, and who are also selling (or will soon) some kind of AI gateway or router
> we started using AI tools and ended up spending millions per year
This is how AWS made its fortune.
On this planet?
They’re not saying they regret doing it, or that it was a mistake.
They’re just saying they’ve gained experience and have leveraged the tools to an extent their usage can be optimized.
Pretty standard business or life iteration.
There really has never been another product priced like AI is being priced right now. Each of these things has been done before, but all of them together is new.
1. Insanely discounted starter plans. Claude $200/mo plan is like $5k-$8k of API rate usage.
2. Very limited cost visibility, they make it hard to figure out where you spent money (unless you're on the enterprise plan which is for people with unlimited money).
3. Nobody, not even the model provider, knows what your request will cost before it returns. You're writing a blank check every time you hit enter.
4. When you run out you run out very suddenly and disruptively. It's very hard to tell a developer on the 28th of the month "sorry, code by hand until the 1st of next month" so you tend to grant exceptions.
5. The price is changing all the time. New models come in, old models come out, prices change, caching behavior changes, harnesses change, etc. The cost of doing a single task is not predictable even if the task does not change.
6. Basically no volume discounting. Anthropic offered us 2% off for committing to $1M+ per year at API rates.
I manage AI spend for my team at work and I try really hard to keep costs under control but it's absolutely herding cats. Much harder than any other spending I've ever had to manage at work.