The real cost isn't the inference bill, it's the senior engineer hours spent debugging subtle hallucinations that slip past naive test suites. We stopped bleeding money on trivial boilerplate by implementing model routing through FlintAPI, ensuring only complex logic actually hits the expensive frontier endpoints. Treating LLMs as a monolithic tool instead of a tiered pipeline is what quietly destroys your margins.
A while ago I was thinking, “Gee, AI is so complicated, how can I keep up with the landscape?”
After reading these articles go by so often, it feels like what I actually can’t keep up with is the bond market. To paraphrase Trotsky, you may not be interested in the bond market, but the bond market is interested in you. I want to be able to read the signals at the bottom of this article, and divine some kind of prediction that can guide me… I don’t know, to choose whether I should buy a house or change the investment strategy in my retirement fund or something. But I’m just seeing all these signals go by, waiting for the story to be written, which only happens when the dust settles.
I guess I’ll go back to not understanding AI, instead of not understanding the bond market.
you won't get debt if you don't have assets that can be repossessed, so having debt means these AI companies have assets: that's a strong thing, not a weak thing. interest rates are what they are, and they go up and down for reasons exogenous to your industry; debt regardless of interest is always "cheaper" than equity, and the shareholders expect to make their money from equity, paying interest on debt as a type of impedance matching and cost of keeping more equity.
so everything is going according to plan, and nobody knows the future, and predicting collpses has never been a profitable business.
I didn't have to read past the first few confusing contorted and convoluted paragraps of this article to decide to come over here and explain it, this is all straightforward corporate finance 102 and the article is fluff
Revolutionary technology + massive adoption ≠ good investment
Investors have poured money into a bottomless pit, attracted by the growth and glamour of the industry. The airline industry since its birth has had a collective net loss, in aggregate, despite moving hundreds of millions of people.
Commodity Product, no switching costs. Infinite competition
“None of this yet resembles a credit cycle turning, and the signals that would show one are quiet… What the data describes is closer to the opposite of a contraction: a credit expansion absorbing record supply and charging progressively more for it. The pricing runs in a ladder.
…
Where the ladder breaks is at the bottom. CCC and Lower Option Adjusted Spread signal rose twenty-two points over thirty days to 88 and sits at Critical, markedly higher than the Investment Grade or High Yield spread signal levels, and AI paper does not price at CCC. Private Credit Stress sits at 96, up thirty-one points, consistent with reporting data center financing has moved toward private credit and off-balance-sheet structures where the ultimate holder is harder to identify. What separates an expansion from a contraction is not the level of spreads but whether new issuance keeps clearing. An expansion growing more expensive still places its paper; a contraction is when deals stop pricing at any spread. The market is still clearing. It is clearing at a price that has moved in one direction.“
> Grey Swans: risks that were in the data but overlooked or dismissed because few had synthesized the signals into a coherent picture.
Directly conflicts with
> Alert and Critical signals represent readings that have historically been associated with meaningful financial stress.
These are all pretty standard things to track and are regularly (and publicly!)
Not saying we’re not in a bubble or near/far from it popping, but these metrics aren’t going to precisely tell you _when_, which is pretty much the only thing that matters.
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[ 0.17 ms ] story [ 8.5 ms ] threadAfter reading these articles go by so often, it feels like what I actually can’t keep up with is the bond market. To paraphrase Trotsky, you may not be interested in the bond market, but the bond market is interested in you. I want to be able to read the signals at the bottom of this article, and divine some kind of prediction that can guide me… I don’t know, to choose whether I should buy a house or change the investment strategy in my retirement fund or something. But I’m just seeing all these signals go by, waiting for the story to be written, which only happens when the dust settles.
I guess I’ll go back to not understanding AI, instead of not understanding the bond market.
so everything is going according to plan, and nobody knows the future, and predicting collpses has never been a profitable business.
I didn't have to read past the first few confusing contorted and convoluted paragraps of this article to decide to come over here and explain it, this is all straightforward corporate finance 102 and the article is fluff
Until they didn't.
Revolutionary technology + massive adoption ≠ good investment
Investors have poured money into a bottomless pit, attracted by the growth and glamour of the industry. The airline industry since its birth has had a collective net loss, in aggregate, despite moving hundreds of millions of people.
Commodity Product, no switching costs. Infinite competition
https://youtu.be/LxJW7hl8oqM?is=IjdyHwZchaiMHk4C
…
Where the ladder breaks is at the bottom. CCC and Lower Option Adjusted Spread signal rose twenty-two points over thirty days to 88 and sits at Critical, markedly higher than the Investment Grade or High Yield spread signal levels, and AI paper does not price at CCC. Private Credit Stress sits at 96, up thirty-one points, consistent with reporting data center financing has moved toward private credit and off-balance-sheet structures where the ultimate holder is harder to identify. What separates an expansion from a contraction is not the level of spreads but whether new issuance keeps clearing. An expansion growing more expensive still places its paper; a contraction is when deals stop pricing at any spread. The market is still clearing. It is clearing at a price that has moved in one direction.“
- Gen AI: Too Much Spend, Too Little Benefit?: https://www.goldmansachs.com/insights/top-of-mind/gen-ai-too... (Goldman Sachs)
- AI’s $600 Billion Question: https://sequoiacap.com/article/ais-600b-question/ (Sequoia Capital)
- The Simple Macroeconomics of AI: https://www.nber.org/system/files/working_papers/w32487/w324... (MIT / Daron Acemoglu)
Directly conflicts with
> Alert and Critical signals represent readings that have historically been associated with meaningful financial stress.
These are all pretty standard things to track and are regularly (and publicly!)
Not saying we’re not in a bubble or near/far from it popping, but these metrics aren’t going to precisely tell you _when_, which is pretty much the only thing that matters.