Thread: https://news.ycombinator.com/item?id=48912577

pre-echos of "too big to fail"

Financial news tends to be written for people who can fill in a lot of blanks themselves.

Essentially yes? The stock market operates entirely on the assumption that the lines will keep going up. As soon as they flatten the whole thing collapses onto itself.

> Is "medium growth" for the next 4 years really the worst people can think of?

At this point anything less than "medium growth" will crash the economy. We'll have bigger problems if that happens (think 2000 or 2008)

Hmm. Perhaps too similar to pre-GFC when the ratings agencies' models never accounted for scenarios where home prices went down at the national level.

The source article says (in a way that I can understand might be a bit non-obvious) that it's analyzing the AI buildout from the perspective of the people who are participating in it. Someone who believes there'll be less than "medium growth" would probably not be buying hyperscaler bonds right now regardless of their precise estimate. They discuss the tail risks if the whole investment thesis is wrong at the end.

Can't you see how much money is being pumped into this lunacy? Of course it's going to succeed. Graphs for failire are such a bummer too and are bad for the economy...

if growth doesn't materialize, then the infrastructure build out plays out exactly like the dot com bubble. the biggest difference this time around is the earnings. if those fall, the rest crubmles.

I think this is a great point.

I want to add context for Duolingo because I think it's confounded by cultural conversation. Duolingo in some Q1 earnings call stated it was going to go AI-native. They were going to switch from contractors to AI. This led to a huge PR crisis, especially on TikTok, where they used to have a big online presence and GenZ influence. I'm not sure if they ever recovered the image they had after that.

They tried, and they got pushback from their consumer base.

Your Costco example makes a lot of sense to me. Right now at my company we are spending hundreds and thousands per employee, but it's not like everyone has an idea that is meant to be integrated into product. So everyone's just making more vaporware.

I do think this is the year the numbers and projections will start coming down to the ground. We can already see this with the fact that the leaders at the frontier labs have stopped talking about AGI and have started talking about token costs and just direct comparisons. It's no longer pie in the sky.

The issue is Duolingo is rubbish, what the app does isn’t that hard to replicate and there are already competitors that have a better product.

So if AI is real then that‘s the cherry on top: people can now make an alternative to your ineffective messy app even easier.

For those kind of SaaS products with no moat LLMs could actually be a problem and definitely aren’t a good thing

I'm not an MBA over here, but this math seems wrong. If they are spending $240 in increased costs, then they only have to make about $247 in additional revenue from that spend to preserve a 3% margin. That seems much more reasonable if it increases the probability that customers find the product they are looking for and have a good experience.

This study finds increased sales and value per customer from GenAI integration at a large Chinese online retailer (all the way back in 2023-24!) The customer Q&A scenario is one of those covered, except the customer talks directly to the LLM rather than an employee with a subscription:

https://arxiv.org/abs/2510.12049

> We quantify the short-term impact of Generative Artificial Intelligence (GenAI) on sales performance through a series of large-scale randomized field experiments involving millions of users and products at a leading cross-border online retail platform. Over 2023-2024, the platform integrated GenAI into seven business workflows spanning customer service, consumer-product matching, advertising, and seller services. We find that GenAI adoption increases sales in most workflows, with effects ranging from no detectable impact to 16.3%, depending on GenAI's marginal contribution relative to baseline firm practices. Across the four GenAI applications with positive sales effects, the implied annual incremental value is roughly $5 per consumer−an economically meaningful impact given the retailer's scale and the early stage of GenAI adoption. The gains operate primarily through higher conversion rates rather than larger cart values, consistent with GenAI improving the shopping experience by reducing search, information, communication, and personalization frictions. Importantly, these effects are not associated with worse post-purchase outcomes, as product return rates and customer ratings do not deteriorate. Finally, we document substantial demand-side heterogeneity, with larger gains for less experienced consumers. Our findings provide novel, large-scale causal evidence on how GenAI shapes sales productivity in online retail, highlighting both its immediate value and broader potential.

Impact on profitability itself is hard to determine due to caveats listed in the paper (which are important to read!) but offhand I would guess that incemental $5 margin per customer is much more than what their prompts cost.

Translator services usually get paid because they offer an accreditation or certification that the humans doing the translation are trained and are not randos / computers. I could imagine these services becoming marginally more efficient but no dramatically improving profits.

The risk here is that either AI commoditizes the software "why ask duolingo to ask chatgpt when I can do so directly?" or simply adds cost to an existing service "why does every costco employee now cost 10% more?"

So far, there hasn't been a clear win for "software wrapping an existing LLM" - if the AI is good enough, then the users can go directly to the source.

I agree with your main observations, but the Costco example is a bit contrived. I expect companies to eventually figure out suitable applications for AI, and I doubt a flat subscription per seat will be one of them. Personally, I feel the main issue is that the tooling + systems needed to deploy AI successfully have only recently started to mature.

AI has been making a ton for advertisers for decades. Think Facebook ads, Google search ads, etc.

That's a different and older kind of AI than chatbots, but it's not fundamentally different, but AI is the engine that makes their ad targeting so effective, and why they're some of the most profitable large companies on the planet.

I don't know why you would expect Duolingo profits be helped a lot by AI. Their profits going up and down are more about how much then enshittify for free users - basically tradeoff between long term success and temporary profits. AI does not change that balance. You can enshittify and profit quickly or not enshittify and keep long term engagement.

AI announcement annoyed some people, the slop translate courses were, well, slop. That is the extend of the change.

just recalled: some significant open source projects are being rewritten in Rust, with the help of Claude. I don't know if these efforts will be successful in the long run, but in some way these news headlines may be creating a media dynamic as part of the IPO preparations?

[1] https://news.ycombinator.com/item?id=48870966 pgrust passes 100% of the Postgres regression tests

[2] https://news.ycombinator.com/item?id=48837877 Rewriting Bun in Rust

[3] https://news.ycombinator.com/item?id=48789325 My AI-built PHP engine in Rust passes 17% of PHP-src tests, renders WordPress (ekinertac.com)

they're probably waiting to see how market reacts to fable5 and gpt 5.6

AFAICT, the last we heard of any AI company IPO was that OpenAI got spooked by the market response to SpaceX and is considering punting to 2027 (https://www.the-independent.com/tech/openai-ipo-date-valuati...). My money is on Anthropic similarly punting, especially if SpaceX manages to cross the very very short distance remaining to drop below the IPO price.

Public utilities tend to pass on all their costs to their customers. If the data centers crumble, that just means the remaining customers (business and residential) each will have to pick up a larger share of the debt payments for the buildout.

No, we won't - there's significant capex on all that infra that will have to be paid down, and we won't have datacenters to help pay for it.

Yes. In inflation adjusted dollars spending on AI dwarfs previous "megaprojects". But as a fraction of GDP it's fairly modest -- comparable to the Apollo Project.

It's a sign of how much the economy has grown that under "1% of GDP for a few years" now is far bigger than "over 10% of GDP for a few decades" was in the late 1800s.

Manhattan Project: $36B, 5 years

▫ Apollo Program: $257B, 14 years

▫ Interstate Highway System: $620B, 37 years

▫ AI data centers: $930B, 6 years and still accelerating

From: https://substack.com/@rubendominguez/note/c-244929068

this time its free printed fiat debt tho, not fully comparable. If market crashes, they will print even few times more again