No that's reddit, Facebook, insta and TikTok.

Right, but the question is whether the companies producing foundation models will capture that value or not. Right now it seems like tokens might end up just being a commodity sold at cost plus, and companies higher up in the supply chain will make the money. Electricity changed the world but electricity companies capture very little of that value.

I'm betting on it. I'm working on a project right now where I'm prototyping everything with Claude, until I hit my limits on my MAX subscription for the week. Then I switch to Codex, and start by ironing out harness differences. When I max out that, I switch to a mix of GLM 5.1, Qwen 3.6m, Kimi K2.5 and Deepseek and spend part of the time ironing out issues with them while they work on other parts of the project. Every iteration, the harness gets hardened and the pain of switching to the cheaper/dumber models reduce for the next cycle. The gap reduces each time, and with each new upgrade of the open models. Everything points to the cost/value intersecting in not too long.

> Everybody is talking about ai. Everybody is using it.

Please take a moment to step outside the tech bubble. Neither my neighbor (a hair stylist) nor the carpenter fixing up her kitching cabinets are "using" AI. They might get Gemini text when googling something, though they often scroll past it because they often don't trust it. And they get lots of fake videos when scrolling their youtube which increasingly annoys them. The only times they are in touch with AI is when it's forced upon them, and otherwise they are living a pretty good life without any of this.

But how do they learn to do their respective task? How is the information disseminated?

The capability is there for robotics to handle these kinds of repetitive tasks from a long term view. They're just statistical processes on a fundamental level.

In general, a lot of this shit that we do can be represented this way. It's just a question of where the incentives are to apply it first and how many economic cycles it'll take to get there.

Also, who controls the training data will matter a lot more. I.e. the sort of "ancestral knowledge" within different enterprises and how they deliver on respective business goals.

Based on what? A lot of this is vibes and FOMO; just like any economic bubble.

There is no objective evidence of anything you’ve said. It isn’t even clear if AI has contributed positively to global economic growth. It reminds me a lot of the late 90s and the dot-com mania. Slapping a domain on a commercial would make your stock go up even if there was no substance to any of it.

The real shame is this mania drowns out serious, practical use cases because when the bubble collapses, the market will throw the baby out with the bathwater.

You can do anything at zombo.com!

How can you look at Anthropic's revenue chart and claim it's just vibes

1. Revenue is not profit; you can make $10 billion by spending $20 billion.

2. It is not clear how they are getting their numbers.

Regardless they are getting that revenue through genuine demand for their product. It’s not like they are selling back some commodity product, billions are being spent on model outputs.

I think anyone who has used Opus 4.6 can see what is causing this demand. It is genuinely “smart” in the sense that it can work its way around non-trivial coding problems.

But at some point even if the product is useful if it costs twice what is getting in, won’t that be a problem ?

I don't see why tokens/$ would suddenly stop dropping. Maybe this is the first time the cost of compute will plateau, but do have any reason to think so?

There is a strong suspicion, especially of people who are skeptical of AI, that the actual price is being severely subsidized. The sense is that it’s an extreme version of growth before revenue. It is questionable if the true cost of training and inference make any of this worthwhile once Anthropic/OpenAI need to stand on their own and make money.

Imagine you open a cookie shop and you are VC funded, so you charge 5¢ for a cookie to attract people.

- Your real cost is $20/cookie. $15 for the fancy retail packaging and presentation, $5 for baking each cookie.

- You get lots of attention, strong profits and go public.

- VC funding is gone so, now instead of charging 5¢, you now need to charge $25 in order to not be in the red.

One of the reasons people think this is the shenanigans that Anthropic is currently playing, quietly tweaking the behavior of Claude Code and whatnot without really telling people. You can see lots of comments online about Claude Code randomly feeling dumber before Anthropic engineers admit they are messing with it.

Imagine you are on the $200/month Max plan. If the sustainable cost of this is several orders of magnitude higher, would enough current users pay something like $3,000/month for what we currently have?

Sure, yeah, I saw grubhub happen too... but this is compute, not cookies. It gets cheaper.

I don't even get what "skeptical of AI" means. We made AI, many companies reliably teach computers every spoken language. I perform my white collar job with a massive AI multiplier to my productivity.

I'm typing this on a machine comparable to Japan's Earth Simulator, a $350M supercomputer.

Well. The 5090ti is significantly faster than a 1080ti. It has 92b vs 12b transistors. That's the 10 years difference you mention. 10 years before the 1080ti we had the 8800 ultra with 600m transistors. So yeah you are a bit right. But stacked transistors in the future might become reality and enable transistor increase again.

A 5090 is more than twice as expensive as a 1080 Ti in real MSRP terms and way more than that in actual real terms, since the 1080 Ti was available for some time below MSRP, while the 5090 realistically never was and usually goes for 50-100% above MSRP. So I don't think these can be compared. Basically a similar story with the 5080, it's significantly more expensive in real terms (and about ~2x in nominal terms).

The 5070 Ti would be the same spot.

If you compare these - the RTX 50 card has a bit higher TDP (which it will usually not reach due to clock limits), is a roughly 100mm² smaller die with around 4x the transistors and about 3x the compute (since much more of the chip is disabled compared to the 1080 Ti's chip). It has 5 GB more memory (11->16) and a lot more bandwidth.

Yeah it also lacked driver support. But it was for a very brief moment the king of the hill.

This is what I call AI slop.

The problem with agents is that it is currently way too expensive. 100 times more expensive maybe. Another big issue is the lack of interactivity with an agent. Therefor for now agentic development is only viable from your own machine. And there isolation is less of an issue easier to manage.

People still believing in AI being a temporary thing are the same ones refusing to get a mobile phone in the late 90s. Stating it wasn't needed and just a nice to have.

A key take away from this article is that you as a developer spending as much time on refactoring as on the actual feature. You are constantly requesting code reviews, architectural assessements, consolidations, extractions etc. only then you can empower AI to become a force multiplier. And prevent slop and spaghetti code to be created. Nice article

Why? Who are you supporting instead?

Is there now a requirement for disliking something that I advocate for something else? I just hate Tesla, I am a Tesla hater. That really is it.

I'd love a train network that worked. I've lost too many friends to car.

Supporting? As in, what car do they drive lol

indeed. moltbook vibes