Small businesses that do the work of curating a niche item, doing QA work that's absent on the shipments from china, and then offering much stronger aftermarket support/replacement/repair? That is often worth a (substantial) premium over wondering if the item showing up in a month is going to work as intended.

The point I'm making is that I think we're rapidly hitting levels where corporate buyers aren't willing to pay multiple-times-more for marginal gains, and I expect that to become more the case over time, not less. You, and a small % of other power users in the market might tolerate a $400/month pro-supreme-plan for access to Mythos or whatever, but I don't think that's going to scale up in quite the same ways we've seen so far.

Even a year ago paying multiples times more for a 50% gain was very sensible for a lot of workflows. But if we're getting to "good enough" for things like coding, justifying to your CTO/CFO why the org should go from spending $1m/year to $5m/year for a 10% higher hit-rate on one-shot prompts from the engineers is a much tougher sell.

I wanted the ability to run whatever cameras on a VLAN and own the stack.

The demand for senior+ engineers has remained steadier through this downturn from my anecdotal observations, with new grads being by far the most negatively affected, but even that seems to both be shifting from talking to people a handful of years younger than me + CS enrollment has already precipitously declined [2] as the narrative that programming is dead because of AI has spread rapidly.

All that leads me to think it's going to be a junk-show over the next decade for people trying to hire as the pipeline was destroyed.

1: https://www.citadelsecurities.com/news-and-insights/2026-glo... 2: https://www.washingtonpost.com/technology/2026/04/13/compute...

I'm already seeing tech execs/hiring managers getting very frustrated at the lack of new-senior-engineers to hire. The market will correct for this in time.

We're 3.5 years into this current AI wave, and a lot of the valuations have been predicated on what you're arguing here -- that essentially should one of the labs make an order-of-magnitude improvement or hit escape velocity on recursive self-improvement they'd become the most powerful economic chokepoint in history.

The reality has been that given access to compute + capital all of the labs can stay pretty competitive with each other. Someone does a bit better on coding, someone else does a bit better on tool calling, and then they swap after each spending another $100bn.

The market looks like a commodity market where the commodity is intelligence, not a winner-take-all market with massive margins. Plenty of people get rich in oil and airlines, but they notably don't tend to be the innovators long term, they tend to be the operators. Obviously if the machines become sentient tomorrow, turn on their masters, and hit world-dominating intelligence, that assessment changes, but after several years of that narrative while objective reality looks quite different I think the more sober voices are starting to gain a foothold.

The larger point I'm making is I think models are rapidly becoming commoditized. There is probably a small market long term that's willing to pay 10x for 10% marginal gains, but the majority of the buyers in the market will be economic and we're likely to have a lot of folks willing to spend 1/10 the cost for 90% of the performance, and plenty of companies that haven't raised hundreds of billions-trillions who can provide that.

A lot of the frontier labs valuations has been based on an assumption that 1-2 companies would get break-away intelligence that basically made them economic chokepoints indefinitely into the future. The reality that's becoming increasingly clear is that model quality is a pretty linear function of (cash burned - ability to copy other's homework) and the economics are starting to look a lot more like airlines than online advertising.

And yeah, that may be the ~decade world, but we're in the mainframe era of the frontier models. It's going to be more economical for basically any consumer, and most businesses, to pay someone else to host models for quite a while.

Claude code was a lot of people's introduction to using coding agents that could do a lot more than copy-pasting from a chatbot or autocomplete.

That's doing a lot of work here.

The future I see isn't most companies buying hundreds of thousands in hardware to run models, it's them adding a line item to their AWS bill. Inference costs on the larger hosted open source models are dramatically lower than the frontier labs API pricing.

If open source models are ~3-6 months behind SOTA, and ~opus4.6 capabilities are good-enough for product market fit, do the frontier labs have half a decade to catch up on their prior burn?

AI cost ballooning faster than companies can afford is becoming a very common topic in my circles right now. The era of "I'll pay infinitely more for marginal gains" is over from what I can tell.

This is taking a hobby to its extremes, in much the same way that a $5k boat and $500k boat let you catch the same fish.

I've had similar experiences with making simple functional parts off a 3d printer with OpenSCAD + LLMs. I'm very aware that the models are worse at it than say, generating react code, and I'm also the antithesis of a skilled pilot. It's still cool and has resulted in me starting to learn a new skill at a hobby level.

The reality of the world faced by today's 21 year old college grad is completely unlike the world graduates went into 20 years ago.

An expert can either use the tool more effectively, or see all the issues in a less experienced person's output.

Both of these are good things, the mistake a ton of people are making is experiencing industrial scale Dunning-Kruger and thinking "Only my expertise is still valuable, every other white collar role is done!"

The second-order mistake is thinking that raising the floor like that devalues expertise instead of increasing demand for it. The net-effect of me starting to play with CAD because it's a little easier now isn't that I don't hire my friends who are experts to make a tiny spacer I'm going to 3d print, I never would have hired them for that, it's that maybe I start learning the skills and decide to take on a more ambitious project where I do need to hire one of them for some help, or start ordering custom CNC'd parts -- scale that to the entire economy.

Not only that. Them and the point-of-sale vendors (aptly shortened PoS), sell that data. They tend to attempt to do this anonymized. How successful they are in anonymizing that is very much so up for debate.

The websites (and even their retail locations) you buy from send your purchase data to meta and other advertisers directly via APIs so they can better track their marketing conversion rates. You can browse their APIs [1][2] to see what kind of data they like to get, but it tends to be every piece of identification they have on you. Rewards programs make this a much richer data set. You don't need to be a user of Google/Meta for them to build a marketing profile based on this. Google links your physical conversion from ads based on your maps data. Facebook does the same if you give them your location data. Many retailers attempt to use the bluetooth/wifi signals from your phone to track the same data even if you pay in cash [3].

There's no legal framework preventing this outside of the EU and California.

1: https://developers.facebook.com/documentation/ads-commerce/c... 2: https://developers.google.com/google-ads/api/docs/conversion... 3: https://www.nytimes.com/interactive/2019/06/14/opinion/bluet...

Jevons paradox is already rearing its head, I've seen data suggesting open roles in tech are at their highest since the post-pandemic slump [1]. If you're a senior leader at a company and your engineers are now capable of multiple-times more productivity, is the logical choice to fire half, or set way more ambitious goals? One assumes engineers are hired because their outputs are worth more than their cost. If outputs, at least for those capable of wielding new tools, are higher, so is the value of that employee to you.

The universal thing I'm hearing from friends at small-mid-size tech companies, and experiencing myself, is that there is way more work and demand for it from senior leaders than they're capable of with their current teams.

1: https://www.ciodive.com/news/tech-job-postings-hit-3-year-hi...