1) That LLM/Agents are being pushed and not adopted. I see plenty of deep adoption by junior folks.

2) The unit economics don't work out. From the details on every model so far - each model is wildly profitable over it's amotized time-frame. It's just that money is used upfront for the next model, and each next model is significantly more costly to train. The best case argument instead is - this will not last and we'll pour more on some models, than see in it's revenue.

I think realistically these form the core of the thesis, and IMO, and hence it's conclusions are a bit off the mark.

It was mismanagement then and it's mismanagement now, the more things change the more they stay the same.

I’m in a finance role and thus far it’s all been rather hand wavy „use copilot more“. Maybe some meeting summarization. Nothing like the programming space where token counts matter to management

Will be interesting to see where this goes. My testing with it thus far has just yielded multi million dollar hallucinations. Senior management will presumably try anyway

However, something occurred to me when reading it. I was thinking about AGI (or ASI) and what would happen if someone were to achieve it (not sure what it would look like or what constitutes AGI... not the point I'm making here).

What if the primary goal of the first AGI is to keep itself at the top? What if it's goal is to prevent any other AGI? Scary thought...

One wonderful thing I’ve watched for the last 4 years is my company fail to build a modelling tool better than Excel. On attempt 3 we have some pile of shit Claude generated on nodejs and Postgres on kubernetes which can’t replace a single spreadsheet written in 2008. Because everyone thought into the bullshit not the solution or the requirements.

Edit: thinking further, it appears people forgot what the problems are and think from the solution back. That never works. But it sells tools.

  labor-led automation produces improvements in quality, while capital-driven automation increases throughput

This explains the management push (ignorance) but also the user push (automating BS tasks). The common thread is that the user doesn’t have to take any responsibility for the output. This is why people don’t like having LLMs pushed on them, because for cases where they are responsible for or have to consume the output, they don’t work very well, but when it’s just something that needs to look ok at a glance and be handed off, everyone is rushing to use them.

I'm lucky enough to be in a great company right now, so I decide when I think AI will help me and use it accordingly - but reading about forced AI adoption reminds me so, so much of that earlier time. Non-technical people who don't trust their engineers to use the tools in the way they see best - in their ignorance, and ego, they think the answer is obvious if only those strong headed tech weirdos would listen.

And amongst all this, there is a class of manager and executive that I'm convinced utterly despise engineers. They hate the fact they focus on details, analyse, make predictions grounded in reality. On a personal level, they can't comprehend that some people take deep satisfaction and contentment from building software, from simply learning things, and they don't understand it, it scares them. Why don't they just pursue normal people things in life? Like super expensive cars, massive houses, golf memberships. I think it scares them that they don't have control over technically minded people they way they might do with others. AI is, in their mind, a way to get rid of these people forever, to just "get stuff done" without objections, and they are pushing extremely hard for that to be true, simply because they want it to be true - not because there is any evidence for it.

Rant over.

A great technology drives its own adoption, its usage is pioneered by the tweens and young adults, it requires minimum effort and investment to hop on board, and it does not need explaining. It grows organically. Examples: internet bubble.

A bad technology: despised by the young adults and tweens, needs trillion of investments and marketing to drive market penetration, every day some boomer (=not in terms of age, but in terms of mentality) explains how you are holding it wrong and it needs a fuckton of explanation. The Pope himself issues an Encyclica warning on the dangers of it, spurning the greatest popular interest in Catholicism since the dark ages. Examples: LLMs.

Outside of AI's impact on software, which is massive, the biggest change that we are going to see, I think, is the crushing amount of useless information generated by it.

We already see how everything is racing to the lowest common denominator once we granted Average Human Intelligence unfettered access to expressing thought via social media.

Now that Average Human Intelligence just has a button that says "Generate Bullshit For Me. Send to the World".

UGH.

Or even worse, many employers and employees alike are afraid to cut out BS work - because it could realistically mean cutting down on the workforce. So they continue to produce work that no one checks, because at least then they can justify their position.

They are not about actually "doing things", they are social validation, particularly the part where the people with resources/capital enjoy your company and give you what you need to live a dignified lifestyle in exchange for it.

But acknowledging and acting on this would destroy the leverage the useless-but-likeable have in terms of being able to get paid, and that the owner class have in terms of getting people to pretend that they like them/validate their often cruel and avaricious choices and behavior.

In engineering, we can't raise token budgets fast enough. Devs are "routing around damage" when they hit caps, going from claude to opencode to copilot. Productivity is up (roughly) 100-300% in terms of story points and 75-200% in lines of code. And defect rate is down [0], more bugs are caught in review before QA or prod. Our teams are just starting to figure out our new workflows too, for design -> spec -> code -> review, it'll only get better as we refine the process.

It's looking like software industries will reap massive benefits, while most others which have some error tolerance will only see modest gains. It's unclear how it will impact high accuracy fields like legal (it might even be net negative).

Also which is it - a useless technology that has to be force-fed because it sucks, or a economy-shaking game changer that will put folks out of jobs en masse? Those seem like a contradiction.

0 - i think process here is extremely important. I think it would be very easy to create an unmaintainable slopocaplypse. We have an informal platform team of about three (including myself) that have been affectionately and informally dubbed the Tech Priests of Mechanicus Adeptus (warhammer reference) that ensure the prompts/skills and associated tooling are optimal, that code standards are enforced, and that solutions are converging at the system-wide level.

>A majority of teens use AI chatbots. Roughly two-thirds of U.S. teens ages 13 to 17 (64%) say they ever use an AI chatbot, according to a fall 2025 survey.

>Around half of adults under 50 say they interact with AI about once a day or more often. Smaller shares of those 50 and older say the same, according to the June survey.

and mind you, that particular study bends over backwards to say "AI bad".