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Drifting? I think it's there. basedpyright is awesome and super fast. Our latest services are all CI gated by type checking. Early in my career you'd hit so many dumb errors running your code - NoneType, attribute, value, and type errors. I'd say that's been cut over 95%.

According to Pew, almost 70% of teens report to have used LLMs/chatbots, and 30% use it daily. This is also over 6 months out of date, which feels like an eternity at the current rate things change.

https://www.pewresearch.org/internet/2025/12/09/teens-social...


You mean that after multiple years, 30% of teens haven't even ever used an LLM? Those kids probably don't even know what an LLM means since using google is now using an LLM.

> > As a group, teenagers and young adults hate AI

Anecdotally, I've observed a robust correlation between the cost/quality of the model, and attitude towards it.

Most of the general public, young folks, and old folks (ie outside gen z, millennials, and some X) are using free models, usually what's immediately available (cough copilot cough), have really unreliable results, hear all the hype, experience dissonance, and chalk it up to just hype, and walk away thinking AI is a crock of junk.

The Z/Y/G cohort - the ones that grew up alongside the growth of the internet - seem to be the best adopters. They recognize a system which is powerful, albeit flaky, and know how to extract utility from it without over-reliance. Especially ones with paid flat-rate subscriptions.

The power users - the ones using API/paid (by usage) models, tricking out their claude with plugins, seem to have the least amount of hate, but rather a healthy respect for a powerful disruptor.

I also don't buy the whole "the young'ns have never dealt with barriers of entry to the internet and thus lack the tech skills the millennials developed." I think the internet cohort that adopted tech was always split between the powerusers/curious learners, and the "just get my goal accomplished and get out" folks. I think that's roughly the same percentage of folks in Z/alpha, and these kids are just as savvy and aware of limitations of the tech.


I think the analysis-space really needs to be divided into three groups: software, media (audio/video/image) generation/alteration, and everything else.

Software - this tech is ludicrously powerful and productive. But it's a force multiplier, not a "push button, receive software" system. Great devs that know how to wield it will become überdevs, becoming more productive and with lower defect rate (we have objective internal numbers backing this). But bad devs and non-devs will become high output slop factories. You basically need a dedicated platform team to keep things on the rails. I think this is very akin to the internet bubble. The process, institutional knowledge, and feedback systems developed at this time will grant the "survivors" massive edges after the pop.

I think media generation is or will be a solved problem. Animators, 3dfx, background/filler music composers, those jobs are in sorry shape based on current trends. But a cost explosion could easily level the playing field.

Everything else, where middle managers are aggressively pushing AI usage? Yeah maybe. At this time, other than for document retrieval (basically suped-up search), the "productivity" gains don't really map to value gains. Oh wow you can crank out powerpoint slide decks 50% faster. Write 50% more corporate emails employees barely read anyways. There's definitely a trust issue there with hallucinations. If the reliability gap can be solved (the bots don't even have to be correct, they just need to be less confidently incorrect, and I already see this somewhat with my own agents with tuning), then that could prove the turning point between "begrudging usage at the behest of higher ups" and "actual productivity enhancer."

Does no one remember in the dot com boom all the internet skepticism? "I don't trust it with high value orders, what if it crashes or loses data? Call me old-fashioned but I'd rather write it down." That attitude was quite prevalent for years, even into the 2000s.


Are the datacenters that are being built not directly analogous? Even if the hardware in them is cooked after 5 years, the buildings, power, cooling, and fiber interconnects are still all valuable.

The models may go out of date but the process and software are continuously improving.


Partially, the GPUS represent about two thirds of the datacenter cost. Hopefully the legacy is going to be a large market of second hand and refurbished datacenter gpus that will democratize compute. We are already seeing Nvidia H100s and AMD MI250s hit the secondary market.

> 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...

is basically the premise of

https://en.wikipedia.org/wiki/If_Anyone_Builds_It,_Everyone_...


The younger devs have largely been the ones showing us old farts (eg millennials) how do to the really sophisticated stuff with claude - custom skills, plugins, tooling like openspec, things that have had massive benefits over stock claude.

We are nowhere near the ceiling in terms of process either.

Re: flat rate going to by-usage, I believe this is largely a long tail problem. You have a small number of power users that capitalize on the flat rate to use the service orders of magnitude more than the average user.


> really sophisticated stuff with claude - custom skills, plugins, tooling

You mean the "make-no-mistakes.md" and linter pipeline? Did not know that was now considered top-notch stuff.


Iceberg surface

I think my company is a microcosm of the current state. The non-engineering side (HR, correspondence, marketing) are on the "forced adoption" side, giving out gift cards to folks using Glean the most.

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.


That's a lot of words, out of which I am unable to understand what your material gains had been so far. And I don't mean the bullshit that the hired managers/CEOs usually mention, like story point "productivity" and "tickets closed". I mean the stuff that founders, i.e. people with skin in the game value: what key features did you build with the incredibly productive new workflows and how much ARR did they generate? How much did you decrease your cost of customer acquisition and how much did you increase your customer LTV? Let's skip the gamified "playing house" bullshit and talk numbers.

zionism != judaism

Zionism is one element of Jewish supremacy, but not all of it. In fact Zionism's execution was birthed from Jewish supremacy. The Rothschilds were in a unique position to receive a "state" from the British government.

That's literally what OpenSpec does (https://openspec.dev/). It's quite nice. I've only exceptionally rarely seen claude do something wrong based on spec docs when it's fully spec'd out. More often it's because something wasn't nailed down and claude was forced to make assumptions.

The downside is the ospx markdown specs sometimes end up too granular, focusing on the wrong or less important details, so reading the specs feels like a slog.

Also at times aspects of the english language spec end up way more verbose than just giving a code example would be.


Is it time for the literate programming renaissance?

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