LLMs upend a few centuries of labor theory.

The current market is predicated on the assumption that labor is atomic and has little bargaining power (minus unions). While capital has huge bargaining power and can effectively put whatever price it wants on labor (in markets where labor is plentiful, which is most of them).

What happens to a company used to extracting surplus value from labor when the labor is provided by another company which is not only bigger but unlike traditional labor can withhold its labor indefinitely (because labor is now just another for of capital and capital doesn't need to eat)?

Anyone not using in house models is signing up to find out.

A while ago I was at the supermarket. I suddenly became curious about some fact, and reached into my pocket to Google it.

I found my pocket empty, and the specific pain I felt in that moment was the feeling of not being able to remember something.

I thought it was interesting, because in this case, I was trying to "remember" something I had never learned before -- by fetching it from my second brain (hypertext).

L1 cache miss, L2 missing.

One might argue that it’s not too too different from higher level abstractions when using libraries. You get things done faster, write less code, library handles some internal state/memory management for you.

Would one be uneasy about calling a library to do stuff than manually messing around with pointers and malloc()? For some, yes. For others, it’s a bit freeing as you can do more high-level architecture without getting mired and context switched from low level nuances.

Assuming that local models are able to stay within some reasonably fixed capability delta of the cutting edge hosted models (say, 12 months behind), and assuming that local computing hardware stays relatively accessible, the only risk is that you'll lose that bit of capability if the hosted models disappear or get too expensive.

Note that neither of these assumptions are obviously true, at least to me. But I can hope!

Well, they obviously are going to say that, they have vested interest in OpenAI and thus Nvidia stock price growing.

Also, I honestly can’t believe the 10x mantra is being still repeated.

Who else is trying to leverage the situation so that they don't dig their own grave too fast ?

    - I often don't ask the LLM for precompiled answers, i ask for a standalone cli / tool
    - I often ask how it reached its conclusions, so I can extend my own perspective
    - I often ask to describe it's own metadata level categorization too

> This quote is more sinister than I think was intended; it likely applies to all frontier coding models. As they get better, we quickly come to rely on them for coding. It's like playing a game on God Mode. Engineers become dependent; it's truly addictive.

What's the worst potential outcome, assuming that all models get better, more efficient and more abundant (which seems to be the current trend)? The goal of engineering has always been to build better things, not to make it harder.

It's very addictive indeed. After I subscribed to Claude, I've been on a sort of hypomanic state where I just want to do stuff constantly. It essentially cured my ADHD. My ability to execute things and bring ideas to fruition skyrocketed. It feels good but I'm genuinely afraid I'll crash and burn once they rug pull the subscriptions.

And I'm being very cautious. I'm not vibecoding entire startups from scratch, I'm manually reviewing and editing everything the AI is outputting. I still got completely hooked on building things with Claude.

I feel like most engineers I talk to still haven't realised what this is going to mean for the industry. The power loom for coding is here. Our skills still matter, but differently.

This engineer had their brain amputated once they started using AI. All the AI-addicted can do is tinker with the AI computer game and feel "productive". They could as well play Magic The Gathering.

You are 100% right to be cautious about this. That's why as stupid as it sounds, I've purposely made my workflow with AI full of friction:

1. I only have ONE SOTA model integrated into the IDE (I am mostly on Elixir, so I use Gemini). I ensure I use this sparingly for issues I don't really have time to invest or are basically rabbit holes eg. Anything to do with Javascript or its ecosystem). My job is mostly on the backend anyway.

2. For actual backend architecture. I always do the high level architecture myself. Eg. DDD. Then I literally open up gemini.google.com or claude.ai on the browser, copy paste existing code base into the code base, physically leavey chair to go make coffee or a quick snack. This forces me to mentally process that using AI is a chore.

Previously, I was on tight Codex integration and leaving the licensing fears aside, it became too good in writing Elixir code that really stopped me from "thinking" aka using my brain. It felt good for the first few weeks but I later realised the dependence it created. So I said fuck it, and completely cancelled my subscription because it was too good at my job.I believe this is the only way that we won't end up like in Wall-E sitting infront of giant screens just becoming mere blobs of flesh.

That's the path we've been going down for a few years now. The current hedge is that frontier labs are actively competing to win users. The backup hedge is that open source LLMs can provide cheap compute. There will always be economical access to LLMs, but the provider with the best models will be able to charge basically whatever they want and still have buyers.

I use local models on a Mac mini for most things and fall back to the hosted ones when they can't get the job done. Of course you have to break the work into smaller pieces yourself that a local model can understand. One good side effect of this is that you end up actually learning the code and how it's structured.

I have found something similar. I am easily distractible and if I don't have a written task backlog in front of me at all times, I find that when Claude is spinning I'll stop being productive. This is disconcerting for a number of reasons. Overall, I think training young people & new hires on agentic workflows -- and how to use agentic "human augmentation" productivity systems is critical. If it doesn't happen, that same couple of classes that lost academic progress during covid are going to suffer a double-whammy of being unprepared for workplace expectations.

Fwiw, I haven't spoken with any management-level colleague in the past 9 months who hasn't noted that asking about AI-comfort & usage is a key interview topic. For any role type, business or technical.

> I'll make more progress than mentally wearing myself out reading a bunch of LLM generated code trying to figure out how to solve the problem manually.

I feel sorry for whoever has to work on that codebase. This is the literal definition of tech debt.

> It's literally higher leverage for me to go for a walk

Touching grass while you're outside might yield highest leverage.

Out of curiousity why do you not refill tokens in this case? When I'm actively working on a project I'm prone to spending a few hundred dollars per day or a few thousand during the initial buildout of a new module etc.

Will the foundation for a skyscraper ever be dug with shovels again?

You’re still the one that’s controlling the model though and steering it with your expertise. At least that’s what I tell myself at night :)

I haven’t really thought about this before, but you’re right, it feels a bit uneasy for me too.

"Every augmentation is also an amputation." – McLuhan

https://driverlesscrocodile.com/technology/neal-stephenson-o...

You are now a manager. If your minions are out sick, project is delayed, not the end of the world.

> than mentally wearing myself out reading a bunch of LLM generated code trying to figure out how to solve the problem manually.

That's probably a bad sign. Skills will atrophy, but we should be building systems that are still easy to understand.

Have a pet project never touched by LLM. Once the tokens run out, go back to it and flourish it like your secret garden. It will move slowly but it will keep your sanity and your ability to review LLM code.

The meta here is to use LLMs to make things simpler and easier, not to make things harder.

Turning tokens into a well-groomed and maintainable codebase is what you want to do, not "one shot prompt every new problem I come across".

Not sure what you're doing then, or what kind of jobs you all work in where you can or do just brainlessly prompt LLMs. Don't you review the code? Don't you know what you want to do before you begin? This is such a non issue. Baffling that any engineer is just opening PRs with unreviewed LLM slop.

Suspect it will be like turn based directions for driving - soon we will have a whole group of people who can barely operate a vehicle without it

> It's literally higher leverage for me to go for a walk if Claude goes down than to write code because if I come back refreshed and Claude is working an hour later then I'll make more progress than mentally wearing myself out reading a bunch of LLM generated code trying to figure out how to solve the problem manually.

Taking more breaks and "not working" during the work day sounds like something we should probably be striving to work towards more as a society.

i wonder if this is how engineers felt when the first electronic calculators came out and engineers stopped doing math by hand.

did we feel uneasy that a new generation of builders didn't have to solve equations by hand because a calculator could do them?

i'm not sure it's the same analogy but in some ways it holds.

soooooo about Claude going down. we're gonna need you to sign in on Saturday and make up for lost time or unfortunately we're going to have to deduct the time lost from your paycheck. and as an aside your TPS reports have been sub-par as of late..is everything OK?

That's why local models are important.

Of course they aren't alternative to the current frontier model, and as such you cannot easily jump from the later to the former, but they aren't that far behind either, for coding Qwen3.5-122B is comparable to what Sonnet was less than a year ago.

So assuming the trend continues, if you can stop following the latest release and stick with what you're already using for 6 or 9 months, you'll be able to liberate yourself from the dependency to a Cloud provider.

Personally I think the freedom is worth it.

It makes me uneasy because my role now, which is prompting copilot, isn't worth my salary.

Totally. That is why it is key important to have open source and sovereign models that will be accessible to all and always.

At the end of the day, all these closed models are being built by companies that pumped all the knowledge from the internet without giving much back. But competition and open source will make sure most of the value return to the most of the people.

Very well put, and it mirrors my own thoughts.

You are that guy in early 1900s who would rather ride a horse than get in a car because cars "continued to make him uneasy."

I actually don't mind the coding part, but the information digging across the project is definitely by orders of magnitude slower if I do it on my own.

Help. They’re constantly trying to make me try crack cocaine on the front page.

"when the tokens run out, I'm basically done working."

Oh stop the drama. Open source models can handle 99% of your questions.

Given that it’s so easy, would you still do this same job if paid half as much?

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eh this kind of FUD needs to stop because it is kind of normal and expected and in fact good to have relation like this with technology.