> One engineer at NVIDIA who had early access to the model went as far as to say: "Losing access to GPT‑5.5 feels like I've had a limb amputated.”
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.
This matches my own experience and unease with these tools. I don't really have the patience to write code anymore because I can one shot it with frontier models 10x faster. My role has shifted, and while it's awesome to get so much working so quickly, the fact is, when the tokens run out, I'm basically done working.
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.
Anyway, it continues to make me uneasy, is all I'm saying.
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.
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
I'm trying to use it to pivot and improve my own problem solving skills, especially for large code base where the difficulty is not conceptual but more reference-graph size> 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.
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!
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.
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.
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.
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.
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.
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.
Will the foundation for a skyscraper ever be dug with shovels again?
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.
> 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.
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.
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.
> It's literally higher leverage for me to go for a walk
Touching grass while you're outside might yield highest leverage.
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.
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.
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
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?
You are now a manager. If your minions are out sick, project is delayed, not the end of the world.
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.
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".
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.
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.
Help. They’re constantly trying to make me try crack cocaine on the front page.
It makes me uneasy because my role now, which is prompting copilot, isn't worth my salary.
"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?
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.
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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.