Beyond the question of should we trust Sam Altman to control our future - why on Earth should we want any single individual to control our future at all?
1,630 karma · joined January 3, 2025
Oh it's a product? What does it do? Leak data and delete inboxes? I would not call that a "product" at least not in the commercial sense.
> I don’t wanna dox myself but last year my company developed a greenfield product with a pretty large headcount of eng (multiple teams)that was built with an AI first development workflow
Yeah you sure are not "doxxing" yourself with this generic statement. I am sure you guys built something with the "AI first" workflow. The point being, based on what he AI CEOs and AI boosters are saying, this should have been a project with one person organising a "fleet of agents" . Why wasn't it? If it still requires a large engineering headcount, what's the point of using the AI?
Also some SVP over there: '"folks", we'll measure your performance and bonus based on how much you use Gen AI:)'
Again, neither serious studies (See that METR study on dev productivity), nor the ever increasing rate of major incidents caused by AI support your statement. Not to mention the absolute lack of well known AI-produced products that we know of.
> If you are only able to think in binaries, no-AI or phd-AI, that’s a you problem.
No, you see if I were a CEO of a public ompany and I lied through my teeth to the investors and the general public, about the capabilities of my product, then I would normally go to jail. The CEOs of major AI companies are making claims that do not seem to be confirmed in reality. They have burned several hundred billion dollars so far, in pursuit of "god-level intelligence". What came out instead is "your prompting sucks" or similar level of nonsense.
I am only holding them to the standards they have repeatedly, boldly and insistently set themselves. You should be too.
So essentially like delegating all work to a beginner programmer only 10x more frustrating? Well, that's not what I would classify under "Pocket PhD" or "Nation of PhDs in a datacenter", which is the bullshit propaganda the AI CEOs are relentlessly pushing. We should not have to figure this out for them - they were saying this will write ALL code in 6 months from "now", the last time "now" being January 2026, so in little over 4.5 months. No, we should not be fixing this mess, f*k understanding the prompts and doing the code reviews of the AI slop. Why does it not work as advertised?
Because the instances of this happening are a) random and b) rarely ever happening ?
That is actually the case with a lot of bakeries these days. But the one major difference being,the baker can rely with almost 100% reliability that the form, shape and ingredients used will be exact to the rounding error. Each time. No matter how many times they use the oven. And they don't have to invent strategies on how to "best use the ovens", they don't claim to "vibe-bake" 10x more than what they used to bake before etc... The semi-automated ovens just effing work!
Now show me an LLM that even remotely provides this kind of experience.
No no no - they are not supposed "to help". They own this complete timeline of LLMs. Dario Amodei said several times over that the agents will be writing ALL CODE in 6 months. We are now at least one month into his latest instance of this promise. He also babbled a lot about "PhD" level intelligence, just like the other ghoul at that other company. THEY are the ones who promote the supposed superintelligence creeping up on us closer each day. Whatever benchmarks they always push out with new release. But we should cut them some slack, accept that we are stupid for not wanting to burn our brains in multihour sessions with LLMs and just try to figure it out? We should not accept explaining it away as merely some cheap "hype". These people are not some C-list celebrities. They are billionaire CEOs, running companies supposedly worth into high hundreds of billions of dollars, making huge market influencing statements. I expect those statements to be true. Because if they are not, and they are smart people and will know if they are pushing out untruths on purpose, well that's just criminal behaviour. Now tell me more about how "we" should figure it out.
> A hill I will happily die on is that LLM tools, including coding agents, are deceptively difficult to use. If you accepted that was true yourself, maybe you would be able to get better results out of them.
:) No mate, please drop that "getting good results" nonsense. I have been getting good results too if I babysit them, and for the record, have done a bit more with them than just various model use cases. The issue for me and a lot of other people, that with a lot of care and safeguarding and attention etc, yes you can even build something to deploy in production - and myself and my team have done so - however it is so that they are not worth all the babysitting and especially the immense mental fatigue that comes out of working with them in continuity over a longer time span. At the end of the day, for complex projects its actually faster if I shortcircuit my thinking machine to my code-writing executors and skip the natural language bollocks altogether (save for the original spec). Using LLMs is like putting additional friction in between my brain and my hands.
So you see, after so much hype and hard and soft promotion efforts ( I count your writing in the latter category), you'd think it should not be "us" figuring it out - should it not be the people who are shoving this crap down our throats?
> That's still a very tiny portion of the software developer population. I know that because I talk to people - there is a desperate need for grounded, hype-free guidance to help the rest of our industry navigate this stuff and that's what I intend to provide.
That's a very arrogant position to assume - on the one hand there is no big secret to using these tools provided you can express yourself at all in written language. However some people for various reasons, I suspect mostly those who wandered into this profession as "coders" in the last years from other, less-paid disciplines, and lacking in basic understanding of computers, plus being motivated purely extrinsically - by money - I suspect those people may treat these tools as wonder oracles and may be stupid enough to think the problem is their "prompting" and not inherent un-reliability of LLMs. But everyone else, that is those of us who understand computers at a bit deeper level, do not want to fix Sams and Darios shit LLMs. These folks promised us no less than superintelligent systems, doing this, doing that, curing cancer, writing all the code in 6 months (or is it now 5 months already), creating a society where "work is optional" etc. So again - where TF is all of this shit promised by people sponsoring your soft promotion of LLMs? Why should we develop dependence on tools built by people who obviously dont know WTF they are talking about and who have been fundamentally wrong on several ocassions over the past few years. Whatever you are trying to do, whether you honestly believe in it or not I am afraid is a fool's errand at best.
I think you have no idea what you're talking about and trying to sound technical based on some concepts you misheard somewhere.
A lot of non-tech people got into "tech" in the last years not because they were passionate about technology but because they heard they could make more money there. This was possible due to VCs throwing around money at various software companies. As a result we get statements like yours. There is one thing that I am hopeful for with the AI bubble - which is the VCs panicking out because they think "everyone will vibecode an SaaS" - and pulling out of software companies investments, causing the folks like you to go back to whatever you were doing before and leaving software to people who actually know it and do it out of genuine interest and not primarily for the money.
Well falcons are not deterministic and are trained to do something in the art of falconry, yes. Still I fail to see an analogy here as it is the falcon gets trained to execute a few specific tasks triggered by specific commands. Much like a dog. The human more or less needs to remember those few commands. We don't teach dogs and falcons to do everything do we ? Although we do teach specific dogs do to specific tasks in various domains. But no one ever claimed Fido was superintelligent and that we needed to figure him out better.
> That's what makes them hard to use! A programming language has like ~30 keywords and does what you tell it to do. An LLM accepts input in 100+ human languages and, as you've already pointed out many times, responds in non-deterministic ways. That makes figuring out how to use them effectively really difficult.
Well yes and no. The problem with figuring out how to use them (LLMs) effectively is exactly caused by their inherent un-predictability, which is a feature of their architecture further exacerbated by whatever datasets they were trained on. And so since we have no f*ing clue as to what the glorified slot machines might pop out next, and it is not even sure as recently measured, that they make us more productive, the logical question is - why should we, as you propose in your latest blog, bend our minds to try and "figure them out" ? If they are un-predictable, that means effectively that we do not control them, so what good is our effort in "figuring them out"? How can you figure out a slot machine? And why the hell should we use it for anything else other than a shittier replacement for pre-2019 Google? In this state they are neither augmentation nor amplification. They are a drag on productivity and it shows, hint - AWS December outage. How is that amplifying anything other than toil and work for the humans?
It would be funny, if by now I weren't convinced you are pushing these false analogies on purpose. The key difference between a piano and LLMs being, the piano will produce the same sounds to a same sequence of keys. Every single time. A piano is deterministic. The LLMs are not, and you know it, which makes your constant comparison of deterministic with non-deterministic tools sound a bit dishonest. So please stop using these very weak analogies.
> I really don't understand the "stop telling me I'm holding it wrong" argument. You probably are holding it wrong!
Right, another weak argument. Writing English language paragraphs is not a science you seem to imply it is. You're not the only person using the LLMs intensively for the last years, and it's not like there this huge secret to using them - after all they use natural language as their primary interface. But that's besides the point. We're not discussing if they are hard or easy to use or whatever. We are discussing if I should replace the magnificent supercomputer already placed in my head by mother nature or God or Aliens or whatever you believe in, for a very shitty, downgraded version 0.0.1 of it sitting in someone's datacenter, all for the sake of sometimes cutting some corners by getting that quick awk/sed oneliner or some boilerplate code? I don't think that's a worthy tradeoff, especially when the relevant reports indicate an objective slowdown, which probably also explains the so-called LLM-fatigue.
> Is this born out of some weird belief that "AI" is meant to be science fiction technology that you don't ever need to learn how to use?
No, actually it is born out of the weird belief which your sponsors have been either explicitly or implicitly promoting, now for the 4th year, in various intensities and frequencies, that the LLM technology will be equal to a "country of PhDs in a datacenter". All of this based on the super weird transhumanist ideology a lot of the people directly or indirectly sponsoring your writing actively believe in. And whether you like it or not, even if you have never implied the same, you have been a useful helper by providing a more "rational" sounding voice, commenting on the supposed incremental improvements and progress and what not.
Ah, the old "you suck at prompting" angle again, isn't it? If you're going to shill this hard, at least come up with something new and original, this is sounding more than desperate.
I mean it's inherently impossible, given the statistical nature of LLMs, so I am not sure are you claiming this out of ignorance or other interests, but again, what you claim is impossible due to the very nature of LLMs.
Well, yes and no. While producing two screens worth of high quality code, a.k.a. software engineering was always expensive, "coding" as such, as in producing Nth React SPA or merely typing out code that you engineered in your head, was never that expensive - most of the work is applying existing patterns. But either way, as you wrote the code yourself, you mostly had a consistent mental model of how your code should work and the key contribution was evolving this model, first in your head, then in typing out code. Now here comes the real problem for the LLMs: I think most of us would be fine if the LLMs could actually just type out the code for us after we engineered it in our heads and explained it to the LLM in English language. Alas, they do produce some sort of code, but not always, or often enough not in a way we desribed it. So unfortunately "AI" boosters like Simon are reverting back to the argument of fast code generation and an appeal to us as unwilling adopters, to "change our ways", as it shows they have no real advantage of the LLMs to put forward - its only ever the "coding" speed and an appeal to us as professionals to "adapt", i.e. serve as cleaners of LLM sh*t. Where is the superintelligence we were promised and single-person-billion dollar unicorns, unique use cases etc? Are you telling us again these are just advanced text generators, Simon?