791–800 of 1001 posts
Or should I say... Everybody thinks that titles using the format "everybody thinks X" would be more honest if they instead said: "I believe X."
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but the opposite is actually true. u can use ai to bypass a lot of SaaS solutions
So you are saying now that you can bypass a lot of solutions offered by a mix of small/large providers by using a single solution from a huge provider, this is the opposite of a centralization of power?
The parent didn't say that though and clearly didn't mean it.
Smaller SaaS providers have a problem right now. They can't keep up with the big players in terms of features, integrations and aggressive sales tactics. That's why concentration and centralisation is growing.
If a lot of specialised features can be replaced by general purpose AI tools, that could weaken the stranglehold that the biggest Saas players have, especially if those open weights models can be deployed by a large number of smaller service providers or even self hosted or operated locally.
That's the hypothesis I think. I'm not sure it will turn out that way though.
I'm not sure whether the current hyper-competitive situation where we have a lot of good enough open weights models from different sources will continue.
I'm not sure that AI models alone will ever be reliable enough to replace deterministic features.
I'm not sure whether AI doesn't create so many tricky security issues that once again only the biggest players can be trusted to manage them or provide sufficient legal liability protection.
I feel like there is an absurd amount of negative rhetoric about how AI doesn't have any real world use cases in this comment thread. I do believe that the product leadership is shoehorning it into every nook and cranny of the world right now and there are reasons to be annoyed by that but there are also countless incredible use cases that are mind blowing, that you can use it every day for. I need to write about som…
What I feel is people are denouncing the problems and describing them as not being worth the tradeoff, not necessarily saying it has zero use cases. On the other end of the spectrum we have claims such as:
> countless incredible use cases that are mind blowing, that you can use it every day for.
Maybe those blow your mind, but not everyone’s mind is blown so easily.
For every one of your cases, I can give you a counter example where doing the same went horribly wrong. From cases being dismissed due to non-existent laws being quoted, to people being poisoned by following LLM instructions.
> I'm worried about some of the problems LLMs will create for humanity in the future but those are problems we can solve in the future too.
No, they are not! We can’t keep making climate change worse and fix it later. We can’t keep spreading misinformation at this rate and fix it later. We can’t keep increasing mass surveillance at this rate and fix it later. That “fix it later” attitude is frankly naive. You are falling for the narrative that got us into shit in the first place. Nothing will be “fixed later”, the powerful actors will just extract whatever they can and bolt.
> and as we add them in smart ways to systems that exist today, things will only get better.
No, they will not. Things are getting worse now, it’s absurd to think it’s inevitable they’ll get better.
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> There are many valid critiques of AI, but “there’s not much there” isn’t one of them. "There's not much there" is a totally valid critique of a lot of the current AI ecosystem. How many startups are simple prompt wrappers on top of ChatGPT? How many AI features in products are just "click here to ask Rovo/Dingo/Kingo/CutesyAnthropomorphizedNameOfAI" text boxes that end up spitting out wrong information? There's cer…
> simply because the market has never really punished people for being less efficient at their jobs In fact, it tends to be the opposite. You being more efficient just means you get "rewarded" with more work, typically without an appropriate increase in pay to match the additional work either. Especially true in large, non-tech companies/bureaucratic enterprises where you are much better off not making waves, and bei…
Its why unions, associations, professional bodies, etc exist for example. This whole thread is an example -> the value gained from efficiency in SWE jobs doesn't seem to be accruing value to the people with SWE skills.
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Then what do they have? Is the siren song of "AI effect" so strong in your mind that you look at a system that writes short stories, solves advanced math problems and writes working code, and then immediately pronounce it "not intelligent"?
Based on the absolute trash I usually get out of ChatGPT, Claude, etc, I wouldn’t say that it writes “working” code.
Seeing an AI casually spit out an 800 lines script that works first try is really fucking humbling to me, because I know I wouldn't be able to do that myself.
Sure, it's an area of AI advantage, and I still crush AI in complex codebases or embedded code. But AI is not strictly worse than me, clearly. The fact that it already has this area of advantage should give you a pause.
Someone wrote on HN the (IMO) main reason why people do not accept AI. AI is about centralisation of power So basically, only a few companies that hold on the large models will have all the knowledge required to do things, and will lend you your computer collecting monthly fees. Also see https://be-clippy.com/ for more arguments (like Adobe moving to cloud to teach their model on your work). For me AI is just a natur…
While for programming task I do use Claude currently, local models can be tuned to serve 80% of the time reduction you win by using AI. Depends a bit on the work you do. This will improve probably, while frontier models seem to hit hard ceilings.
Where I would disagree is that joining concepts or knowledge works at all with current AI. It works decently bad in my opinion. Even the logical and mathematical improvements of the latest Gemini model don't impress too much yet.
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The hate starts with the name. LLMs don't have the I in AI. It's like marketing a car as self-driving while all it can do is lane assist.
Then what do they have? Is the siren song of "AI effect" so strong in your mind that you look at a system that writes short stories, solves advanced math problems and writes working code, and then immediately pronounce it "not intelligent"?
Same for short stories, it doesn’t actually write new stories, it rehashes stories it (probably illegally) ingested in training data.
LLMs are good at mimicking the content they were trained on, they don’t actually adopt or extend the intelligence required to create that content in the first place.
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I've generally found an inverse correlation between "understands AI" and "exuberance for AI". I'm the only person at my current company who has had experience at multiple AI companies (the rest have never worked on it in a production environment, one of our projects is literally something I got paid to deliver customers at another startup), has written professionally about the topic, and worked directly with some big…
Personally, I don't understand how LLMs work. I know some ML math and certainly could learn, and probably will, soon. But my opinions about what LLMs can do are based on... what LLMs can do. What I can see them doing. With my eyes. The right answer to the question "What can LLMs do?" is... looking... at what LLMs can do.
One key thing that people prefer not to think about is that LLMs aren't created by humans. They are created by an inhuman optimization algorithm that humans have learned to invoke and feed with data and computation.
Humans have a say in what it does and how, but "a say" is about the extent of it. The rest is a black box - incomprehensible products of a poorly understood mathematical process. The kind of thing you have to research just to get some small glimpses of how it does what it does.
Expecting those humans to understand how LLMs work is a bit like expecting a woman to know how humans work because she made a human once.
The distinction between "real products" (solving actual problems) and "hype products" (exciting investors) reflects a pragmatic engineering perspective.
The situation seems less about AI itself and more about corporate dysfunction using AI as cover for broader organizational failures.
I understand why people are irritated by this.
However, recently I tried the GitHub Copilot agent with VS Code using Claude Opus 4.5. It literally implemented, tested and fixed entire new features in minutes, that otherwise would have taken days or even weeks of routine repetitive work from me. All while mimicking style and patterns in my existing codebase which made me instantly understand exactly what it was doing. I found it to be an insane productivity boost and I can see how it might be affecting hiring processes in numerous industries, especially in software engineering space.