281–290 of 886 posts
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Zuckerberg, as always, is well known for making excellent business decisions that lead to greater sector buy in. The Metaverse is going great.
On the other hand, Instagram has been called one of the greatest acquisitions of all time only below the Apple/Next acquisition.
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I think that LLMs are only going to make people with real tech/programming skills much more in demand, as younger programmers skip straight into prompt engineering and never develop themselves technically beyond the bare minimum needed to glue things together. The gap between people with deep, hands-on experience that understand how a computer works and prompt engineers will become so insanely deep. Somebody needs to…
Isn’t this kind of thing the story of tech though? Languages like Python and Java come around, and old-school C engineers grouse that the kids these days don’t really understand how things work, because they’re not managing memory. Modern web-dev comes around and now the old Java hands are annoyed that these new kids are just slamming NPM packages together and polyfills everywhere and no one understands Real Software…
Everything has a place, you most likely wouldn't write an HPC database in Python, and you wouldn't write a simple CRUD recipe app in C.
I think the same thing applies to using LLMS, you don't use the code it generates to control a power plant or fly an airplane. You use it for building the simple CRUD recipe app where the stakes are essentially zero.
Some companies will try to fire as many programmers as possible and will end up struggling bc they have no moats against other companies with access to the same AI, or will hit some kind of AI saturation usefulness threshold. Other companies will figure out a smart hybrid to utilize existing talent and those are probably the ones that will thrive among the competition.
But why do you need programmers to utilize the AI? The whole point of AI is that it doesn't need an "operator". I'm not talking about GH Copilot or some autocomplete IDE feature, I'm talking about fully autonomous agents 2-3 years in the future. Just look at the insane rate of progress in the past 2 years. The next two years will be even faster if the past few months are anything to go by.
You can outsource the execution of a task but only if you know how to formulate your requirements and analyze the situation.
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They are skating where bleachers full of hype men are screaming that the puck will go.
I think the common theme is that a lot of people: meaning both people in the community, like here on HN, and people making decisions in industry, are treating AI today as if it's what they hope it will be in five years. That's a very leveraged bet, which isn't always the wrong call, but I'm not convinced they are aware that that's what they're doing. I think this is different from the usual hype cycle.
Imagine "The Innovator's Dilemma" was written in the Idiocracy universe:
1) We're in late stage capitalism, so no companies have any viable competition, customers are too dumb to notice they didn't get what they paid for, and with subsidies, businesses cannot fail. i.e., "Plants love electrolytes!"
2) Costs are completely decoupled from income.
3) Economic growth is pinned to population growth; otherwise the economy is zero sum.
4) Stocks still need to compound faster than inflation annually.
5) After hiking prices stops working, management decides they may as well fire all the engineers (and find some "it's different now" excuse, even though the real justification is 2).
6) This leads to a societal crisis because everyone forgot the company was serving a critical function, and now it's not.
7) A new competitor fills the gaps, takes over the incumbent's original role, then eventually adopts the same strategy.
Examples: Disney Animation vs. Pixar, Detroit vs. Tesla, Boeing vs. SpaceX.
(Remember when Musk was cool?)
There's such a huge disconnect between people reading headlines and developers who are actually trying to use AI day to day in good faith. We know what it is good at and what it's not. It's incredibly far away from doing any significant change in a mature codebase. In fact I've become so bearish on the technology trying to use it for this, I'm thinking there's going to have to be some other breakthrough or something…
Part of the problem is that many working developers are still in companies that don't allow experimentation with the bleeding edge of AI on their code base, so their experiences come from headlines and from playing around on personal projects. And on the first 10,000 lines of code, the best in class tools are actually pretty good. Since they can help define the structure of the code, it ends up shaped in a way that w…
This assumes a typical project is fairly big and complex. Maybe I'm biased the other way, but I'd guess 90% of software engineers are writing boilerplate code today that could be greatly assisted by LLM tools. E.g., PHP is still one of the top languages, which means a lot of basic WordPress stuff that LLMs are great at.
There's such a huge disconnect between people reading headlines and developers who are actually trying to use AI day to day in good faith. We know what it is good at and what it's not. It's incredibly far away from doing any significant change in a mature codebase. In fact I've become so bearish on the technology trying to use it for this, I'm thinking there's going to have to be some other breakthrough or something…
I try to use AI daily, and every month I see how it is able to generate larger and more complex chunks of code from the first shot. It is almost there. We just need to adopt the new paradigm, build the tooling, and embrace the new weird future of software development.
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But why do you need programmers to utilize the AI? The whole point of AI is that it doesn't need an "operator". I'm not talking about GH Copilot or some autocomplete IDE feature, I'm talking about fully autonomous agents 2-3 years in the future. Just look at the insane rate of progress in the past 2 years. The next two years will be even faster if the past few months are anything to go by.
> Just look at the insane rate of progress in the past 2 years. Are we living on the same planet? I haven't seen much real progress since the release of chatGPT. Sure brenchmarks and graphs are going up, but in practice, meh...
I am completely blind and I used Gemini Live mode to help me change BIOS settings and reinstall Windows when the installer didn't pick up my USB soundcard. I spoke, with my own voice and completed a task with a computer which could only see my webcam stream. This, to me, is a heck of a lot more than ChatGPT was ever able to do in November 2022.
If you continue to insist that stuff isn't improving, well, you can in fact do that... But I don't know how much I can trust you in terms of overall situational awareness if you really don't think any improvements have been made at all in the previous two years of massive investment.
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Part of the problem is that many working developers are still in companies that don't allow experimentation with the bleeding edge of AI on their code base, so their experiences come from headlines and from playing around on personal projects. And on the first 10,000 lines of code, the best in class tools are actually pretty good. Since they can help define the structure of the code, it ends up shaped in a way that w…
My company allowed us to use it but most developers around me didn't reach out to the correct people to be able to use it. Yes I find it incredibly helpful and try to tell them. But it's only helpful in small contexts, auto completing things, small snippets, generating small functions. Any large scale changes like most of these AI companies try to push them being capable of doing it just falls straight on its face. I…
What models are you using that you feel comfortable trusting it to understand and operate on 10-20k LOC?
Using the latest and greatest from OpenAI, I've seen output become unreliable with as little as ~300 LOC on a pretty simple personal project. It will drop features as new ones are added, make obvious mistakes, refuse to follow instructions no matter how many different ways I try to tell it to fix a bug, etc.
Tried taking those 300 LOC (generated by o3-mini-high) to cursor and didn't fare much better with the variety of models it offers.
I haven't tried OpenAI's APIs yet - I think I read that they accommodate quite a bit more context than the web interface.
I do find OpenAI's web-based offerings extremely useful for generating short 50-200 LOC support scripts, generating boilerplate, creating short single-purpose functions, etc.
Anything beyond this just hasn't worked all that well for me. Maybe I just need better or different tools though?
This article is entirely built on 2 big and wrong assumptions: 1. AI code ability will be the same as is today 2. Companies will replace people for AI en masse at a given moment in time Of course both these assumptions are wrong, the quality of code produced by AI will improve dramatically as model evolves. And is not even just the model itself. The tooling, the Agentic capabilities and workflow will entirely change…
What makes you think (1) will be true? It is only generating based on training data. In mature code bases there is a massive amount of interconnected state that is not already present in any github repository. The new logic you'd want to add is likely something never done before. As other programmers have stated, it seems to be improving at generating useful boilerplate and making simple websites and such related to…
99% of software development jobs are not as groundbreaking as this. It’s mostly companies doing exactly what their competitors are doing. Very few places are actually doing things that an LLM model has truly never seen crawling through GutHub. Even new innovative products generally boil down to the same database fetches and CRUD glue and JSON parsing and front end form filling code.
There's such a huge disconnect between people reading headlines and developers who are actually trying to use AI day to day in good faith. We know what it is good at and what it's not. It's incredibly far away from doing any significant change in a mature codebase. In fact I've become so bearish on the technology trying to use it for this, I'm thinking there's going to have to be some other breakthrough or something…
Same, LLMs are interesting but on their own are a dead end. I think something needs to actually experience the world in 3d in real time to understand what it is actually coding things or doing tasks for.
Reasoning LLMs feel like an attempt to stuff the context window with additional thoughts, which does influence the output, but is still a proxy for plasticity and aha-moments that can generate.