951–960 of 1001 posts
As others have stated, I don't think we have anything to worry about. As a SWE you are expected to neatly balance code, its architecture and how it addresses the customers' problems. At best, what I've seen LLMs produce is code monkey level programming (like copy pasting from StackOverflow), but then a human is still needed to tweak it properly. What would be needed is General AI and that's still some 50 years away (…
Nice try, ChatGPT!
Nothing because I’m a senior and LLM’s never provide code that pass my sniff test, and it remains a waste of time. I have a job at a place I love and get more people in my direct network and extended contacting me about work than ever before in my 20 year career. And finally I keep myself sharp by always making sure I challenge myself creatively. I’m not afraid to delve into areas to understand them that might look “…
source: been coding for 15+ years and using LLMs for past year.
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This is spot on. It's essentially like saying "What I do in particular, is much too difficult for an AI to ever replicate." It is always in part, humble bragging. I think some developers like to pretend that they are exclusively solving problems that have never been solved before. Which sure, the LLM architecture in particular might never be better than a person for the novel class of problem. But the reality is, an…
> I would guesstimate that less than 1 out of 10,000 developers are solving truly novel problems with any regularity. And those folks tend to work at places like Google Brain. Looks like the virtue signalling is done on both sides of the AI fence.
This is just a natural consequence of the ever growing repository of solved problems.
For example, consider that sorting of lists is agreed upon as a solved problem. Sure you could re-discover quick sort on your own, but that's not novel.
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Sounds like you’re working in react. The models are orders of magnitude worse at less common frameworks and/or languages. React is so boilerplate-heavy that it’s almost a perfect match for LLMs. That said, every large react codebase I’ve worked in inevitably became really complex and had a ton of little quirks and tweaks to deal with unexpected re-renders and such. I avoid the FE when I can these days, but I’d be fai…
Not in my experience, claude seems great at writing idiomatic and performant react. You can even highlight code and ask it to spot performance issues and it will tell you where you can improve rendering efficiency etc.
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Another anecdote: when mechanical looms became a thing, textile workers were afraid that the new tools would replace them, and they were right.
Oh my, no. Fabrics and things made from fabrics remain largely produced by human workers. Those textile workers were afraid machines would replace them, but that didn't happen - the work was sent overseas, to countries with cheaper labor. It was completely tucked away from regulation and domestic scrutiny, and so remains to this day a hotbed of human rights abuses. The phenomenon you're describing wasn't an industry…
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Recovering enterprise SaaS PM here. I don't necessarily know that a lot of enterprise SaaS will disappear, but I do think that a lot of the companies that build it will go out of business as their customers start to build more of their internal systems with LLMs vs. buy from an existing vendor. This is probably more true at the SMB level for now than actual enterprise, both for technical and internal politics reasons…
Long-time enterprise SaaS PM here, and sorry, this does not make any sense. The SMB segment is likely to be the least exposed to AI, and software, and the concept of DIY software through AI. As you visualize whole swaths of human workers getting automated away, also visualize the nitty gritty of day-to-day work with AI. If it gets something wrong, it will say "I apologize" until you, dear user, are blue in the face.…
The value of a human worker is in a more meaningful apology? I think the relevant question here is who's going to make more mistakes, not who's going to be responsible when they happen. A good human is better than AI today, but that's not going to last long.
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Recovering enterprise SaaS PM here. I don't necessarily know that a lot of enterprise SaaS will disappear, but I do think that a lot of the companies that build it will go out of business as their customers start to build more of their internal systems with LLMs vs. buy from an existing vendor. This is probably more true at the SMB level for now than actual enterprise, both for technical and internal politics reasons…
For trivial setups this might work, but for anything sufficiently complex that actually hits on real complexity in the domain, it's hard to see any LLM doing an adequate job. Especially if the person driving it doesn't know what they don't know about the domain.
I mostly agree with this for now, but obviously LLMs will continue to improve and be able to handle greater and greater complexity without issue.
> Especially if the person driving it doesn't know what they don't know about the domain.
Sure, but if the person driving it doesn't know what they're doing, they're also likely to do a poor job buying a solution (getting something that doesn't have all the features they need, selecting something needlessly complex, overpaying, etc.). Whether you're building or buying a piece of enterprise software, you want the person doing so to have plenty of domain expertise.
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Recovering enterprise SaaS PM here. I don't necessarily know that a lot of enterprise SaaS will disappear, but I do think that a lot of the companies that build it will go out of business as their customers start to build more of their internal systems with LLMs vs. buy from an existing vendor. This is probably more true at the SMB level for now than actual enterprise, both for technical and internal politics reasons…
> go out of business as their customers start to build more of their internal systems with LLMs vs. buy from an existing vendor. there is going to be so much money to make as a consultant fixing these setups, I can't wait!
Short term defense is learning about, and becoming an expert in, using LLMs in products. Longer term defense doesn't exist. If Software Engineering is otherwise completely automated by LLMs, we're in AGI territory, and likely recursive self-improvement plays out (perhaps not AI-foom, by huge uptick in capability / intelligence per month / quarter). In AGI territory, the economy, resource allocation, labor vs. capital…