I find it hard to understand how using a tool to do the heavy lifting actually imparts the skills onto you directly. Why should there be multiplicative returns when you haven't actually learned anything?
> I find it hard to understand how using a tool to do the heavy lifting actually imparts the skills onto you directly.
My primary skill is as a software engineer who builds complex systems that solve difficult real world problems. That overarching skill encompasses a wide body of sub skills, from UX to doing user case studies to writing blog posts about my work. The actual writing of the code is a non-trivial portion of that, but ideally the code falls out naturally from a correctly planned approach to the problem domain.
Futzing around with some broken API that has a bunch of "gotchas" that can only be gleaned from reading a dozen blog posts on the topic (because the official documentation sucks) is a huge time sink that is not related to any of my core competencies.
I've previously spent days going through annoying stupid code doing work that an AI can do in hours.
> Why should there be multiplicative returns when you haven't actually learned anything?
I do fear this for the generation of coders coming up now. The best way to learn is to build it from scratch once, which already fewer and fewer people have a chance to do, and AI is only going to make it worse.
It's probably not about skill but productivity. Many founders have no skills apart from getting others to do the actual work (I am not being sarcastic, that is a skill too) so for them automated agents are just another road to productivity. Not everyone is driven by curiosity or wants to learn, some people only want to 'ship'. So in that sense there can be multiplicative returns without the person becoming more technically skilled.
At least for me, I've used ChatGPT for areas where I don't really have much experience doing it nor get much out of learning how to do it better, especially if 100% correctness isn't necessary - writing job reqs/descriptions has been the best use so far. I use ChatGPT as the idea mill and take the best sounding ideas out of it and manipulate it a tiny bit for my purposes. In that sense, it makes me more "productive" because I don't need to spend so much time on a task like that and I can spend more time on a task that I have more expertise in, ie, programming.
My primary skill is as a software engineer who builds complex systems that solve difficult real world problems. That overarching skill encompasses a wide body of sub skills, from UX to doing user case studies to writing blog posts about my work. The actual writing of the code is a non-trivial portion of that, but ideally the code falls out naturally from a correctly planned approach to the problem domain.
Futzing around with some broken API that has a bunch of "gotchas" that can only be gleaned from reading a dozen blog posts on the topic (because the official documentation sucks) is a huge time sink that is not related to any of my core competencies.
I've previously spent days going through annoying stupid code doing work that an AI can do in hours.
> Why should there be multiplicative returns when you haven't actually learned anything?
I do fear this for the generation of coders coming up now. The best way to learn is to build it from scratch once, which already fewer and fewer people have a chance to do, and AI is only going to make it worse.