The sad thing is that may not be true. If you use LLMs to write docs and actually read it, you can spend far longer trying to convince the LLM to write in a sane way than to just write it yourself.
Semi related, but i've caught myself nitpicking small things from the code of an LLM only to realize i'm putting in more work trying to convince the LLM to make the code the way i want rather than just modifying it myself lol. It's as if i'm trying to educate it in the ideal way, as if it would learn and not repeat the mistake.. but it rarely does of course.
It seems to me that interacting with LLMs has a large pile of cognitive traps for humans.
Oh don't, I remember being at a Google PWA Conference where they showed a world where you walked up to a coffee machine which served you a website over some local Bluetooth beacons, you asked for a coffee and it made it. It was such a hopeful concept looking back.
You managed to say everything but the difficult bit. People don't generally have a problem with cameras, all our computers and phones have one. The problem is who can use them and when.
There are some of us who do have problems with cameras on computers/phones, and will take steps to disable or obscure them, if removal or purchase without such a feature isn't an option.
What is there to mock? Making ten smart rings because each one is consumable sounds worse for the environment than making one that has a simple charging circuit?
Well, it would have gone something like this, what I would have said: smart rings everywhere, littering the streets! Landfill sites, crammed full with smart rings! Towering trash heaps of smart rings, unmanageably vast, on fire, falling on us in an avalanche of smart ring pollution, what will we do! This might sound ridiculous, but it all adds up. We have to be concerned about every little bit of waste, because our concern successfully prevents it, as can clearly be seen nowhere.
Rip the band-aid. You don't own your email, which means all the things you're worried about could at any moment be lost anyway.
Buy a domain, own the MX records, send your emails where-ever you want. Then just try live your life, and anytime you log into something, try swap it over to your new domain.
Keep your gmail, keep it as the backup email. Just reduce your risk.
Anecdotal but over several years with an AMD GPU in my desktop I've tried multiple times to do real AI work and given up every time with the AMD stack.
Im running fine on my AMD 7800xt 16gb... Yes memory is a bit limited, but apart from the i have found that it works great using Vulcan in LM studio for example.
ROCm works great too, the only issue i have had is that my machine froze a couple of times as it used 100% of the graphics and the OS had nothing left. Since moving to vulcan i stopped getting these errors apart from a little UI slowdown when i had 4 models loaded at the same time taking turns.
Im also on a i7 6700 with 32gb DDR4 so im sure that is causing more slowdowns then the graphics card.
I think it's more: when I don't have access to a compiler I am useless. It's better to go for a walk than learn assembly. AI agents turn our high-level language into code, with various hints, much like the compiler.
If my compiler "went down" I could still think through the problem I was trying to solve, maybe even work out the code on paper. I could reach a point where I would be fairly confident that I had the problem solved, even though I lacked the ability to actually implement the solution.
If my LLM goes down, I have nothing. I guess I could imagine prompts that might get it to do what I want, but there's no guarantee that those would work once it's available again. No amount of thought on my part will get me any closer to the solution, if I'm relying on the LLM as my "compiler".
What stops you from thinking through the problem if an LLM goes down, as you still have its previously produced code in front of you? It's worse if a compiler goes down because you can't even build the program to begin with.
In my opinion, this sort of learned helplessness is harmful for engineers as a whole.
Yeah I actually find writing the prompt itself to be such a useful mechanism of thinking through problems that I will not-infrequently find myself a couple of paragraphs in and decide to just delete everything I've written and take a new tack. Only when you're truly outsourcing your thinking to the AI will you run into the situation that the LLM being down means you can't actually work at all.
An interesting element here, I think, is that writing has always been a good way to force you to organize and confront your thoughts. I've liked working on writing-heavy projects, but often in fast-moving environments writing things out before coding becomes easy to skip over, but working with LLMs has sort of inverted that. You have to write to produce code with AI (usually, at least), and the more clarity of thought you put into the writing the better the outcomes (usually).
Why couldn’t you actually write out the documents and think through the problem? I think my interaction is inverted from yours. I have way more thinking and writing I can do to prep an agent than I can a compiler and it’s more valuable for the final output.
I think if you're vibe coding to the extent that you don't even know the shapes of data your system works with (e.g. the schema if you use a database) you might be outsourcing a bit too much of your thinking.
This. When compilers came along, I believe a bunch of junior engineers just gave up utterly on understanding the shape of how the code was generated in assembly which was a mistake given early compilers weren't as effective as they are today. Today vibe-coders are using these early AI tooling and giving up on understanding the shape, and similarly struggling.
Still misses the mark. You aren’t useless in the same way because you are still in control of reasoning about the exact code even if you never actually write it.
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