Computers were supposed to be bicycles for the mind, but increasingly we want them to think for us.
LLMs are, in fact, one of the few products in the past decades that - at least for now - align with this vision. That's because they empower the end users directly. Anyone can just go to chatgpt.com or claude.ai to access a tool that will understand their problem, no matter how clumsily formulated, and solve it, or teach them how to solve it, or otherwise address it in a useful fashion. That's pure and quite general force multiplier.
But don't you worry, plenty of corporations and countless startups are hard at work to, like with all computing before, strip down the bicycle and offer you Uber and theme park rides for your mind.
Oh BULLSHIT. Computer users have been empowered since the very first programming languages were invented. They simply chose not to engage with them.
Even if, the last time what you said was true was somewhere in the 80s, maybe early 90s. Afterwards, "programming" was solidly a domain of professionals, not regular users. I don't know about MacOS, but Windows didn't even ship with anything resembling a programming environment until 2010s.
Also, time and again with technology, the users didn't chose shit. Technology is thrust at them, it's first and foremost a supplier-driven phenomenon. It's the vendors that chose to gradually remove any ability of customization and end-user automation from software and devices. Initially it was under guise of UI/UX - simplify everything, avoid confusion (and making users engage with their brains). Nowadays, the software is as basic, dumb and functionality-free as it can possibly be, so the excuse shifted to security - everything an end-user can do an attacker can do, so let's take away every possible use that isn't authorized by application and OS vendors.
What makes LLMs refreshing is that, for now, they're fully general. The main chat apps don't limit what you can talk about (beyond the usual ass-covering corporate prudishness) - hell, you can use them to work around bullshit limitations regular software has to stop you from harming vendors' profits. But again, only a matter of time - users will get disenfranchised again as near-raw access to LLMs gets replaced by "AI apps".
And what do I mean limitations? Think of Copilot in Microsoft Office. If you used it in the past year, you definitely know its limitations. A monkey could hook up GPT-4 to VBA and get more functional Copilot than what Microsoft gave us. But it's not because they can't make powerful assistant - that's the easy part. The challenge they took is making as weak assistant as possible that does anything useful at all. That's the prevailing attitude in software industry, and it has been for good two decades now.
I'm not sure I agree completely...back in the day on the Mac we had Hypercard, RezEdit, and I do recall various code builder tools that someone could kinda wire up small tools - think things we called "4GLs". On Windows, Visual Basic was a full programming language and tooling, but I distinctly recall lots of non-programmers creating small office scripts and tools. In the late 90s we had things like FrontPage where non-programmers could wire up a simple web page and make it do things they wanted...
Today? Open up Xcode and stare into the abyss of confusion. Apple has made these "Playground" tools - man, that's a big jump for someone who isn't serious about programming to get from there to a full-fledged Swift app ready to deploy. Can generative AI tools bridge this gap for non-programmers? Possibly, but I think we're aligned that these tools aren't likely to replace us anytime soon, because of something you allude to - what's possible today is so much more complex than what we were building in the 80s and 90s, and AI isn't close to being able to replicate all of layers of stuff a professional programer wades through every day.
MacOS only really started doing that with OS X. The classic environment had an undocumented (to normal people) debugger for a console, and likewise HyperCard did exist but I never once saw documentation explaining how to actually use it (perhaps I was looking in all the wrong places?)
I eventually found REALbasic on a magazine cover CD, and paid a lot of pocket money for an educational version of Metrowerks' C compiler that only output 68k-series binaries, neither of which my machines (or OS upgrades) arrived with.
But some people are willing to learn brutally hard.
(As a father facing the challenge now, I wonder if it's harder for the kid or for the parent...)
I like the implication that they might drive you into the median or the side of a semi truck. Very apt analogy - we built it because we could, without asking whether we should
So if I can outsource the mundane, annoying and repetitive parts of SW development (like typing the coding) to a machine, so that I can focus on the parts I enjoy (debugging, requirements gathering, customer interaction, architecture etc), what's wrong with that?
If the end product is good and fulfills the customers needs who cares if a large part of it was written by a machine and not by a human?
I also wish we can go back to the days we were coding in assembly in stead of say JavaScript, but that's not gonna happen professionally for 99% of jobs, you either use JS to ship quickly or get run over by the companies who use JS while you write assembly. ML assisted coding will be the next step.
Sure, we can! That's in some sense what computers are. It's nice that they can quickly multiply two integers far faster than you can. Handing off that mental chore to the computer allows you to do your job better in every way.
The difference (and yes, I know that I'm perhaps falling into the trap of "but this time it's different!") is that AI models are very often used in a completely different capacity. You inspect the plates, load up the dishwasher, run it, and inspect the results. You don't just wave your hand over the kitchen and say "this dirty, do fix", and then blindly trust you'll have clean cutlery in a few hours.
Moreover, the menial tasks and assembly-line work that you describe are all repetitive. Most interesting coding isn't (since code has zero duplication cost, duplicate work is pointless – outside of the obvious things like fun and learning, but you want to keep those out of this discussion anyway).
> So if I can outsource the mundane, annoying and repetitive parts of SW development (like typing the coding) to a machine, so that I can focus on the parts I enjoy (debugging, requirements gathering, customer interaction, architecture etc), what's wrong with that?
Nothing is wrong with that. Except you'll still need to inspect the AI's output. And in order to do that, you'll need to have a good understanding of the problem and how it solved it. Maybe you do. That's excellent! This discussion is lamenting that, seemingly, more and more people don't.
That's ok when you already understand programming and can guide the codegen and step in to correct when it generates bullshit. But you don't get to that level without learning programming yourself. Education is built from the ground up towards higher and higher levels of abstraction. You don't get to skip learning arithmetic on your way to learning quantum physics, just because numpy will do all your arithmetic once you get there. In other words, it's ok for people who don't like cooking to order takeout, but you don't become a professional cook this way.
How many people who write SW professionally worldwide, know everything about the OS underneath, the sys-calls, disassembly, memory allocation, CPU architecture, network layers, internet routing, cloud and virtualization, etc?
Most SW jobs are just routine plumbing, connecting one FOSS pipe to another in whatever way works for you, till you get the desired result which often is unoptimized slop but if it serves the business use case and makes money nobody but the cool-aid drinking stickler developers care that it's slop. It's not rocket science that requires you to know assembly or CPU architectures or linear algebra and optimize ever single bit to perfection, but low cost and time to market is more important.
You can try to educate people about everything but not all jobs are gonna require you to know everything. In fact, jobs are being more and more specialized where you'll have one HW expert, one networking expert, one compiler expert, one typescript expert, one GoLang expert etc.
The article isn’t about code, and on HN we default to that all the time.
Which is understandable. All societies are constrained by lack of experts / intelligence. Think about how relatively inaccessible healthcare is, even in rich countries.