AI has a multiplying effect on existing technical skills

voidUpdate

> "I think AI tools are more like Iron Man’s suit. It can do incredible things, but not on its own." Someone needs to watch iron man 3...

reconnecting

> I think AI tools are more like Iron Man's suit. There's an interesting repository with 63600 stars on GitHub (1). The developer of the repository is No 1 at the GitHub's trending contributors list (2). However, it seems like the application isn't what it's described to be (3), and the developers, on their end, are unable to clearly answer whether this is real or not, as it's just messy LLM output. Proof that the suit alone doesn't make anyone Iron Man. 1. https://github.com/ruvnet/RuView 2. https://github.com/trending/developers?since=weekly 3. https://github.com/deletexiumu/wifi-densepose

martythemaniak

I think they're jumping to the right conclusions - because the impetus to get as rid of as many people as possible isn't generally based on understanding, analysis, results, or lessons learned but a FOMO-like mania spread primarily through executive-class groupchats. This is, IMO, what mitchelh referred to last week as entire companies being in the grip of AI psychosis. So while the author's points are completely true and valid, an executive will say "True, but Claude will get smarter faster than these problems and in 3 years it'll fix everything" and there's absolutely nothing you can say or do in response to this.

Waterluvian

I had an Iron Man moment last week where I was “vibe coding” a UI design with component tests live on the other screen. Iterating by asking it to move things, reduce emphasis of an element, exploring layout options, etc. The loop was near realtime and felt amazing. The code it generated was awful. The kind of garbage that people who don’t know any better would ship: it looked right and it worked. But it was instantly a maintenance dead end. But I had an effortless time converging on a design that I wouldn’t have been able to do on my own (I’m not a designer). And then I had a reference design and I manually implemented it with better code (the part I am good at).

snide

I mostly share Josh's opinion, but I think a lot of these posts that talk about Senior vs. Junior experience when working with AIs is kind of rubbish. Sure, you get better results as a Senior working with AI tooling and struggle more as a Junior. Nothing has changed in that equation except the amplification. What folks seem to avoid is that a Junior (in ANY subject) has the ability to LEARN so much faster with an AI research assistant, and that becoming an expert has accelerated for those with the personal stamina to dig deep (this as a requirement hasn't changed). I spend just as much time with my AI tooling asking questions as I do asking it to "build" or "fix" things. "How does this work?". "Can you suggest other tools?". I think some people always think about AI as an input / output relationship, when a lot of the time, the fiddling in between, with or without AI was always the important part. Yes people will suck in the beginning, against they always did. I think the good folks though will suck for a MUCH shorter time than I did getting into things. A lot of people will drop out and get discouraged. That happened before too. Learning things requires persistence. I think the only real case to be made is that AI's sense of immediate pleasure can neuter people away from running into friction. AI natives likely won't understand friction and question it.

worldsayshi

I see two points: 1. AIs aren't yet good at architecture. 2. AIs aren't yet good at imagining technically exciting stuff to build. And I agree that there's still space there to build a career in the short to medium term (plus Jevons Paradox). When both those points are no longer true we are certainly much closer to, dear I say it, agi. I suspect that (1) will be solved for somewhat limited domains in the near future using harnesses. And it could snowball from there.

akersten

Hmm. I think extrapolating from the reddit people who say "I tried vibe coding an entire app from scratch and all I said was fix this and make no mistakes and it didn't work" is a bad data source and will give you the wrong intuition. Of course it won't work when you hold it like that. But put just a tiny bit of knowledge and guidance into the prompt and AI will nail it. I didn't think this 6 months ago but today after what I've seen these models debug and accomplish in established, messy production monoliths, I'm fully convinced even the worst vibe coders are only a year or two away from being able to actually create something from scratch and have it not blow up 50 files in. So I guess I take the totally opposite stance, today's AI is the worst AI will ever be at coding , and I believe the vested interests behind AI do not plan on making it any worse at this task, so...

xnx

An "elephant in the room" is a big topic that no one is talking about. Everyone is talking about AI. Better headline: "Why AI Multiplies Developer Skills Rather Than Replacing Them"

yanis_t

> the most talented developers I know amplify what they can do with AI Not the most talented developer, but this has been pretty much my experience as well. Just keep it under control, know what and why its doing at every step, read the code, and then it will boost your productivity.

mapcars

I see this as a much more solid and mature take than those who "boo" about AI taking their jobs.

vb-8448

I don't agree, LLMs/AI does definitely have agency. Maybe not the same agency you would expect from a human being, but if you put them in a ralph loop they can go far, far away, and mostly because on how we build our world in the pre-llm era: do you need to order something (or you want to hire a hitman)? -> you can go do it on a web site or via whatsapp or by calling some API.

sarreph

I agree with the author that -- right now -- we're still in the part of the AI adoption / product development curve that it's an extreme force multiplier. I like to think of it as a normal distribution, the further away a programmer is to the right of the mean, the more their benefit. It's almost like it's their standard deviation squared (σ²). So someone like Matt Perry (as OP mentioned), who is a >99.99% programmer for argument's sake and is therefore four standard deviations away from the mean... Matt gets a (4×4) 16x multiplying effect on their productivity. Someone who is a slightly above average programmer might see a 2 or 3x boost on their productivity, which is huge(!) and might also make them fear for their job. Which tracks with the level of moral panic we are seeing and experiencing. This math kinda still holds up for "bad programmers" too (i.e. left of the mean), as in they still see a boost to their productivity (negative squared is a positive number)... but there's something iffy about their results. The technical debt is unmaintainable and because they don't _understand_ the systems that they're operating in, they end up in the "3 hour" prompt loops that the OP refers to. > Similarly, if Matt Perry handed me the keys to the Motion repository and told me to take over, I wouldn’t have the same results even though I have access to the same set of LLM tools. The question is -- how long is this multiplier going to exist for? Some people would wager "for the foreseeable long-term future"; some people think it will widen further; and some people think it will diminish or god forbid even collapse. It feels like most arguments at the moment (like this article's) are that the humans who "know what they are doing" will be able to baton the hatches and avoid being usurped by ever-capable models. I saw it in a café yesterday: someone was using a coding agent to build a marketing website for their project, getting more and more frustrated by not getting the outcome they wanted. Their friend typed a couple of sentences on their keyboard and got a "Dude! How did you do that? That was sick!" a minute or so later. "I used to build websites" the friend said. -- The friend 'knew what they were doing'. How much longer is knowing what you're doing going to be a moat?

mehagar

I just hope my employer comes to the same conclusion before I get laid off.

rasgkl

The "it is just a tool" talking point is very fashionable right now to pretend that plagiarizing material is still a meritocracy.

muldvarp

The fact that AI currently requires some human supervision to produce valuable results is not a good predictor that it will stay this way sadly. LLMs were basically unable to reason two years ago. They are now better at many reasoning tasks than most people. If there is even a remote chance that LLMs will make your job obsolete I would pivot as fast as I could. This includes first and foremost software engineering.

datakan

Back in the late 90's when the internet was really just becoming a thing with most people, a friend said something that's stuck with me all these years. "We're losing our moderate speech." Everything these days is either the greatest thing ever or the worst thing ever. All the stuff in the middle has vanished. Very few it seems acknowledge AI as being a useful tool. It's either "We're all being replaced" or "The technology is all slop" and everyone talks over each other like it's the Super Bowl and their teams are battling it out. It would be nice if we could just look to the opportunities this tech offers and focus on that.

0xbadcafebee

> AI models have become shockingly good at completing a wide variety of programming tasks. They’re certainly not perfect, but in many cases, they’re good enough. I’m not happy about this, for a wide variety of ethical/environmental/safety reasons You cannot hold a computer liable for any of those reasons. You can, however, sue the human that built or used the AI. So those concerns shoudn't be any different with or without AI. The same problems will be here either way. If you really care about those problems, you would demand your representatives in government actually enshrine those things in law, with some teeth, to ensure companies prevent problems with them. If you don't do something about those problems (with or without AI), then it's clear by your actions that ethical/environmental/safety concerns aren't actually that important to you.

therealmacsteel

We are quickly reaching a point though that programmers will become so reliant on llm for coding so much so as people have become soul reliant on their phones to remember phone numbers, the younger generations dont have a single phone number they can call to memory and soon the same will be true of code.

x187463

> Without guidance, LLMs tend to paint themselves into a corner, because they’re generating code to solve individual prompts, not thinking holistically about an application’s architecture. I've found I can prevent the LLM, in many cases, from thrashing on a bug/feature for long periods of time by switching into plan mode and, even in the middle of a conversation, having it reassess the structure around the problem, first. If you keep prompting about the same bug, it may keep producing variations of the problem code. But forcing it to stop and 'think' for a bit, has yielded much better results.

idopmstuff

I think the problem with this logic is it's based on the capabilities of LLMs today and really fails to address the prospect that they will continue to improve. I used to be a PM and am technically literate enough but can only very minimally write code. I have been using LLMs to build (or try to, at least) internal tools for my business since GPT-4. In the early days, I'd get a little ways, then the LLM would start breaking things, and I'd try but fail to get it to fix things. But over successive generations, I was increasingly able to get it unstuck by offering suggestions on where it may have gone wrong. With Opus 4.7, I don't even really have to do that - if something isn't working it's usually sufficient to just tell it what's broken. It can figure out how to fix it without my input. And of course fewer things are broken in the first place. So I think I'm very well positioned to understand how these things are improving - better able to get the LLM to do what I want than the post OP quoted from /vibecoding (though I am 99% sure that post is actually AI slop), but less so than most of the people posting in this thread. As they've improved, whatever ability I have to guess at the causes of problems based on my experience having seen things go wrong with products I've PMed has become less necessary to getting the right outcome. I expect that trend to continue - increasingly the LLM won't need the guidance of people with a great deal of technical expertise. I basically no longer have to attempt to diagnose problems in order to get them fixed, though with the caveat that I am building internal tools for which I am the only user, so certainly much simpler in scope than the stuff OP is talking about. > Without guidance, LLMs tend to paint themselves into a corner, because they’re generating code to solve individual prompts, not thinking holistically about an application’s architecture. The crux of what I'm trying to say here is that I absolutely believe that this line is 100% true today, but I would be deeply cautious about assuming that it will continue to be true given the improvements in LLMs over the past few years.