The two senior engineers in my org (in a FAANG) who vibe-code the most have lost literally all of their skills. Their code has become terrible and their judgment even worse.
All of this makes me selfishly excited for my own future. It's glaringly obvious that anyone who's a heavy user of LLMs is atrophying their skills in real-time. I have yet to meet a single person for whom it's not the case.
But I essentially completely stopped using them for software engineering (why isn't really relevant, but it's not because od this skill atrophy). So as the skills of everyone else is diminishing, mine is proportionally raising.
It has never been easier to get better than others. You don't need to put in more effort, just the same effort as you always have, and others will do the job of losing their skills for your own benefit.
Idk man my system design game is better than its ever been because I put in the effort to use these tools and recognize they can't do software design better than I can and because I've increased the scope of what I'm building I often have to think more deeply about the problem up front. A typical speccing sessions lasts a few hours for me on big work before I have AI start writing that work where I'm just going back and forth on what I want, points of consideration for performance, usability, structure etc pushing back on where AI (always) chooses the most naive way it wants to do something.
Every time I see an anecdote like this, A it reaffirms my belief that FAANG devs are fairly mediocre on the whole (not saying this is you, obviously there are good FAANG devs) and B it reaffirms my belief that the developers who kind of give up their thinking like this are really using the tool wrong or didn't really care about the work before AI either so its now just a quick means to an end.
> Every time I see an anecdote like this, A it reaffirms my belief that FAANG devs are fairly mediocre on the whole
I think another (partially causal?) problem is how they're managed. The whole perf circus is just ridiculous, especially the stuff recently reported about facebook. But they're all more or less like that. Steeped in that cocktail of incentives, who even knows what might happen to an otherwise excellent engineer.
But also just numerically, they can't be much above average, on average, because there are so many.
+100 on this. In addition, if you don't outsource your thinking and you're willing to go through all this, you absolutely don't need the top tier models.
I strongly believe that you cannot evaluate how good a system design is if you don't implement it by hand.
LLMs will implement what you ask them to, even if it is the wrong approach. They can be lazy and take shortcuts all the time, but they do not feel PAIN (obviously they don't feel anything and aren't lazy, I'm just personifying them but you get the point). Only when you implement by hand can you feel if the implementation of your design is painful or not, and only this signal can tell you if your design if truly good or not.
I do think LLMs are useful for design work, they are good at asking clarifications and probing questions which actually do push you to approach problems differently, but leaving implementation of designs to LLM is a recipe for disaster, and judging your own design skills when you're not implementing such designs is seriously laughable. And to be clear, it already was before LLMs, when "software architects" were just designing and then had peons implement for them.
LLMs are enabling a whole new level of bad code that is best describe by the following Jurassic Park quote: “Your scientists were so preoccupied with whether or not they could, they didn't stop to think if they should.”.
> A it reaffirms my belief that FAANG devs are fairly mediocre on the whole
Off-topic but having worked in other companies as well, I can guarantee you that this is not the case. The skill of engineers in FAANGs and other "top tier" companies is much higher than average.
> I strongly believe that you cannot evaluate how good a system design is if you don't implement it by hand.
Fwiw we both agree that LLMs should not design systems. I do the design, but otherwise I don't get how this is true, the success of a design is indicated by long term success in the system it built. You can measure this against success in the task it was deployed for via performance metrics for one. And then from a developer standpoint how easy it was to maintain later on. Success of a system is a measurement over time, but it's not some quality that can only be measured by those who built it.
> Off-topic but having worked in other companies as well, I can guarantee you that this is not the case. The skill of engineers in FAANGs and other "top tier" companies is much higher than average.
I have first hand knowledge of this so I agree to disagree. Being surrounded by google, aws, and meta folks my understanding is the best people leave faang when they get the itch to do something better with their time.
> my understanding is the best people leave faang when they get the itch to do something better with their time.
Your understanding is wrong. The extreme majority of people who leave FAANGs don't leave willingly, and are not the best, unless it's to go to even better companies like Jane Street and the like, but those are rare.
Turns out for most people, there's not much better to do during your 9 to 5 than solving problems for half a million a year.
> Turns out for most people, there's not much better to do during your 9 to 5 than solving problems for half a million a year.
Lol. I don't know I was talking with a guy yesterday who left a FAANG clearing 1.4 million / yr who's now running his own successful startup. My sample is successful founders backed by top tier VCs or exited founders who have done much better than FAANG. If you can't do more you stick around the FAANG, those who can go and do it.
You're talking about what happens to engineers who decide they want to be small business owners rather than engineers. That's orthogonal to this thread about where engineers with the best technical skills end up.
Most of the best engineers I know leave faang because the work at faang sucks. It is not orthogonal. The majority of faang work is not highly impactful work like trivially because the amount of work outstrips the amount of interesting work by an easy oom.
FAANG doesn't straightforwardly retain the best technical talent, and the median task there is routine.
> Only when you implement by hand can you feel if the implementation of your design is painful or not, and only this signal can tell you if your design if truly good or not.
I think this touches obliquely on a point I keep coming back to, that one of the most important things a codebase does is to communicate ideas about how a process should work. Yes, it also produces some binary that runs on a bunch of servers or whatever, but that's a really temporary, ephemeral artifact. The lasting thing is the idea. Making your ideas (expressed in code) easy to understand, easy to work with, and easy to evolve in time is the art of software engineering. I 100% agree, from my own experimentation with LLMs, glancing at something a model has produced and checking that it has some test coverage isn't enough to know whether it's well-engineered. You'll only find out later when you try to work with the code.
I recently did a manual exercise to force myself to keep my skills from decaying too much after about a year of using agents exclusively. My ability to go from a blank slate to software was indeed in the toilet, but my ability to reason over and edit code seems to be surviving fine. I suspect that your LLM-pilled coworkers' judgment issues are related to laziness that LLMs have enabled, rather than an inherent property of LLM use.
You can't be able to do one but not the other, they're the same thing.
> I suspect that your LLM-pilled coworkers' judgment issues are related to laziness that LLMs have enabled, rather than an inherent property of LLM use.
Does it matter? The end result is the same. Maybe the studies that the article mentions are simply showcasing the exact same effect that you're suggesting here, but it doesn't change the fact that there is indeed a negative outcome.
Not true, blank page syndrome, inertia and write vs edit flows are a known thing across disciplines. You might not think about it as much because you have a command in your package manager or framework to bootstrap projects, but imagine if you had to hand code _everything_. I'll guess there are languages/frameworks where you consider yourself quite proficient but where you couldn't bootstrap a project without checking the docs if not for the tooling.
It matters. If LLMs are like alcohol, useful but potentially dangerous, they should be treated very differently than if they're just poison. If someone's a drunk and they can't keep their lives together, it's not the alcohol's fault, it's the person's.
Yes, feeling like I had to relearn to walk. The first week was rough, everything was wired for LLM usage and autocomplete. Couldn't even type right anymore.
> I had the same experience over the past year with early coding harness at the beginning of the year, then Claude code since its release date. But after 1+year going that direction I really don’t want to continue. The novelty is gone, dealing with AI now feels frustrating and boring, I miss engaging deeply with the actual lower level technical challenges. I do not want to manage fleets of agents. I do not want to rediscover for the hundredth time that in fact all this time an agent took shortcuts for acceptance tests I rely upon and didn’t catch. Or once again get the agent to understand why and what I want it to do after its context got bloated and it start to drift completely. While I got artifacts I can use (libraries, tools, docs), including some things that I’m pretty confident are SoA I do not feel satisfied anymore knowing that I used a model to generate them, even if I was the one designing every part of it. I do feel that I’m lying anytime I come to a colleague to share a new cool tool I have made.
> YMMV but I’m personally feeling burnt out with AI coding agents and ready to go back to the old ways for my next personal project
Are you actually seeing any signs that we’re going back to how software was written before, and needing those skills in the same way? Because I sure am not seeing that right now. As someone who vibe codes 100% and has become managements favorite, while being more or less allowed to break the platform every other release I know my skills are atrophying. But it’s taking me different places in my career entirely. There’s a path to managing other engineers now that opened years before it would have previously. Even writing this makes it sound ridiculous, but that’s what’s infront of me right now. There is an entirely other set of skills that I’m interested in sharpening now. Definitely no more sitting down several hours per day and meeting about system design and integrations with others.
It's not really about going back. Evolution happens within a pattern of ebb and flow, back and forth. We never get anything perfectly right. We overdo, then course correct, rinse and repeat. Right now, we're embracing AI, but we're also noticing atrophy of skill as an effect. These may be the last generations of such craftspeople that can notice, compare, and inform as to whether there's actual loss. That future you're seeing for yourself is still being written. Stay tuned.
The article is saying that using AI degrades certain skills when AI is not available. You're claiming that AI is making people less effective even when they have access to AI. I'm skeptical of your claim.
The article's claim is probably true, but not really an argument against AI. Using keyboards degrades my ability to write by hand but that's not a good argument against keyboards. AI will become another tool that allows us to operate more effectively and at a higher level of abstraction. Just like keyboards and Python.
Now, we still occasionally need people who can write assembly (and do calligraphy). But mostly we don't.
Another tactic is to use LLMs to help you learn. That's another way to approach "It has never been easier to get better than others."
Avoiding tool use because you're afraid you won't be able to use the tool responsibly is not likely to be a winning strategy in the end. Learning to use the tool well is much more effective.
But they're also unreliable in what they present, they still hallucinate. I rather do my own research or listen to a real human on the topic who actually has an internal concept and structure of what they're talking about.
As someone who was self taught as a programmer and has a reasonable high level understanding of some CS concepts but not lots of experience applying them, and no good mentor, I’ve found working with an LLM really englightening. Asking Claude to think about “good ways to structure this” or asking how similar problems get solved in industry or high profile projects has really helped me design better solutions and avoid painfully reinventing wheels (recent eg was for a plugin type architecture).
I think a lot of academics and researchers who code but aren’t software engineers or CS majors are going to benefit, provided they take the time to prove what the model does and are curious about whether it’s doing something sensible!
Relative to a 1% coder hand rolling something then yes it’s AI slop etc. but it’s prob still raising the bar generally.
> Asking Claude to think about “good ways to structure this” or asking how similar problems get solved in industry or high profile projects has really helped me design better solutions
I think this highlights the difference between the “how do I make a ham sandwich?” approach of chat vs the “sudo make me a ham sandwich” of agentic coding.
Writing code seems more like walking to me; at least it is the most manual way of getting a computer program. Horses might be more like one of those low-code/no-code solutions (it really fits, they are useful but very opinionated, so not always cooperative). And, the situation with AI seems a bit worrying for them.
To continue the modified analogy, if your friends lost the ability to walk, you’d be quite worried, right?
"My friends can't reason as well as they used to, they've been using LLMs to do their reasoning for them." is going to be the eventual outcome. What's the point in getting more done if it ruins your mind in the process?
A very similar topic was discussed here: https://news.ycombinator.com/item?id=48392004 and I make the exact same conclusion:
All of this makes me selfishly excited for my own future. It's glaringly obvious that anyone who's a heavy user of LLMs is atrophying their skills in real-time. I have yet to meet a single person for whom it's not the case. But I essentially completely stopped using them for software engineering (why isn't really relevant, but it's not because od this skill atrophy). So as the skills of everyone else is diminishing, mine is proportionally raising.
It has never been easier to get better than others. You don't need to put in more effort, just the same effort as you always have, and others will do the job of losing their skills for your own benefit.