Comment by toastmaster11
18 hours ago
How much pontificating needs to be done before people acknowledge nobody has any idea what to do with AI on an individual level?
First being good developer and learning how to use AI was sufficient, next it was being able to design architecture, then it was “taste” that made all the difference and now being an expert in the domain is the only thing that matters really.
Until AI is basically in a stable, predictable, state of improvement or stagnation, these takes will continue to be pointless and most likely completely wrong.
An idea that's beginning to solidify for me is that AI tools make software development harder.
It's harder because they dramatically raise the bar for what's possible to do. An individual developer can take on significantly more challenging projects now, because the ultimate constraint has always been time and AI can help you get more done in the time available.
But the stuff you can get done with that time is a whole lot harder. You have to understand lots more things, and get radically outside your pre-AI comfort zone.
It used to be acceptable to spend several days refactoring a codebase, or figuring out how to ship a small feature because it's in a part of the system you hadn't worked in before or involved learning a new library in order to build it.
Coding agents mean you can climb those curves a whole lot faster, but you still need to climb them - and the volume of information coming your way is much higher.
If you're worried about non-technical vibe coders taking your job, the correct response is to be much better at building software than those vibe coders. That means you need more skill, more ambition, and more experience. It's hard!
From that perspective, development has always been harder since I started. I left college with a copy of K&R and remembering courses that applied to real life immediately, because data structures and such were just what we had. In my first job, I ended up writing a code generator to help serialize a large number of data structures, straight from a compiler design class.. which right now you don't need to know a thing about, because serialization and languages with introspection are everywhere. The knowledge you need to be a professional engineer just kept going up through the last 30 years, while most of the basics became far less relevant, because the libraries just did it.
AI raises the bar again, as its probably at least as good as me, if not better, at anything I learned in college. I've spent years living off of random trivia from the last 30 years, as I saw computing grow with me. How do you know this?! Because everything built on top of it didn't exist when I was your age, so I had to learn it! But well, nowadays the AI is better at that trivia too.
The world moves, we do what we can with what we kno. It's not just programming, but what innovation and automation has done to the vast majority of things humans have done to be productive for each other since humans are people. We'll have to cope, like the guy that bred oxes to pull the plows.
So in essence: it got harder because the easier parts have been solved for?
> If you're worried about non-technical vibe coders taking your job, the correct response is to be much better at building software than those vibe coders. That means you need more skill, more ambition, and more experience. It's hard!
This is a false fear. The real risk isn't that some 19 year-old vibe coder is going to replace you, it's that there's simply less need for more experienced engineers. The market is shrinking.
Also, even if the premise behind the SaaSpocalypse is naive and oversimplified (companies aren't going to replace all their SaaSes with internally vibe-coded replacements), it looks reasonable that net-net AI will have a negative impact on the value of software.
> The real risk isn't that some 19 year-old vibe coder is going to replace you, it's that there's simply less need for more experienced engineers. The market is shrinking.
That last sentence is verifiably false if you look at SWE job postings and their recovery since 2022.
It’s also a poor take in general, buying very much into the narrative propagated primarily by OpenAI and, especially, Anthropic, who nonetheless continue to hire large numbers of SWEs while paying double the market rate.
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I worry this is looking at where the ball is now instead of where it's going. The recent disproof of an Erdos conjecture should put to rest the idea that LLMs will reach a skill ceiling before they reach superintelligence.
I believe we are headed for a world of superintelligent AI where LLMs are much better at logical thinking than humans, the same way that chess engines are much better at chess than humans.
In that world there's really nothing humans can offer in terms of logical thinking other than their humanity itself. An 8 year old with Stockfish can beat Magnus Carlsen, and an 8 year old with Codex (and daddy's credit card) will be able to beat me at software engineering.
I don't buy that at all.
It doesn't matter how great the LLMs get, the act of creating software using them will still require a great deal of skill.
Most people just don't think in terms of software.
Try asking a non-developer in your life what their dream software would be for their work, or their hobby. If they don't have what Nilay Patel calls "software brain" I'd be surprised if they came up with something actionable.
(For more on software brain see "THE PEOPLE DO NOT YEARN FOR AUTOMATION", which makes the point I"m making here but much, much better: https://www.theverge.com/podcast/917029/software-brain-ai-ba...)
You could give a non-developer the smartest LLM in the world and they wouldn't be able to create GitHub with it, because creating GitHub requires an enormous amount of understanding of what software developers need from a cloud source control tool.
Sure, you can argue that the LLM "knows" what GitHub needs already and can guide their human-user to that, but why would a human-user who doesn't understand the domain ask an LLM to do that in the first place?
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I personally don't see that much sense worrying about this scenario because if it comes true then it doesn't really matter what I do.
If building software (and even programming, as the basis for it) was just an expression of logical thinking, we would have cornered it long time ago IMO.
But then again, logic is really a lot more discrete and well defined and easily expressed with traditional computing than LLMs are (which are probabilistic systems instead and as such require large knowledge bases).
We can observe that at a couple hundred billion parameters they behave similarly to a point (in the sense that they can produce similar results), but the challenge is really in understanding the problem's multifaceted structure and competing needs and priorities.
Are you confident in putting a timeline on this prediction?
One of the reasons I'm increasingly skeptical of this prediction is that I've now lived past a few of the dates I heard people put on the achievement of this level of superintelligence in previous years.
Chess and proofs only work as comparisons to the extent that you can find parts of your job that share their key property: A solution is sought to a problem that can be stated with relatively little information.
What prompt would someone have used to get a superhuman coding agent to output the Linux kernel or GTA5?
Before you accuse me of moving the goalposts, that's not my point: The examples are there to help think about what humans would still need to do to build complex projects even if the coding itself was perfectly reliable.
Both the Linux kernel and GTA5 contain a large amount of incompressible information; humans thought long and hard about how to design them, i.e. about what that thing they were building was even supposed to be.
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> In that world there's really nothing humans can offer in terms of logical thinking other than their humanity itself.
By your logic anyone who's not in the top 10% of intelligence can't offer anything. The world keeps spinning.
> An 8 year old with Stockfish can beat Magnus Carlsen, and an 8 year old with Codex (and daddy's credit card) will be able to beat me at software engineering.
That's just nonsense, nobody will work with 8 year old (it's illegal, to start with). Go touch grass.
That's true but in a way it's also more fun and engaging because the tedious stuff just gets worked through leaving you to think about the bigger picture items.
Though I'll say I don't buy the stuff about AI "democratizing" development since making it much more capital-intensive kind of has the opposite effect for anybody doing dev work at home.
That's a roundabout way of saying it makes software development easier. Perhaps even a 180.
But yes - once it's that easy you have to step up your ambitions.
Maybe it makes software development easier, but a career as a professional software engineer harder.
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> If you're worried about non-technical vibe coders taking your job
I'm not worried about non-technical vibe coders taking my job. I'm worried about psychotic VCs and CEOs putting me on the street in the name of "optimization" of "lower value human capital".
I had the same thought recently, I've had it happen to myself.
I've been working on something relatively large and greenfield recently.
A big chunk of my time is spent thinking about the hard parts. The raw information processing rate needed to keep up with the state of the project is high.
It feels almost like mental athleticism, whereas coding used to be a rather chill activity.
developers now are expected to randomly jump around projects and ship without friction. For employers it means they can move us around like pawns. Lot of companies have not reorged themselves to this new type of workforce thats much more malleable.
it used to be that i pay your due at some enterpise and learn some corner of codebase really well and become go to person. that would give you job security.
Working in silos like this has always been an anti pattern though. You end up being employed for 10 years but only have 1 year of actual development experience. Just turning-the-crank and going home was always risky because one day you get laid off and realize you’re 10 years behind the competition.
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So what enables job security now?
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> developers now are expected to randomly jump around projects and ship without friction
This describes the expectation my managers had of me at every software job I've had, and I've been doing this for a decade and a half
It's definitely not a new thing since LLMs came around, if that is what you were implying
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> it used to be that i pay your due at some enterpise and learn some corner of codebase really well and become go to person. that would give you job security.I
I had the displeasure of working with those types. One of them replies to any question or challenge to a technical problem emerging from the PRs they posted with variants of "I've worked here for over a decade, this is how we do things". And then proceeds to argue things like defensive programming is a code smell because it means developers don't trust themselves.
I cannot envision any healthy, effective engineering environment where developers don't periodically switch between projects.
You will never beat the vibe coders.
The vibe coders have a key advantage you don’t: they don’t give a fuck.
They blow through a task and move onto the next one. Management sees this as progress, and the vibe coders are rewarded.
When shit breaks later on down the line, and fires have to be put out and things rewritten, the vibe coders do NOT get the blame. They do NOT get punished. Most engineering teams operate on a blameless culture. If code was approved for production, then it should have been good enough. Vibe coders will keep on doing what they do, and skilled experts will be left cleaning up their messes.
For anyone who actually cares, it’s over. You are not steering development anymore.
This will invariably be a problem in organizations where tokens, lines of code, PR count etc are the metrics - which happens to be in most places. I do not know if there are metrics or rewards for maintainable code, OR penalty for write code that breaks down and causes product incidents down the line. By then those engineers would have been promoted and moved on to better things.
> You are not steering development anymore.
This hasn't been the case for at least a decade. Long before LLMs.
That might be true in the short-term, but I'd be very surprised to see that hold for the long-term.
We've had plenty of technology trends in the past that have promised faster development but has later turned out to have problems. Organizations that stick around learn lessons about what works and what doesn't.
If in a year's time organizations aren't feeling severe downsides from all of the unreviewed vibe-coded junk they put into production then maybe the vibe-coders were right. I'll believe that when I see it.
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Who approved the vibe coders’ PRs?
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> The vibe coders have a key advantage you don’t: they don’t give a fuck. They blow through a task and move onto the next one. Management sees this as progress, and the vibe coders are rewarded.
This is a complete unrealistic assessment. Who do you think vibecoders are? They are yesterday's software developers using today's tools.
The people who manually write their PRs are also not giving a fuck when they break production code with spaghetti code that later has to be thrown out and rewritten. They are the same people.
The key difference is that now their output volume is much greater, and they iterate much faster. They roll out plenty of bullshit, but it also hits the fan much faster and triggers fixes at a higher rate.
People hate on vibecoders because they do exactly what your average developer does but at a much higher rate.
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Not really. The primary stopper was never time or effort. It was need (and wisdom). If a project was important enough, you’d do it. If it’s not, it falls on the wayside.
Now with LLM tools, what you got is a slew of projects their creators aren’t even interested in. It’s theater.
There's just no way this can be true. Every project I've committed to has been a bet made with incomplete information. Sometimes it pans out, sometimes it doesn't. Every time I've made one of those bets, I've had to shoulder the opportunity cost of 2-3 other 1/8th-finished but promising projects I could have driven to completion instead. Not having that opportunity cost anymore wildly changes the dynamics of what I build.
This weekend I'm playing with a SwiftUI MusicKit player (everything I'm doing lately has been Swift/SwiftUI, itself a radical change from just a couple months ago when everything was a TUI, and then a few months back from that and all the way back to 1993, when everything was a CLI) with a Responses API hookup that turns the player into an agent, with tool calls to let the model see what I've been playing. "Keep a continuous queue of music playing while I'm working in the wood shop".
Worked a treat. I'm genuinely interested in where I can take this. I have a real problem, one that's been annoying me since ~2000, which is that I "own" a lot of music but find myself stuck in an epicycle of the same 200 songs. Problem solved-ish. I never, ever, in a million years, would have built anything like this before.
It's really hard to sell me on the idea that nothing profound has changed here in terms of the projects we now pick up. Go build an operating system. I'm serious! Claude will practically one-shot it. Mine has smoltcp hooked up to a Rust virtio-net driver Claude pulled out of its butt.
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That’s the trick - always stay hard!
LLMs are an additional tool to add to your arsenal. They are not omnipotent and need care, just like any other tool.
My best effort, so far, at an analogy is a modern drill driver compared to a screw driver/brace and bit/etc:
You can get some remarkable results in a very short time compared to the "old school" gear.
You can get some "amazing" anecdotes eg "I screwed down an entire floor at 16" x 1" c/c within an hour instead of an entire day and I took loads of fag breaks" (I could have used a nail gun instead in half the time but I'll never raise that floor easily in the future, and probably done at twice the cost)
I have several on prem LLMs and access to the rest and I'm pretty sure I'll be extending my analogy to ... brand, eventually.
What I do not expect to be doing is looking for a new job. A drill driver is not a carpenter/site labourer/useful without a person!
But a modern drill absolutely 100% removes the need for a brace and bit. An LLM doesn't replace any existing tools.
From what I've heard for many devs it replaced an IDE... I still use one myself, but I've a lot of people don't anymore.
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I think we will see very limited human displacement - it'll be in narrow places where it makes sense. Much of it will just be augmentation.
Remember the OOP Hype 20 years ago? I'm still cleaning shit up from then in our codebase when everyone used patterns after skimming through the GoF book without even knowing why .... My prediction is in 20 years I will clean up the shit that was co-authored by Claude ...
https://mastodon.gamedev.place/@JeremiahFieldhaven/116654345...
OOP and GoF are not the same thing - conflating the two has been the biggest mistake everyone has made (detractors and proponents alike)
And there's nothing "wrong" with the GoF Patterns per-se. The issue was always people applying them blindly without understanding why (or more to the point, "if") they were needed. Once writing code filled with patterns became "the thing you do"... all bets were off. :-(
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I know, but they didn't.
The idea that a lot of people have in their heads is that if the code doesn't fit the need, you'll just start over completely with a fresh codebase, because it's so fast to generate it.
In other words, there won't be 20-year-old code in this future.
We'll see if that comes to pass, but there's a lot of money betting that will happen; enough to where people will disregard what the downsides are.
my roommate at the time was trying to implment all the patterns from gof book at work. it was ridiculous but hype was ridiculous.
It all feels to me similar to how spectators or laypeople judge pro sports.
Don’t quote me on this, just trying to make a point:
They’ll say you need perfect symmetry to do well in sports, which is highly correlated to development stability in the womb; higher symmetry = perfect development.
Then after some years, news will come: Bruce Lee’s one leg is shorter than the other by a significant amount, and Usain Bolt has a similar asymmetrical development.
Then they’ll flip-flop around their initial argument by claiming that they are outliers so the general rule need not apply.
brother just build what you find interesting and it may work :)
It's well established that injuries occur at much higher rates when you have asymmetries/imbalances. Not even just physical "deformities" but just when your body is shifted or twisted in some way such that you don't move with balance.
Haven’t you heard? If you don’t adapt now you’ll be left behind, never to be able to work again! Copilot? That’s so last year. Agentic engineering? You’re already late!
jibecoding is the latest thing: you insult the LLM's bloodline providing it with greater motivation to complete the code you won't review without bugs.
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Do you have a link to your paid content that will put me ahead of the curve so my career will be bulletproof? /s
> Until AI is basically in a stable, predictable, state of improvement or stagnation, these takes will continue to be pointless and most likely completely wrong.
Little thing to keep in mind about AI: a technology is only called AI while it doesn’t work yet. Once it works reliable, we give it a proper name and something else becomes AI.
"AI is whatever hasn't been done yet" - Larry Tesler https://en.wikipedia.org/wiki/AI_effect
I think it's more: AI assisted engineering is a new skill people are trying to develop and we're on this collective experimentation process, working out how to use AI for engineering with varying degrees of success.
If that's true, any statements defining what is necessary to do should be ignored in that context. I'm still interested in hearing about what people tried, what results they think they saw, and then trying to apply those findings to my own processes.
Which is to say I don't think the pontificating is pointless, but as statements of Real Truth, I agree they're likely wrong. We're too early in the game.
Being a domain expert has been more valuable than being an excellent software developer before the ai.
In 2018 I witnessed one guy with no prior coding experience who built a tool that after a month of coding was making very decent money (more than me), just because he was aware of a particular niche.
He showed me parts of his code and it was as bad as my first program, but his was solving a real life problem.
Overall I agree with this, though I do think that there will be a trend to hoard/keep-secret domain knowledge by professions. Like plumbers will try and make it a trade-secret or protected intellectual property how to change a pipe fitting.
For basic residential plumbing work the moat is not knowledge. There are already books and YouTube videos that will teach you everything you need to know. Professional plumbers can't stop that. The real moat is that most people don't have time, don't want to buy tools, and don't want to get shit on their hands.
For new construction and commercial work the moat is a contractor's license. They don't allow LLMs to take the licensing exam yet.
The moat is the difference between knowledge and know-how.
You can read all the plumbing books, but you need to get your hands dirty a few times, mess it up and fix it, to get mentally comfortable and efficient with the work
Yep. I can do basic plumbing, but I haven't touched it since I started making enough money to pay a plumber to do it for me. Plumbers are worth every dollar they charge if it means I don't have to spend two hours under a sink cursing at rusty bolts.
"Professional plumbers can't stop that. The real moat is that most people don't have time, don't want to buy tools, and don't want to get shit on their hands."
"don't want to buy tools, and don't want to get shit on their hands"
Thats closer to the truth. The rest of your post is fluff. Its pure economics, not rocket science.
How trades gate keep is time. You can’t just become a plumber or electrician on your own. You have to be an apprentice for years no matter your knowledge or skill. This is how it works in trades and unions and where the term “pay your dues” comes from. Like you have to literally pay($$) dues for years before you can move up.
There is a difference between something being a hidden/gate kept trade secret and something being easier for person X to do than person Y through a combination of real world experience and practice.
Taste, architecture, new innovations. These are all streams of tokens which are subject to the same scaling laws as code, language, and basic classification.
We are going to see a new generation of models which effectively “solves” these problems for most businesses. Likely within the next two years- then we’ll talk about some other problems which limit adoption.
I'd like to believe that stable state ends in a pair-programming structure, with a systems thinker/engineer and a domain expert.
Someone needs to spot when a linked list is better than a map. And the other needs to spot when clinical trial coding should happen before claims, audits, or patient outreach.
As software engineers we’ve now suddenly become a sort of “god of the gaps” - our existence is only justified in the (fewer and fewer) situations where the AI can’t do the job just as well on its own
I write software that makes money and AI helps me write software that makes more money.
That's a rare niche; the vast majority of software makes no money whatsoever.
What type of software do you produce?
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My comment was in response to:
> How much pontificating needs to be done before people acknowledge nobody has any idea what to do with AI on an individual level?
I explained the idea of what I do with AI on an individual level. Hope that helps.
Concurred
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Grifters are trying to get their 5 minutes of fame by posting some unhinged shower thought that they have. It's just that you're noticing it now, because it pops up in the feed. Previously they'd say some shit about Agile, OOP/Functional programming or some other bullshit, and it would be swept under the rug.
> nobody has any idea what to do with AI on an individual level?
I appreciate the frustration, but some of us are actually successfully using these tools.
you completely misread that statement
Several things can be true at once.
>How much pontificating needs to be done before people acknowledge nobody has any idea what to do with AI on an individual level?
if nobody has any idea what to do, talking about it is the right approach
So far AI has been a (genuinely) massive improvement for...
Search
It's reading my requests more clearly than (for example) Google's search input ever did, and it's got (some) understanding of how close the result (or fragments of results) are to what I want.
I can ask it about things I know about, and it can answer with strategies I hadn't thought of.
HOWEVER - I still need to understand the results AND AI can overreach - it can say (figuratively) "Oh you are searching for Event handling, therefore I will write a orchestration saga" - which, if I am not across, can get us both in trouble.
Further, we KNOW that AI has no (real) understanding of the responses - it's just token adjacency - and it fails basic logic tests
Current AI is just awesome natural language processing, but it's still got a ways to go to where I would say "It can replace people"
Edit: LLMs demonstrate (almost perfectly) the difference between correlation and causality. LLMs identify correlative patterns, but the job still needs (us) to make the causative judgments.
Thank you! That's exactly what it is. Instead of presenting you 1000 results (or 0) which you have to manually skim through, it generates 1 result as a summary. And even if there is no actual search result, it will hallucinate you 1 result (full of BS).
But because the result sounds right (and in cases with good data it actually is) people tend to trust it. I do not dismiss the potential, but for me the line is crossed when you take the result for granted without verifying and while I'm sure many here think that is implied, I bet you, at large, it is not and will be even less so in the future.
Brave New World!
> It's reading my requests more clearly than (for example) Google's search input ever did
I see this take a lot and it puzzles me.
While I think LLMs provide some advantages over traditional search in some modestly nontrivial contexts, they tend to be inferior to traditional search at its peak. I attribute this attitude to two things: the broad progressive enshittification and productization of search, and the fact that (re)search is a skill that most people tend to be bad at. Without massaging, LLMs spit out the most utterly braindead boneheaded queries, which are fine in cases where the problem is very well understood with minimum uncertainty or critical nuance. If your problem has either, God help you. But perhaps those queries are at least as good as the average human generated query
I think that the issue here is that the definition of search/results has changed (in my mind at least they were always - what knowledge are you looking for, followed by, here are the results that carry that knowledge OR point in the right direction, but I recognise that other people will hold more strict definitions)
AI has changed how I find and synthesise information in ways Google never managed - we've always had the problem with Google that we couldn't express exactly what we were looking for - that much I think we can both agree has changed dramatically for the better with LLMs
Edit: I have always held that searching for an answer (whether it be internet or human) has always been about asking the right person, the right question, at the right time.
LLMs most certainly improve that - I don't need to know the exact technical term I am looking to solve in order to get the results I want (eg. I can ask how to "stop (a) function from running too many times" instead of the industry terms "throttling" or "debouncing")
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Hype folks need to move those goal posts to justify all the money and time invested into something we are starting to realize is a liability.
All of those things matter. One needs to be able to judge the solution in order to make a judgement if it is fine, or not. Why yes, and why no. No matter who you export the typing process to. LLMs are just tools speeding up the typing process.
I think what matters is.... the person being intelligent. I do not mean this as an us vs them thing, but a LOT of companies have some not very smart people in and running them. It's never about exact skills or roles.
My observation on AI is that some frankly less intelligent folks think they don't need smart people any more because AI makes them smarter. I disagree.
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