AI makes programming differently difficult

https://cacm.acm.org/opinion/ai-didnt-make-programming-easier-it-just-made-it-differently-difficult/

by tchalla • 1 day ago

160 141 1 day ago

cacm.acm.org

Havoc3• 1 day ago

It can be both at the same time - easier and different.

stellalo• 1 day ago

But the thesis of the OP is that it is !easier && different

Havoc3• 1 day ago

Which I disagree with hence my comment?

FinnLobsien5• 1 day ago

I think the bigger issue in defining this is that “programming” is too big a task to say whether it got easier or harder.

Some YAML formalities now take zero effort while architectural thinking became way more important and difficult.

Havoc3• 1 day ago

architectural thinking became way more important and difficult.

Did it though? I think the architectural stuff was always there and was always hard. And still is. I don't buy that it got harder now that you've got a pretty smart AI you can bounce ideas off, ask to investigate stuff, maybe make a quick mockup trivial test of both options on an architectural choice you face, send off to do research etc.

...so in my mind the aggregate {{programming}} got easier because the hard parts are still hard and the trivial parts got AI'd.

The only step up in complexity imo is wrangling a bunch of agents. Even very good coders report mental exhaustion from that

FinnLobsien5• 1 day ago

It’s the same with writing: AI writing is coherent on the surface, but is impossible to edit because it’s built on no real insight.

Now the sharpening of a coherent point, challenging one’s assumptions, and editorial decisions of what (not) to include are super important because they’re no longer a byproduct of the writing process.

snerbles2• 1 day ago

Human insight can emerge from attacking the semblance of sense in the LLM's output.

Much of the cognitive work in writing emerges in the labor of writing prose and challenging assumptions against the model you build in your head as you go. I've found this process is inverted when working with an LLM: it in effect emits a provisional structure first, and I discover what I actually think by finding where its output is vague, overconfident, incomplete or outright false.

Accepting surface-level coherence as finished thought is the failure mode to avoid.

FinnLobsien5• 1 day ago

Sure this is true. And if an AI draft helps in creating quality writing, great!

I was thinking more when it comes to stuff other people send me (like a freelance writer) and “editing” is basically writing the first draft because no cognitive effort has yet been spent on the piece

contextfree2• 1 day ago

Yeah I've written some docs using the following process:

1. Throw some notes, PR links, etc. into copilot and ask for a first draft

2. Go back and forth for a while asking for revisions

3. Trash all of the AI-generated text and rewrite the whole thing myself from scratch, which I can do quickly in a typing frenzy because I now have a clear idea what I want, by way of seeing what I don't want.

Terr_2• 1 day ago

It’s the same with writing: AI writing is coherent on the surface, but is impossible to edit because it’s built on no real insight.

LLMs lie in the unhappy-medium between an abstract machine we can reason-about versus a person we can instinctively model and simulate.

Instead it's a complicated machine that evades both reasoning and intuition.

dsmurrell• 1 day ago

It's somehow more tiring, reading complex plans in response to your guidance, and then making decision after decision. Reminds me of this Alan Watts bit...

A farmer who ordered a farmhand quickly discovered he was an extraordinarily efficient worker.

The first day, he put him on sawing logs, and the farmhand sawed more logs than anybody else, ever. It was fantastic — but the wood-cutting work was all done in one day.

So, the next day, the farmer put him onto mending fences. There were all kinds of broken fences around the farm. And, again, the farmhand had all the work done in one day.

So the farmer thought, “What am I going to do with this guy?”

The next day, he took the farmhand to a basement and said, “Look, here all the potatoes that have come in from this harvest. I want you to sort them into three groups: those we sell, those we use for seeding, and those we throw away.”

He left the farmhand to it. And at the end of the day, the laborer came back and said, “Well, that’s enough, mister, I quit.”

“Oh,” the farmer replied, “You can’t quit. I’ve never had such an excellent worker. I’ll raise your salary — I’ll do anything to keep you around me.”

The farmhand said, “No. It’s all right mending fences and chopping wood, but this potato business is decision after decision after decision.”

leke4• 1 day ago

If the AI is asking you questions and requiring you to make decision after decision, then perhaps it's a spec issue. I know I've written a good spec if the AI does not ask any questions and doesn't get anything wrong after implementing the user story.

knickish• 1 day ago

You're not wrong, but isn't that just moving the same amount of decision making to earlier in the process?

Cerium• 1 day ago

What is a spec but a collection of decisions?

tossandthrow3• 1 day ago

Historically, we make systems to make these decisions - build a method to sort potatoes. Or build a method that can build a method to sort potatoes.

Ai, as a cognitive technology, has the potential to climb that hierarchy.

Yes, current software developers need to make more decisions now. But that is just until the methodologies settle.

Then it is over.

cadamsdotcom2• 1 day ago

If you think the hierarchy has a highest level, or that abstraction can only go "this far and no further".. I don't know what to tell you.

chasd00• 1 day ago

It's somehow more tiring, reading complex plans in response to your guidance, and then making decision after decision.

This is the world of a manager working with a development team hah. When writing the code yourself is it not the same? If you're writing the code by hand then you're still making the decisions and still having to plan and design. I mean someone/something has to...

bluefirebrand3• 22 hours ago

For me, the stress about making decisions as an employee isn't about making a choice.

It's knowing that any moment a manager is going to wander along and change it from under me. So I might as well ask the manager first.

It showed up on my performance reviews that I'm bothering other people with questions and I should make my own choices, so I started doing that and documenting every time the choice I made got overturned by a manager. Next performance review when it came up I brought out my list. My performance reviewer was pissed at me for documenting this and I was let go four months later. :)

I would love a job where people let me make decisions after decision after decision

And yeah you could say that if my manager had to overturn my decisions that often it probably meant that I made bad decisions, and maybe that's true, but I don't think so. It was often things like "this is the best solution but it will take longer", "This low priority, do it the quick way instead". But priorities changed a lot.

AnimalMuppet• 7 hours ago

But for me to be able to make decision after decision, I need to know what the over-riding guidelines are. I need to know what we're trying to build, and know it well enough that I know how my part fits.

And then I need to be able to tell when I can make a decision, and when I don't have enough information to make that decision and therefore need to ask questions of someone who has a better handle on the overall picture.

bnfcl3• 1 day ago

Quote of the main point in the article:

    In other words, the hard part moves from recall (“How do I write this?”) to judgment (“Does this actually make sense?”)

This is very true. But to evaluate if it makes sense, you first need experience writing the code. I am glad I learned software development over 15 years ago, and not today. AI is a super power, but without the experience to guide it, it can go horribly wrong really quickly.

mostlysimilar• 1 day ago

That's where I've landed too. Maybe I'm just delusional and telling myself a comfortable story, but I think my ~15 years of experience building software by hand lets me utilize these robots in a way that people lacking it simply can't.

I still absolutely loathe talking to them and using them. But I feel less scared about losing my career these days. Work wants me to use it, I'm using it at work. In my hobby projects I still code by hand.

asdfman1233• 1 day ago

Yep, that's definitely true... for now.

The thing that concerns me, however, is that just a year ago it was only useful for doing things like reminding me how to read in a file. Now it's at the level of a competent junior, who can almost do the whole task from start to finish but needs a little supervision.

All the AI companies are retaining the messages we're sending to their agents to train the next models. I wouldn't be surprised if the agents will be able to do what I'm doing in a year or two.

UPDATE: I'm getting a lot of replies to this thread and while I'm not trying to be argumentative here, I have to ask if a lot of them aren't rooted in denial... it's been a hard adjustment process for me too.

gofreddygo3• 1 day ago

hobby projects I still code by hand

So true. I was too blinded to not notice the joy of my hobby getting sucked away by not doing it by hand.

guywithahat2• 1 day ago

I wonder about this. One would think new programmers, like old, will learn through experience to care most about the things that matter, and ignore things that don’t. In 10 years my pre-AI experience may condition me to waste time thinking about struct packing, while younger developers simply won’t know or care

cdkmoose• 1 day ago

I think the problem will be that there was only so much we could do wrong while we were learning 15+ years ago and our mentors had a reasonable scope to watch around us as we learned. People learning now can get a coding agent to build the entire system for them and it is much harder for the mentor to review that work.

My concern is how much damage could be done by someone learning 15+ years ago vs someone learning now.

asveikau• 1 day ago

thinking about struct packing, while younger developers simply won’t know or care

That particular ship sailed more than 15 years ago. Back then if you asked people trained on high level GC-based languages about low level details or memory allocation, they wouldn't know.

jorgeleo• 1 day ago

Yup!. Over 30 years experience here. Landed on the same place with the added feeling of "We were always intended to develop the judgement of what makes sense and maintainable, where is the surprise here?"

People want the "Fluent Text Generator" to think for them because its marketing calls it AI. At the end is just a tensor collection, probabilistically backtracked adjusted, text generator. It does produces fluency in the answer, but the fact that it sounds correct, to the point of passing a compiler approval, has nothing to do with been well thought out.

reinitctxoffset2• 1 day ago

I think it's easier to make your point without the baggage of the mechanism assertions.

The code is just wrong a lot. By denying the possibility of emergent phenomemona or model interiority you just hand the hypsters an easy point to score.

The code is just wrong, all the time. You're right about the part that matters and that we can measure.

agumonkey• 1 day ago

Yes a LLM is mostly an information memory de vice, but as a worker you still have to vet it.

I believe the human constraint made us find ways to layer and modularize systems so it is easier to check. Now the LLM produces a lot of code and abstraction have to be enforced. Something is missing.. (resonates with the latest Pocoo blog)

zombot• 12 hours ago

What is "de vice" supposed to mean?

leke4• 1 day ago

Yep, I feel fortunate that programmers that made it well before AI are going to be very sort after in a world where software development is going to explode and be in very high demand.

NuclearPM• 1 day ago

Sort?

gjvc• 1 day ago

"sought"

gofreddygo3• 1 day ago

"How can we dig a well here" and "should we dig a well here" are neither mutually exclusive nor sufficient in their own regard.

Cant answer should we without having done a lot of it before. Cant learn unless you actually do it and see the consequences through.

order-matters• 1 day ago

and yet it's also incredibly effective to be able to recognize "oh this plot is incredibly similar to these 100 other plots and there appears to be a pretty consistent pattern to what is driving where the well is built, and they are all constructed in a very similar fashion, i am just going to copy what they did"

AI is very useful when you dont need to invent anything new

techteach00• 1 day ago

This is called the bargaining phase.

typon• 1 day ago

I am using a model that runs on a 100 GB300s, near AGI, all bets are off, $10B training run on a 1GW cluster, and it can't realize that when I told it to "please implement v2 of feature X" that I mean delete v1, not support v1 and v2 together, in a weird Frankenstein's monster of the two. Sorry, but I think my job is quite secure for the forseeable future.

nphardon• 1 day ago

How many times can we have the same discussion.

ramesh31• 1 day ago

"How many times can we have the same discussion."

Until the people wishing it to be true are thoroughly sated.

The reality is that this is the end of programming as a large scale well paying white collar profession as we knew it.

leke4• 1 day ago

Today a co-worker told me he thought this would mean programmers would get more money because we have been making so much, so quickly, with much fewer bug reports, it's saving the company lots of money on man hours.

Anduia• 1 day ago

It's existential crisis Tuesday

leke4• 1 day ago

I'm stealing this for an office sign.

bigstrat2003• 1 day ago

Until the people foolish enough to think that you can replace people with an LLM learn their lesson.

ux266478• 1 day ago

Never let possibility get in the way of a value-signaling business decision, I always say.

asdfman1233• 1 day ago

Until we've all finally let go of the past.

ben_w• 1 day ago

That's the neat thing, with LLMs we can fully automate this discussion and have it at thousands of tokens per second and millions of tokens per dollar.

MangoCoffee• 1 day ago

Yeah, I believe I’ve seen this topic posted on HN many times now.

Code has always been cheap, even before AI/LLMs. It’s your ability to understand your client’s problem and come up with a good solution that’s what gets you paid.

furyofantares2• 1 day ago

It's true that there are new skills to acquire (and that those with talents for the old skills may be less talented with the new skills).

It's absolutely not true that it "just" moved the difficulty around. If that were true then I'd be just as well off continuing to use my decades of programming expertise just as I always have; but the reality is I can get more done, and get better work done (depending on level of vibing), than ever before.

Thing is, though, making programming easier doesn't mean programmers will work less hard. That's how competitive markets work. LLMs made programming easier. Capitalism prevents workers from capturing that value.

lelanthran• 1 day ago

It's true that there are new skills to acquire

What new skills?

furyofantares2• 1 day ago

Getting the most out of out agent. Knowing how to give it context that will cause it to succeed. Knowing what things it will succeed at and what it won't. Knowing how to tell when it's failing.

Figuring out when it's appropriate to fully wrap your head around the details of a solution, and when it's appropriate to let the agent handle that and only know a bunch of properties of the solution. Knowing when it's appropriate to try 10 things, throw them all away, then go deep. Knowing how to learn from these things so you can make something better, not just faster.

1970-01-01• 1 day ago

Tackling software architecture is not programming, that is architecture. They're called different things for a reason. It is now easier to write working code via AI. Anyone that can type can do it. The syntax (language) barrier is fully removed. I'm done with syntax, looking up the new right way to do things, etc. It works via prompting. Tell it what to write and it comes out the other end with a working program. That's programming, and that's not an opinion. This alone makes it easier to program.

twa927• 1 day ago

Code becomes only one representation of thought among many overlapping ones.

This is wrong, code is the concrete "truth" being executed, the rest (plans, prompts, agent instructions) are just temporary artifacts used to generate the code. What's left is the code alone.

LLMs don't have any semantics, they can't execute anything with 100% certainty. So far programming languages are the only langugues that can do that.

causal• 1 day ago

I think you misunderstand. Code is also representing something. It may be what gets executed, but that does not make it "correct".

kloop• 1 day ago

It does make it correct in the reality sense

If someone says something happens and the code says something else, the code wins.

pydry2• 1 day ago

No, I think it's correct. One artefact of programming for decades is that I ended up thinking in code directly without "translating" from English first.

Thus the push to use LLMs has felt a little bit like being a fluent French speaker being told that all of the best French writers are using google translate to write French translated from English now.

Terr_2• 1 day ago

What's left is the code alone.

The necessary work is more than just the deliverable. Even a simple patch implies an indefinite number of other approaches not-taken, and sometimes not-taken for good reasons.

Sometimes we explicitly document those, sometimes we trust that a human expert decided against them. Those other aspects of work still exist, even if they are getting skipped/mismanaged with LLMs.

chungusamongus2• 1 day ago

Nope. Code is a representation. Even low level code. The fact that you do not understand this is concerning.

bluefirebrand3• 22 hours ago

No? Code is literally instructions to the machine. Especially low level code. It's not a representation of anything, it's a list of commands in sequence for the computer to execute

The fact that you do not understand that is concerning.

kypro4• 1 day ago

It's way easier. People don't need to read code anymore, nor will they have to care about building mental models about the system as this article suggests.

The way to think about coding agents is that a good one should in theory literally replace the developer entirely. No, a whole organisation of developers.

In theory a product owner should just be able to dictate how they want to product to function at a high level and the AI should take care of the rest in the same way a human programmer or team of programmers would have in the past. If there are conflicts in what's being requested, then the AI should be able to recognise that and ask for production direction.

As always with every generation of AI people seem to way over index on the now.

- "They're good for autocomplete, that's about it"

- "They're good for quickly mocking up small functions, but they make a lot of mistakes"

- "They're good for scaffolding some parts of the system if you're good at prompt engineering"

- "They're good at writing most of the code, but humans will always need to do the last 10%"

- "They can write all of the code, but humans will still need to architect the system"

You are here. Perhaps this is where progress stops. I wouldn't bet on that however.

AI is making programming an irrelevent field.

sgarland3• 24 hours ago

If my experience with RDBMS generalizes, I predict that this trend will result in companies hiring skilled developers to unfuck their codebases.

Furthermore, I predict they will identify massive structural issues, propose huge lifts to redo it correctly, and will instead be told to do patchwork fixes to stop the bleeding.

Now, I do think AI is (or will be) good enough to implement these patchwork fixes when given explicit instructions, but someone will need to figure it out for them.

The problem is if you don’t understand the root cause, you’ll at best feed the LLM a list of symptoms, and it will dutifully fix them. “Our p99 on this endpoint is breaching” becomes “I’ve added an index for this query,” or “I’ve added a caching layer,” when the actual problem may well be that you’re storing huge blobs that bloat your working set, cause buffer pool churn, and saturate your NIC. Is the symptom solved? Yes. Is it scalable? No, you’ll next need to vertically scale the instance, which is more expensive, and has an upper bound. Eventually you’ll decide to shard, which adds complexity, when the actual solution would’ve eliminated all of those issues at once.

kypro4• 22 hours ago

The problem is if you don’t understand the root cause, you’ll at best feed the LLM a list of symptoms

Today maybe.

When Cloudflare has an outage does the CEO need to know the root cause though? If he just assigns some engineers to investigate, fix and report back to him – what's the issue with that?

Assuming you agree with my analogy, can you explain what it is that you feel an agent or group of agents assigned to an engineering tasks could not do that a human can? And if can't do it today, why do you believe it wouldn't able to do it in the future?

Are we just disagreeing about timelines here or whether humans have some magical quality which algorithms and AI can never capture?

I feel like it's reasonable to disagree on timelines. It's quite unreasonable to assume human coders are special.

yananghelp• 1 day ago

AI merely reduces the difficulty of coding, without directly increasing the difficulty of architectural judgment. It merely brings to light the actual difficulty of this task. Moreover, I believe that in the future, AI will also possess certain architectural judgment capabilities. However, the cost of such AI might even be higher than that of humans.

epolanski• 1 day ago

I don't think I write or read or code anymore, bar prs from juniors or senior colleagues wanting a review.

I didn't think it would work just 6 months ago, but reality is that at this point AI writes better code than me and I'm not the average developer, but someone who loved the craft and was good at it.

Lots of effort was required to get the repositories to a good level, best practices, documentation, etc, but reality is that once you do that and have strong rails most of your work is having it to write a plan focused on business logic, review it, have it derive an implementation plan, review it and then it's mostly on its own.

Codebases have never been healthier, cleaner, better documented, consisted and thoroughly tested as they are now. There was just no spare time and mental energy to bring them there before, now there is and experimenting to get there was cheap.

Needless to say I no longer enjoy the job anymore and thinking of changing domain. I loved tinkering about implementation details, etc, but the job nowadays is more of qa and architectural design than writing or reviewing code.

austin-cheney2• 1 day ago

I am looking at the subtitle:

The future of software development will belong to those who can think clearly at scale, maintain durable mental models amid rapid change, and integrate machine-generated output into human-directed intent.

Wasn't this always the case? Maybe I just take this for granted because I am dumb Army guy and this is the only lens through which we dumb Army people see the world.

Whenever the subject of AI comes up in connection to programming it feels like the conversation always misses the human element. When you look at this only in terms of human behavior I am not seeing anything new with AI.

Maybe, its because I write in JavaScript and maybe its different in other areas of programming. In JavaScript it has always been a race to the bottom. The product is never the goal. The goal is always hiring and regarding code as a commodity that is designed to fail elegantly and frequently. So, when I look at AI writing code for developers I can't help but ask: What's different? Isn't that why Angular and React became popular, because they abstract away writing code?

kerblang• 1 day ago

Ever since the first programming language the goal was to make the work easier, although there are different kinds of "easy", and sometimes you end up worse off because tools don't live up to promises.

The human element is "What do I want?" You have ideas about how you need things to work. Some folks don't care much at all about how things work, just that they can shove a thing out the door and get paid with minimal effort. Sometimes their boss is completely in agreement. Sometimes things fall apart because nobody cared enough to bother, and sometimes even that doesn't matter, and everybody gets paid anyhow.

Sometimes you wish things mattered more, and sometimes they do.

skydhash4• 1 day ago

Some folks don't care much at all about how things work, just that they can shove a thing out the door and get paid with minimal effort. Sometimes their boss is completely in agreement

The issue is not the quality per se (I can write hacky things if that’s needed). The issue is when you become responsible for the shoddy things that were rushed and is now hacks on pile of hacks.

austin-cheney2• 1 day ago

Ever since the first programming language the goal was to make the work easier

The historical evidence disagrees. The point of software is automation and the point of automation is elimination of labor by any means. Nowhere in that is easier.

Clearly developers have forgotten what automation is because the quest for easier satisfies the narcissism of people who lack the ability to see otherwise.

skydhash4• 1 day ago

Whenever the subject of AI comes up in connection to programming it feels like the conversation always misses the human element. When you look at this only in terms of human behavior I am not seeing anything new with AI

You’re not wrong. I think that’s the confusion in LLM conversation. It seems that most people believe that programmers only think about code like it’s some kind of lego bricks we have to assemble. While the truth is that most projects is about building a sets of concepts that interacts in a specific way. The code is just the medium to do so, like letters helping to create words when writing.

I was reading the OpenBSD code (some investigation about a pen tablet) and the layers in abstraction was the following:

  xinput
  ws       (driverfor x11)
  --|ioctl syscall|---
  wsmouse  (wscons subsystem)
  hidms    (hid mouse) Some other things use the usb hid format
  ums      (usb mouse)
  uhidev   (usb hid device)
  usb      (root controller hub abstraction)
  xhci     (usb root controller under the hood, usb side
  pci_xhci (usb root controller, pci side)

You can stop at several point and not worry about what’s in the lower level of the abstraction tower, but those mechanism exists and have been built by someone. Imagine if that tower has been flattened out and all the code needed to coexist within the same module. It would be madness.

Programming was always about taking some lower order of things and rearranging it into meaningful concepts for some higher purposes. Whether it’s the DOM api, the jQuery suite of functions, the React model of components and reactive state, the goal is to create UI widgets for a page.

People (sometimes?) see the building blocks (dom api…) and the end result (figma sketch) but have no idea how the two connect.

1saadcodes• 1 day ago

I agree with this, but I'd add that good judgment comes from experience. Before you can evaluate whether AI-generated code makes sense, you need to have written enough code yourself to recognize the trade-offs and failure modes. AI is an incredible productivity multiplier, but it can also make it much easier to move quickly in the wrong direction without even knowing that you are moving in the wrong direction

foo12bar• 1 day ago

This article will apply for about 3 months until AI advances again and the assumptions made are no longer true.

You can't take a rapidly developing field and pretend progress is going to freeze at its current development level so you can decide how to handle it.

It's a coping mechanism to deal with rapid change by pretending change is going to stoo right here right now and you can get a handle on it.

skippyfish• 1 day ago

I always find it hilarious when these opinion pieces about the impacts of AI are AI-written (as is almost certainly the case here, a major trend in ACM and IEEE publications). Like, really? An LLM has a breadth of experience managing AI, and can recall it, and explain it to humans?

luciana1u• 1 day ago

we automated the easy part of programming and it turns out the easy part was the fun part

nasretdinov2• 1 day ago

Definitely not my experience. No matter the model, if I'm working on something important (and there is little reason on working on something not important) I do care about correctness and understandability. While LLMs are great for throwaway one-time code (although that's also debatable), they cannot compete with code written by a seasoned professional. No matter how many times I've tried delegating writing code to LLMs I've always regretted it in a few months' time, because it is more buggy and I don't really know what is happening there.

The future is using LLMs for what they are good for. What that is still being found out. I've had great experience with LLMs reviewing the code (matches with Primagean's ~50% accuracy at finding bugs, which is really good) and for explaining unfamiliar concepts to me.

I firmly believe that the code itself needs to be 100% organic, and if it's not and you're relying on LLMs to generate tons of code, you haven't built enough abstraction to make it unnecessary.

noodlescb• 1 day ago

After 18+ months of this, LLMs are incredible for getting rid of the work I hated most: Updating JIRA tickets, tedious little cleanup jobs, refactoring, etc. They are great at finding infosec issues.

They are also GREAT at writing code based on standards and patterns established by an actual human engineers. They are STILL trash at anything meaningfully complex from the ground up. I will go through hours of planning where I have to kick the hell out of its plans in ways that I don't think someone without a ton of real world experience could do. Even in the fancy new Fable models that remains true. They are not creative and any engineering worth doing requires creativity.

vorticalbox• 1 day ago

I have to kick the hell out of its plans in ways that I don't think someone without a ton of real world experience could do

I think that’s the real point the article’s making. Unless you already know the ropes, you can’t tell if a plan is actually any good. I use LLMs all the time for work, but only because I get the system well enough to spot the nonsense or catch when a plan duplicates something that already exists. They really do keep rewriting the same functions over and over in the code.

echelon4• 1 day ago

You're moving too slow.

Over the last four days I've few shotted a 1:1 clone (and improvement) of Fal, OpenRouter, and Replicate in Rust. It's going to be open source.

I've lined up $300k of monthly commitments for it that land at launch. Might apply to YC with it.

Moving "organic" is too slow for the world today.

ozim• 1 day ago

Should have get some AI for bait posts :D

overgard2• 1 day ago

Oh cool, you're remaking things that already exist. You know why you can few shot those things? Because they already exist.

nasretdinov2• 1 day ago

Depending on what you're working on, moving slowly and thoughtfully might be a feature. Just saying

sph2• 17 hours ago

Would you believe me if I told you you’re only the second biggest AI maximalist on this forum? Despite the extraordinary claims I keep reading from you. Gotta work harder at it mate.

overgard2• 1 day ago

One thing that I find frustrating/disturbing about LLM generated code is that wrong stuff doesn't usually look wrong, so you almost have to review it even closer than what you'd review from a person. Like in the past when a developer was being sloppy, usually you could kind of tell superficially, but with LLM code it's usually well documented and superficially well structured, all while doing batshit insane things. Like today I noticed some code that it had written was just silently returning on errors without logging a warning or returning an error code. It "worked" but it was a major foot-gun!

m3kw94• 1 day ago

double edge sword of LLM code generation, you cannot catch 100%, nor do you want to always ready every single word. Gotta develop a feel.

m3kw94• 1 day ago

I can generate LLM code and it will be very stable long term, but you must be QA minded and non-stop testing, ask and make sure it generate maintainable code, watch for code smell etc. Maybe it won't match a very seasoned dev, but LLM's generate sht code because the dev allows it at the review stage.

gwbas1c• 7 hours ago

Some things to consider:

1: The quality of code varies widely from model to model. In Visual Studio Copilot, I get so-so code from GPT, great code from Claude 4.x, lousy results from Claude 5.x

2: "Novel work" is harder to get from an LLM than when it's following an example. For example, I can get great Blazor / HTML / css from an LLM (and then spend time iterating making small adjustments,) but if I'm writing a complicated DB query or implementing a novel algorithm, it's best to do by hand.

3: But, in the case of a novel algorithm or query, I get great results saying "please write unit tests for XXX". That alone makes me develop code twice as fast!

atemerev• 1 day ago

Oh finally my ADHD will pay for itself! I waited for so long!

bystander2026• 1 day ago

I am tired of all these AI is so smart vs AI is not so smart. AI is a tool. It is like CNC machine tools or robotics in manufacturing.

How's about a test? Put all the smart AI researchers/developers onto an airplane that its software was entirely created by AI. Now tell that airplane to travel around the world with airborne refueling and land at an airport. When will this happen and how many of AI advocates will get on this autonomous airplane?

kernc• 1 day ago

The convergence is ongoing. We are Borg. You will be assimilated.

m3kw94• 1 day ago

Also, the need to move with speed is an exercise in self control so you don't cut corners and accept code without really look at it. There are so many times when I catch really blatant stuff that if not caught would be over engineering, wrong engineering, hacks, logic code copies without reuse etc etc.

holoduke• 1 day ago

Since rise of AI u haven't touched single line of code. Even though I know AI isn't good enough still in many areas, I cannot find the energy to invest in programming with writing code.

cratermoon2• 1 day ago

It also made it way orders of magnitude more expensive.

AI makes programming differently difficult

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