I asked Codex to write some unit tests for Redux today. At first glance it looked fine, and I continued on. I then went back to add a test by hand, and after looking more closely at the output there were like 50 wtf worthy things scattered in there. Sure they ran, but it was bad in all sorts of ways. And this was just writing something very basic.
This has been my experience almost every time I use AI: superficially it seems fine, once I go to extend the code I realize it's a disaster and I have to clean it up.
The problem with "code is cheap" is that, it's not. GENERATING code is now cheap (while the LLMs are subsidized by endless VC dollars, anyway), but the cost of owning that code is not. Every line of code is a liability, and generating thousands of lines a day is like running up a few thousand dollars of debt on a credit card thinking you're getting free stuff and then being surprised when it gets declined.
Hi, I'm the primary Redux maintainer. I'd love to see some examples of what got generated! (Doubt there's anything we could do to _influence_ this, but curious what happened here.)
FWIW we do have our docs on testing approaches here, and have recommended a more integrated-style approach to testing for a while:
The equivalent of "draw me a dog" -> not a masterpiece!? who would have thought? You need to come up with a testing methodology, write it down, and then ask the model to go through it. It likes to make assumptions on unspecified things, so you got to be careful.
More fundamentally I think testing is becoming the core component we need to think about. We should not vibe-check AI code, we should code-check it. Of course it will write the actual test code, but your main priority is to think about "how do I test this?"
You can only know the value of a code up to the level of its testing. You can't commit your eyes into the repo, so don't do "LGTM" vibe-testing of AI code, it's walking a motorcycle.
Generating code was always cheap. That’s part of the reason this tech has to be forced on teams. Similar to the move to cloud, it’s the kind of cost that’s only gonna show up later - faster than the cloud move, I think. Though, in some cases it will be the correct choice.
ATM I feel like LLM writing tests can be a bit dangerous at times, there are cases where it's fine there are cases where it's not. I don't really think I could articulate a systemised basis for identifying either case, but I know it when I see it I guess.
Like the the other day, I gave it a bunch of use cases to write tests for, the use cases were correct the code was not, it saw one of the tests broken so it sought to rewrite the test. You risking suboptimal results when an agent is dictating its own success criteria.
At one point I did try and use seperate Claude instances to write tests, then I'd get the other instance to write the implementation unaware of the tests. But it's a bit to much setup.
This is how you do things if you are new to this game.
Get two other, different, LLMs to thoroughly review the code. If you don’t have an automated way to do all of this, you will struggle and eventually put yourself out of a job.
If you do use this approach, you will get code that is better than what most software devs put out. And that gives you a good base to work with if you need to add polish to it.
I think if your job is to assemble a segment of a car based on a spec using provided tools and pre-trained processes, it makes sense if you worry that giant robot arms might be installed to replace you.
But if your job is to assemble a car in order to explore what modifications to make to the design, experiment with a single prototype, and determine how to program those robot arms, you’re probably not thinking about the risk of being automated.
I know a lot of counter arguments are a form of, “but AI is automating that second class of job!” But I just really haven’t seen that at all. What I have seen is a misclassification of the former as the latter.
A software engineer with an LLM is still infinitely more powerful than a commoner with an LLM. The engineer can debug, guide, change approaches, and give very specific instructions if they know what needs to be done.
The commoner can only hammer the prompt repeatedly with "this doesn't work can you fix it".
So yes, our jobs are changing rapidly, but this doesn't strike me as being obsolete any time soon.
My job is to make people who have money think I'm indispensable to achieving their goals. There's a good chance AI can fake this well enough to replace me. Faking it would be good enough in an economy with low levels of competition; everyone can judge for themselves if this is our economy or not.
I don’t think this is the issue “yet”. It’s that no matter what class you are, your CEO does not care. Mediocre AI work is enough to give them immense returns and an exit. He’s not looking out for the unfortunate bag holders. The world has always had tolerance for highly distributed crap. See Windows.
This is actually a really good description of the situation. But I will say, as someone that prided myself on being the second one you described, I am becoming very concerned about how much of my work was misclassified. It does feel like a lot of work I did in the second class is being automated where maybe previously it overinflated my ego.
You are describing tradition (deterministic?) automation before AI. With AI systems as general as today's SOTA LLMs, they'll happily take on the job regardless of the task falling into class I or class II.
Ask a robot arm "how should we improve our car design this year", it'll certainly get stuck. Ask an AI, it'll give you a real opinion that's at least on par with a human's opinion. If a company builds enough tooling to complete the "AI comes up with idea -> AI designs prototype -> AI robot physically builds the car -> AI robot test drives the car -> AI evaluates all prototypes and confirms next year's design" feedback loop, then theoretically this definitely can work.
This is why AI is seen as such a big deal - it's fundamentally different from all previous technologies. To an AI, there is no line that would distinguish class I from II.
> I know a lot of counter arguments are a form of, “but AI is automating that second class of job!”
Uh, it's not the issue. The issue is that there isn't that much demand for the second class of job. At least not yet. The first class of job is what feeds billions of families.
I see a lot of the same (well thought out) pushback on here whenever these kinds of blind hype articles pop up.
But my biggest objection to this "engineering is over" take is one that I don't see much. Maybe this is just my Big Tech glasses, but I feel like for a large, mature product, if you break down the time and effort required to bring a change to production, the actual writing of code is like... ten, maybe twenty percent of it?
Sure, you can bring "agents" to bear on other parts of the process to some degree or another. But their value to the design and specification process, or to live experiment, analysis, and iteration, is just dramatically less than in the coding process (which is already overstated). And that's without even getting into communication and coordination across the company, which is typically the real limiting factor, and in which heavy LLM usage almost exclusively makes things worse.
Takes like this seem to just have a completely different understanding of what "software development" even means than I do, and I'm not sure how to reconcile it.
To be clear, I think these tools absolutely have a place, and I use them where appropriate and often get value out of them. They're part of the field for good, no question. But this take that it's a replacement for engineering, rather than an engineering power tool, consistently feels like it's coming from a perspective that has never worked on supporting a real product with real users.
I'm not sure you're actually in disagreement with the author of this piece at all.
They didn't say that software engineering is over - they said:
> Software development, as it has been done for decades, is over.
You argue that writing code is 10-20% of the craft. That's the point they are making too! They're framing the rest of it as the "talking", which is now even more important than it was before thanks to the writing-the-code bit being so much cheaper.
Yeah in a lot of ways, my assertion is that @
“Code is cheap” actually means the opposite of what everyone thinks it does. Software Engineer is even more about the practices we’ve been developing over the past 20 or so years, not less
Like Linus’ observation still stands. Show me that the code you provided does exactly what you think it should. It’s easy to prompt a few lines into an LLM, it’s another thing to know exactly the way to safely and effectively change low level code.
Liz Fong-Jones told a story on LinkedIn about this at HoneyComb, she got called out for dropping a bad set of PR’s in a repo, because she didn’t really think about the way the change was presented.
> Takes like this seem to just have a completely different understanding of what "software development" even means than I do, and I'm not sure how to reconcile it.
You're absolutely right about coding being less than 20% of the overall effort. In my experience, 10% is closer to the median. This will get reconciled as companies apply LLMs and track the ROI. Over a single year the argument can be made that "We're still learning how to leverage it." Over multiple years the 100x increase in productivity claims will be busted.
We're still on the upslope of Gartner's hype cycle. I'm curious to see how rapidly we descend into the Trough of Disillusionment.
My recent experience demonstrates this. I had a couple weeks of happily cranking out new code and refactors at high speed with Claude’s help, then a week of what felt like total stagnation, and now I’m back to high velocity again.
What happened in the middle was I didn’t know what I wanted. I hadn’t worked out the right data model for the application yet, so I couldn’t tell Claude what to do. And if you tell it to go ahead and write more code at that point, very bad things will start to happen.
The book Software Engineering at Google makes a distinction between software engineering and programming. The main difference is that software engineering occurs over a longer time span than programming. In this sense, AI tools can make programming faster, but not necessarily software engineering.
Just because a bunch of people tell you the practice of performing the art form of producing software via handwriting code is over doesn't mean it's over. This form of hyperbole is intended to overwhelm your reason, get you to forget your own expertise, and trick you into engaging with the topic in a fearful manner (literally FOMO). Don't fall for this cheap stunt.
There will always be a niche for any form of expression. However technologies change practice. It is your responsibility to be able to solve problems that balance performance, cost, schedule, and quality. Use the right tool for the job.
> crystal clear software development plan and the exact know-how to implement it
This is simply not how expert programmers work. Programming is planning, and programming languages are surprisingly good planning tools. But, of course, becoming an expert is hard and requires not only some general aptitude but also substantial time, experience and effort.
My theory is that this is a source of diverging views on LLMs for programming: people who see programming languages as tools for thought compared to people who see programming languages as, exclusively, tools to make computers do stuff. It's no surprise that the former would see more value in programming qua programming, while the latter are happy to sweep code under the rug.
The fundamental problem, of course, is that anything worth doing in code is going to involve pinning down a massive amount of small details. Programming languages are formal systems with nice (well, somewhat nice) UX, and formal systems are great for, well, specifying details. Human text is not.
Then again, while there might be a lot of details, there are also a lot of applications where the details barely matter. So why not let a black box make all the little decisions?
The question boils down to where you want to spend more energy: developing and articulating a good conceptual model up-front, or debugging a messy system later on. And here, too, I've found programmers fall into two distinct camps, probably for the same reasons they differ in their views on LLMs.
In principle, LLM capabilities could be reasonably well-suited to the up-front thinking-oriented programming paradigm. But, in practice, none of the tools or approaches popular today—certainly none of the ones I'm familiar with—are oriented in that direction. We have a real tooling gap.
> My theory is that this is a source of diverging views on LLMs for programming: people who see programming languages as tools for thought compared to people who see programming languages as, exclusively, tools to make computers do stuff. It's no surprise that the former would see more value in programming qua programming, while the latter are happy to sweep code under the rug.
i'd postulate this: most people see llms as tools for thought. programmers also see llms as tools for programming. some programmers, right now, are getting very good at both, and are binding the two together.
The original phrase "talk is cheap" is generally used to mean "it's easy to say a whole lot of shit and that talk often has no real value." So this cleaver headline is telling me the code has even less value than the talk. That alone betrays a level of ignorance I would expect from the author's work. I go to read the article and it confirmed my suspicion.
I think you are hyper-focusing on the headline, which is just a joke. The underlying article does not indicate to me that the author is ignorant of code, and if you care to look, they seem to have a substantial body of public open source contributions that proves this quite conclusively.
The underlying point is just that while it was very cognitively expensive to back up a good design with good code back in 2000, it's much cheaper now. And therefore, making sure the design is good is the more important part. That's it really.
Yes, the original phrase has a specific meaning. But in another context, "talk" is more important than the code.
In software development, code is in a real sense less important than the understanding and models that developers carry around in their heads. The code is, to use an unflattering metaphor, a kind of excrement of the process. It means nothing without a human interpreter, even if it has operational value. The model is never part of the implementation, because software apart from human observers is a purely syntactic construct, at best (even there, I would argue it isn't even that, as syntax belongs to the mind/language).
> Software development, as it has been done for decades, is over.
I'm pretty sure the way I was doing things in 2005 was completely different compared to 2015. Same for 2015 and 2025. I'm not old enough to know how they were doing things in 1995, but I'm pretty sure there very different compared to 2005.
For sure, we are going through some big changes, but there is no "as it has been done for decades".
I don't think things have changed that much in the time I've been doing it (roughly 20 years). Tools have evolved and new things were added but the core workflow of a developer has more or less stayed the same.
Yeah, I remember being amazed at the immediate incremental compilation on save in Visual Age for Java many years ago. Today's neovim users have features that even the most advanced IDEs didn't have back then.
I think a lot of people in the industry forget just how much change has come from 30 years of incremental progress.
talk is even cheaper, still show me the code, people claim 10x productivity that translates to 10x of work done in a month, even with Opus 4.5 out since November 2025 I haven't seen signs of this. AI makes the level of complexity with modern systems bearable, it was getting pretty bad before and AI kinda saved us. A non-trivial React app is still a pain to write. Also creating a harness for a non-deterministic api that AI provides is also pain. At least we don't have to fight through typing errors or search through relevant examples before copying and pasting. AI is good at automating typing, the lack of reasoning and the knowledge cutoff still makes coding very tedious though.
Best example of this is Claude's own terminal program. Apparently renders react at 60fps and then translates it into ANSI chars that then diff the content of the terminal and do an overwrite...
All to basically mimic what curses can do very easily.
This "Code is cheap. Show me the talk." punchline gets overused as a bait these days. It is an alright article but that's a lot of words to tell us something we already know. There's nothing here that we don't already know. It's not just greedy companies riding the AI wave. Bloggers and influencers are also riding the AI wave. They know if you say anything positive or negative about AI with a catchy title it will trend on HN, Reddit, etc.
Also credit where credit is due. Origin of this punchline:
In January 2026, prototype code is cheap. Shitty production code is cheap. If that's all you need—which is sometimes the case—then go for it.
But actually good code, with a consistent global model for what is going on, still won't come from Opus 4.5 or a Markdown plan. It still comes from a human fighting entropy.
Getting eyes on the code still matters, whether it's plain old AI slop, or fancy new Opus 4.5 "premium slop." Opus is quite smart, and it does its best.
But I've tried seriously using a number of high-profile, vibe-coded projects in the last few weeks. And good grief what unbelievable piles of shit most of them are. I spend 5% of the time using the vibe-coded tool, and 95% of the time trying to uncorrupt my data. I spend plenty of time having Opus try to look at the source to figure out what went wrong in 200,000 lines of vibe-coded Go. And even Opus is like, "This never worked! It's broken! You see, there's a race condition in the daemonization code that causes the daemon to auto-kill itself!"
And at that point, I stop caring. If someone can't be bothered to even read the code Opus generates, I can't be bothered to debug their awful software.
> Ignoring outright bad code, in a world where functional code is so abundant that “good” and “bad” are indistinguishable, ultimately, what makes functional AI code slop or non-slop?
I'm sorry, but this is an indicator for me that the author hasn't had a critical eye for quality in some time. There is massive overlap between "bad" and "functional." More than ever. The barrier-to-entry to programming got irresponsibly low for a time there, and it's going to get worse. The toolchains are not in a good way. Windows and macOS are degrading both in performance and usability, LLVM still takes 90% of a compiler's CPU time in unoptimized builds, Notepad has AI (and crashes,) simple social (mobile) apps are >300 MB download/installs when eight years ago they were hovering around a tenth of that, a site like Reddit only works on hardware which is only "cheap" in the top 3 GDP nations in the world... The list goes on. Whatever we're doing, it is not scaling.
I'd think there'll be a dip in code quality (compared to human) initially due to "AI machinery" due to its immaturity. But over-time on a mass-scale - we are going to see an improvement in the quality of software artifacts.
It is easier to 'discipline' the top 5 AI agents in the planet - rather than try to get a million distributed devs ("artisans") to produce high quality results.
It's like in the clothing or manufacturing industry I think. Artisans were able to produce better individual results than the average industry machinery, at least initially. But overtime - industry machinery could match the average artisan or even beat the average, while decisively beating in scale, speed, energy efficiency and so on.
One issue is that tooling and internals have been optimized for individual people's tastes currently. Heterogeneous environments make the models spikier. As we shift to building more homogenized systems optimized around agent accessibility, I think we'll see significant improvements
Elegantly, agents finally give us an objective measure of what "good" code is. It's code that maximizes the likelihood that future agents will be able to successfully solve problems in this codebase. If code is "bad" it makes future problems harder.
Finally, someone articulates the middle better than I have:
> Thus, the extreme proponents of manic “agentic” vibe coding,[19] and the outright denouncers of LLMs, are both missing the forest for the trees. That there is a pragmatic middle path, where people who have the experience, expertise, competence, and the ability to articulate can use these tools to get the outcomes they desire with the right sets of trade-offs.
LLMs are tools. They are not gods to replace man, nor are they exclusively means of harm. It is entirely possible to denounce the blatant attempt of rent extraction in the form of OpenAI, Google Gemini, Microsoft CoPilot, Anthropic, and others, while still running Qwen and Ministral and their like on local hardware. You can, in fact, have it “both ways”.
As fun as it is to poke at cloud services to see their new features and advancements, I (in IT terms) personally could never recommend them in any serious enterprise context for the very reason that they’re fundamentally insecure; you will never, ever have full E2EE with these services because it would nullify their ability to evolve, improve, monetize, and exploit.
That said? I can truly be a one dinosaur army in an enterprise now, as a generalist with a modest Mac Mini (or Studio) and a local LLM to fill in edge cases as needed. I can query these local tools for questions on database schemas or build a one-off API integration for me, so I can focus on the substance of work in safeguarding and accelerating the enterprise. I don’t need fleets of specialists unless I’m running a huge conglomerate or have specific needs - and even then, it’s going to be cheaper to retain one or two seniors to direct the larger army of generalists when needed. The landscape has changed, and it’s why I target leadership and management roles accordingly with my sales pitch (“One senior generalist can do the work of three mid-level specialists”).
Don’t get me wrong, I still have immense grievances regarding theft of work, reductions in force, rent extraction, and the seeming attempt at destroying local general compute, but local LLMs as a tool have been in my kit for years, and that’s not going away.
Historically, it would take a reasonably long period of consistent effort and many iterations of refinement for a good developer to produce 10,000 lines of quality code that not only delivered meaningful results, but was easily readable and maintainable. While the number of lines of code is not a measure of code quality—it is often the inverse—a codebase with good quality 10,000 lines of code indicated significant time, effort, focus, patience, expertise, and often, skills like project management that went into it. Human traits.
Now, LLMs can not only one-shot generate that in seconds,
Evidence please. Ascribing many qualities to LLM code that I haven't (personally) seen at that scale. I think if you want to get an 'easily readable and maintainable' codebase of 10k lines with an LLM you need somebody to review its contributions very closely, and it probably isn't going to be generated with a 1 shot prompt.
Okay I was writing a comment to simon (and I have elaborated some there but I wanted this to be something catchy to show how I feel and something people might discuss with too)
Both Code and talk are cheap. Show me the trust. Show me how I can trust you. Show me your authenticity. Show me your passion.
Code used to be the sign of authenticity. This is whats changing. You can no longer guarantee that large amounts of code let's say are now authentic, something which previously used to be the case (for the most part)
I have been shouting into the void many times about it but Trust seems to be the most important factor.
Essentially, I am speaking it from a consumer perspective but suppose that you write AI generated code and deploy it. Suppose you talked to AI or around it. Now I can do the same too and create a project sometimes (mostly?) more customizable to my needs for free/very-cheap.
So you have to justify why you are charging me. I do feel like that's only possible if there is something additional added to value. Trust, I trust the decision that you make and personally I trust people/decisions who feel like they take me or my ideas into account. So, essentially not ripping me off while actively helping. I don't know how to explain this but the most thing which I hate is the feeling of getting ripped off. So justifiable sustainable business who is open/transparent about the whole deal and what he gets and I get just gets my respect and my trust and quite frankly, I am not seeing many people do that but hopefully this changes.
I am curious now what you guys of HN think about this & what trust means to you in this (new?) ever-changing world.
Like y'know I feel like everything changes all the time but at the same time nothing changes at the same time too. We are still humans & we will always be humans & we are driven by our human instincts. Perhaps the community I envision is a more tight knit community online not complete mega-sellers.
My perspective is that AI is a multiplier if existing skill (both positive and negative aspects). A bad developer can now produce bad code at 10x the rate and a good developer can produce good code at 10x the rate.
There is a net positive gain on the automated testing side of things but I think a bad developer, even with AI will not be able to out-compete a good 10x developer without AI. The costs of incorrect abstractions is just too high and LLMs don't really help avoid those.
You have to ask the right questions. It's a bit like in Hitchhiker's Guide to the Galaxy... Where a super-intelligent computer took millions of years to calculate the meaning of life as the number 42. The wrong question will always waste computation.
> because one is hooked on and dependent on the genie, the natural circumstances that otherwise would allow for foundational and fundamental skills and understanding to develop, never arise, to the point of cognitive decline.
After using AI to code, I came to the same conclusion myself. Interns and juniors are fully cooked:
- Companies will replace them with AI, telling seniors to use AI instead of juniors
- As a junior, AI is a click away, so why would you spend sleepless nights painstakingly acquiring those fundamentals?
Their only hope is to use AI to accelerate their own _learning_, not their performance. Performance will come after the learning phase.
If you're young, use AI as a personal TA, don't use it to write the code for you.
as someone who is sort of a medior programmer it is very hard to balance, trying to keep up with the advancements in AI while not shooting myself in the foot by robbing myself of learning experiences
> Code was always a means to an end. Unlike poetry or prose, end users don’t read or care about code.
Yes and no. Code is not art, but software is art.
What is art, then? Not something that's "beautiful", as beauty is of course mostly subjective. Not even something that works well.
I think art is a thing that was made with great care.
It doesn't matter if some piece of software was vibe-coded in part or in full, if it was edited, tested, retried enough times for its maker to consider it "perfect". Trash is something that's done in a careless way.
If you truly love and use what you made, it's likely someone else will. If not, well... why would anyone?
4. To learn (to get better by absorbing how the pros do it).
5. To verify and improve it (code review, pair programming).
6. To grade it (because a student wrote it).
7. To enjoy its beauty.
These are all I can think of right now, and they are ordered from most common to most rare case.
Personally, I have certainly read and re-read SICP code to enjoy its beauty (7), perhaps mixed in with a desire to learn (4) how to write equally beautiful code.
The best definition of art I've read is the one from "What is Art?" by Tolstoy. I haven't read it myself, but came across it in a Van Neistat video recently.
Tolstoy argued that art is essentially the transmission of feeling from the artist to the audience. He claimed that when an artist experiences an emotion and then, through their work, evokes that same emotion in others, that is art.
Code, talk, who cares. Show me the product. If it works and is useful I will incorporate it into my life. Ultimately no one cares how the sausage is made.
Uhh I kinda care? And some people do too? People have given software social permission so far. I have a feeling that it’s about to change. Engineers are thinking too narrowly about the effects of LLM assisted coding. They only see the shiny bits that benefit them.
I keep on wondering how much of the AI embrace is marketing driven. Yes, it can produce value and cut corners. But it seems like self driving by 2016 Musk prediction. Which never happened. With IPO/Stock valuations closely tied to hype, I wonder if we are all witnessing a giant bubble in the making
How much of this is mass financial engineering than real value. Reading a lot of nudges how everyone should have Google or other AI stock in their portfolio/retirement accounts
There's nothing to wonder about. It's obviously marketing.
The whole narrative of "inevitability" is the stock behavior of tech companies who want to push a product onto the public. Why fight the inevitable? All you can do is accept and adapt.
And given how many companies ask vendors whether their product "has AI" without having the slightest inkling of what that even means or whether it even makes sense, as if it were some kind of magical fairy dust - yeah, the stench of hype is thick enough you could cut it with a knife.
Of course, that doesn't mean it lacks all utility.
Maybe we haven't seen much economic value or productivity increase given all the AI hypes. I don't think we can deny the fact that programming has been through a paradigm shift where humans aren't the only ones writing code and the amount of code written by humans I would say is decreasing.
What you are saying may have made sense at the start of 2025 where people were still using github copilot tab auto completes(atleast I did) and was just toying with things like cursor, but unsure.
Things have changed drastically now, engineers with these tools(like claude code) have become unstoppable.
Atleast for me, I have been able to contribute to the codebases i was unfamiliar with, even with different tech stacks. No, I am not talking about generating ai slop, but I have been enabled to write principal engineer level code unlike before.
So i don't agree with the above statement, it's actually generating real value and I have become valuable because of the tools available to me.
I realize many are disappointed (especially by technical churn, star-based-development JS projects on github without technical rigour). I don't trust any claim on the open web if I don't know the technical background of the person making it.
However I think - Nadh, ronacher, the redis bro - these are people who can be trusted. I find Nadh's article (OP) quite balanced.
>> Remember the old adage, “programming is 90% thinking and 10% typing”? It is now, for real.
> Proceeds to write literal books of markdown to get something meaningful
>> It requires no special training, no new language or framework to learn, and has practically no entry barriers—just good old critical thinking and foundational human skills, and competence to run the machinery.
> Wrote a paragraph about how it is important to have serious experience to understand the generated code prior to that
>> For the first time ever, good talk is exponentially more valuable than good code. The ramifications of this are significant and disruptive. This time, it is different.
> This time is different bro I swear, just one more model, just one more scale-up, just one more trillion parameters, bro we’re basically at AGI
Completely disagree that "software development, as it has been done for decades, is over".
AI is a useful tool, agreed - but it will always be reliant upon humans writing code.
Let's take a very simple example to prove my point. Let's say that everybody is now using AI to write code, and someone develops a new programming language with it. Cool! We have a new language now.
What we don't have, however, are any examples of how that programming language is used. Nothing that the AI can learn from.
How well do you think AI is going to handle being able to code in this new language which doesn't appear at all in its training data?
> One can no longer know whether such a repository was “vibe” coded by a non-technical person who has never written a single line of code, or an experienced developer, who may or may not have used LLM assistance
I would like articles like this to have a quick "who" and "what experience" is talking. I can usually tell the conclusions based on experience/skill level regardless, but it would be nice.
Also, that projects page on his website is atrocious; hate to be "that guy" but I don't trust the author's insight since "personal projects" seems to include a lot more than just his work; the first several PRs I looked at where all vibed.
I'm not interested in re-implementations of the same wheel over and over again telling me and people who know how to write real software (have been doing it since I was 12) that we are becoming unnecessary bc you can bully an extremely complex machine built on a base theory of heuristics abstracted out endlessly (perceptually) to re-invent the same specs in slightly different flavors.
> 100% human written, including emdashes. Sigh.
If you can't write without emdashes, maybe you spend too much time with LLMs and not enough time reading and learning on your own. Also people can lie on the Internet, they do it all the time, and if not then I'm doing it right now.
Ok imho this _blog’s_ words looks like stitching of some fancy words. Is this a thing for rich execs to write like this? Doesn't even convey the message easily.
Talk is never cheap. Communicating your thoughts to people without the exact same kind of expertise as you is the most important skill.
This quote is from Torvalds, and I'm quite sure that if he weren't able to write eloquent English no one would know Linux today.
Code is important when it's the best medium to express the essence of your thoughts. Just like a composer cannot express the music in his head with English words.
I don't think Linus is a people person. This is something which he talks about himself in the famous ted-ed video.
I just re-watched the video (currently halfway) & I feel like the point of Linux is something which you are forgetting but it was never intended to grow so much and Linux himself in the video when asked says that he never had a moment where he went like oh this went big.
In fact he talks about when the project was little. On how he had gratitude when the project had 10 people maybe 100 people working on it and then things only grow over a very large time frame (more than 25-30years? maybe now 35 just searched 34)
He talks about how he got other people's idea which he couldn't have thought of things themselves and when he first created the project he just wanted to show off to the world to look at what I did (and he did it mainly for both the end result of the project and programming itself too) and then he got introduced to open source (free software) by his friend and he just decided to have it open source.
My point is it was neither the code nor the talk. Linus is the best person to maintain Linux, why? Because he has been passionate over it for 25 years. I feel like Linux would be just as interested in talking about the code and any improvements now with maybe the same vigour as 34 years ago. He loves his creation & we love Linux too :)
Another small point I wish to add is that if talk was the only thing, then you are missing the point because Linux was created because hurd was getting delayed (so all talks no code)
Linux himself says that if the hurd kernel would've been released earlier, Linux wouldn't have been created.
So all talk no code Hurd project (which from what I hear right now is still a bit limbo as now everyone [rightfully?] uses linux) is what led to creation of linux project.
Everyone who hasn't watched Linus's ted ed should definitely watch it.
If you have a solid test environment that would allow for an agent to check if it is right or wrong, I encourage you to do the experiment.
Put the agent on the wheel and observe it as it tries ruthlessly to pass the test. These days, likely it will manage to pass the tests after 3-5 loops, which I find fascinating.
Close the loop, and try an LLM. You will be surprised.
Feels like this website is yelling at me with its massive text size. Had to drop down to -50% to get it readable.
Classical indicators of good software are still very relevant and valid!
Building something substantial and material (ie not an api wrapper+gui, to-do list) that is undeniably well made, while being faster and easier than it used to be, still takes a _lot_ of work. Even though you don't have to write a line of code, it moves so fast that you are now spending 3.5-4 days of your work week reading code, using the project, running benchmarks and experimental test lanes, reviewing specs and plans, drafting specs, defining features and tests.
The level of granularity needed to get earnestly good results is more than most people are used to. It's directly centered at the intersection between spec heavy engineering work and writing requirements for a large, high quality offshore dev team that is endearingly literal in how they interpret instructions. Depending on the work, I've found that I average around one 'task' per 22-35 lines of code.
You'll discover a new sense of profound respect for the better PMs, QA Leads, Eng Directors you have worked with. Months of progress happen each week. You'll know you're doing it right when you ask an Agent to evaluate the work since last week and it assumes it is reviewing the output of a medium sized business and offers to make Jira tickets.
AI was never the problem we have been having a downgrade in software in general AI just amplifies how badly you can build software. The real problem is people who just dont care about the craft just pushing out human slop, whether it be because the business goes “we can come back to that dont worry” or what have you. At least with AI me coming back to something is right here and right now, not never or when it causes a production grade issue.
It might be a mistake to think in terms of production costs.
The real "cost" of software is reliance: what risk do your API clients or customers take in relying on you? This is just as true for free-as-in-beer software as for SaaS with enterprise SLA's.
In software and in professions, providers have some combination of method and qualifications or authority which justifies reliance by their clients. Both education and software have reduced the reliance on naked authority, but a good track record remains the gold standard.
So providers (individuals and companies) have to ask how much of their reputation do they want to risk on any new method (AI, agile, ...)? Initially, it's always a promising boost in productivity. But then...
So the real question is what "Show me" means - for a quick meet, an enterprise sale, an enduring human-scale consumer dependence...
So, prediction: AI companies and people that can "show me" will be the winners.
(Unfortunately, we've also seen competitive advantage accrue to dystopian hiding of truth and risk, which would have the same transaction-positive effect but shift and defer the burden of risk. Let's hope...)
I hate this trend of using adjectives to describe systems.
Fast
Secure
Sandboxed
Minimal
Reliable
Robust
Production grade
AI ready
Let's you _____
Enables you to _____
But somewhat I agree, code is essentially free, you can shit out infinite amounts of code. Unless it's good, then show the code instead.
If your code is shit, show the program.
If your program is shit, your code is worse, but you still pursing an interesting idea (in your eyes), show the prompt instead of the slop generated. Or even better communicate an elaborate version of the prompt.
>One can no longer know whether such a repository was “vibe”
I for one am quite happy to outsource this kind of simply memorisation to a machine. Maybe it's the thin end of the slippery slope? It doesn't FEEL like it is but...
premise is wrong. have seen a number of claude/codex disasters that never make it to production with clients, yet consumed an enormous amount of human time and bandwidth.
expertise and effort is and will continue to be for the forseeable future essential.
> The real concern is for generations of learners who are being robbed of the opportunity to acquire the expertise to objectively discern what is slop and what is not.
How do new developers build the skills that seniors generated through time? I see my seniors having higher success in vibe-coding than me. How can I short-circuit the time they put through for myself?
I think that's always been true. The ideas and reasoning process matter. So does the end product. If you produced it with an LLM and it sucks, it still sucks.
for a group of people as smart as developers, it sure took us long enough to realize billionaires were liquidating our code integrity to become trillionaires
overgard|1 month ago
This has been my experience almost every time I use AI: superficially it seems fine, once I go to extend the code I realize it's a disaster and I have to clean it up.
The problem with "code is cheap" is that, it's not. GENERATING code is now cheap (while the LLMs are subsidized by endless VC dollars, anyway), but the cost of owning that code is not. Every line of code is a liability, and generating thousands of lines a day is like running up a few thousand dollars of debt on a credit card thinking you're getting free stuff and then being surprised when it gets declined.
acedTrex|1 month ago
acemarke|1 month ago
FWIW we do have our docs on testing approaches here, and have recommended a more integrated-style approach to testing for a while:
- https://redux.js.org/usage/writing-tests
visarga|1 month ago
The equivalent of "draw me a dog" -> not a masterpiece!? who would have thought? You need to come up with a testing methodology, write it down, and then ask the model to go through it. It likes to make assumptions on unspecified things, so you got to be careful.
More fundamentally I think testing is becoming the core component we need to think about. We should not vibe-check AI code, we should code-check it. Of course it will write the actual test code, but your main priority is to think about "how do I test this?"
You can only know the value of a code up to the level of its testing. You can't commit your eyes into the repo, so don't do "LGTM" vibe-testing of AI code, it's walking a motorcycle.
sjsizjhaha|1 month ago
akst|1 month ago
Like the the other day, I gave it a bunch of use cases to write tests for, the use cases were correct the code was not, it saw one of the tests broken so it sought to rewrite the test. You risking suboptimal results when an agent is dictating its own success criteria.
At one point I did try and use seperate Claude instances to write tests, then I'd get the other instance to write the implementation unaware of the tests. But it's a bit to much setup.
cheema33|1 month ago
Get two other, different, LLMs to thoroughly review the code. If you don’t have an automated way to do all of this, you will struggle and eventually put yourself out of a job.
If you do use this approach, you will get code that is better than what most software devs put out. And that gives you a good base to work with if you need to add polish to it.
zamalek|1 month ago
hahahahhaah|1 month ago
jjimmy2k|29 days ago
pmarreck|1 month ago
Waterluvian|1 month ago
But if your job is to assemble a car in order to explore what modifications to make to the design, experiment with a single prototype, and determine how to program those robot arms, you’re probably not thinking about the risk of being automated.
I know a lot of counter arguments are a form of, “but AI is automating that second class of job!” But I just really haven’t seen that at all. What I have seen is a misclassification of the former as the latter.
enlyth|1 month ago
The commoner can only hammer the prompt repeatedly with "this doesn't work can you fix it".
So yes, our jobs are changing rapidly, but this doesn't strike me as being obsolete any time soon.
Buttons840|1 month ago
figassis|1 month ago
HorizonXP|1 month ago
crazylogger|1 month ago
Ask a robot arm "how should we improve our car design this year", it'll certainly get stuck. Ask an AI, it'll give you a real opinion that's at least on par with a human's opinion. If a company builds enough tooling to complete the "AI comes up with idea -> AI designs prototype -> AI robot physically builds the car -> AI robot test drives the car -> AI evaluates all prototypes and confirms next year's design" feedback loop, then theoretically this definitely can work.
This is why AI is seen as such a big deal - it's fundamentally different from all previous technologies. To an AI, there is no line that would distinguish class I from II.
mips_avatar|1 month ago
raincole|1 month ago
Uh, it's not the issue. The issue is that there isn't that much demand for the second class of job. At least not yet. The first class of job is what feeds billions of families.
Yeah, I'm aware of the lump of labour fallacy.
gipp|1 month ago
But my biggest objection to this "engineering is over" take is one that I don't see much. Maybe this is just my Big Tech glasses, but I feel like for a large, mature product, if you break down the time and effort required to bring a change to production, the actual writing of code is like... ten, maybe twenty percent of it?
Sure, you can bring "agents" to bear on other parts of the process to some degree or another. But their value to the design and specification process, or to live experiment, analysis, and iteration, is just dramatically less than in the coding process (which is already overstated). And that's without even getting into communication and coordination across the company, which is typically the real limiting factor, and in which heavy LLM usage almost exclusively makes things worse.
Takes like this seem to just have a completely different understanding of what "software development" even means than I do, and I'm not sure how to reconcile it.
To be clear, I think these tools absolutely have a place, and I use them where appropriate and often get value out of them. They're part of the field for good, no question. But this take that it's a replacement for engineering, rather than an engineering power tool, consistently feels like it's coming from a perspective that has never worked on supporting a real product with real users.
simonw|1 month ago
They didn't say that software engineering is over - they said:
> Software development, as it has been done for decades, is over.
You argue that writing code is 10-20% of the craft. That's the point they are making too! They're framing the rest of it as the "talking", which is now even more important than it was before thanks to the writing-the-code bit being so much cheaper.
techblueberry|1 month ago
Like Linus’ observation still stands. Show me that the code you provided does exactly what you think it should. It’s easy to prompt a few lines into an LLM, it’s another thing to know exactly the way to safely and effectively change low level code.
Liz Fong-Jones told a story on LinkedIn about this at HoneyComb, she got called out for dropping a bad set of PR’s in a repo, because she didn’t really think about the way the change was presented.
patrickmay|1 month ago
You're absolutely right about coding being less than 20% of the overall effort. In my experience, 10% is closer to the median. This will get reconciled as companies apply LLMs and track the ROI. Over a single year the argument can be made that "We're still learning how to leverage it." Over multiple years the 100x increase in productivity claims will be busted.
We're still on the upslope of Gartner's hype cycle. I'm curious to see how rapidly we descend into the Trough of Disillusionment.
wrs|1 month ago
What happened in the middle was I didn’t know what I wanted. I hadn’t worked out the right data model for the application yet, so I couldn’t tell Claude what to do. And if you tell it to go ahead and write more code at that point, very bad things will start to happen.
mehagar|1 month ago
unknown|1 month ago
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jatins|1 month ago
mupuff1234|1 month ago
jaredcwhite|1 month ago
doug_durham|1 month ago
tikhonj|1 month ago
This is simply not how expert programmers work. Programming is planning, and programming languages are surprisingly good planning tools. But, of course, becoming an expert is hard and requires not only some general aptitude but also substantial time, experience and effort.
My theory is that this is a source of diverging views on LLMs for programming: people who see programming languages as tools for thought compared to people who see programming languages as, exclusively, tools to make computers do stuff. It's no surprise that the former would see more value in programming qua programming, while the latter are happy to sweep code under the rug.
The fundamental problem, of course, is that anything worth doing in code is going to involve pinning down a massive amount of small details. Programming languages are formal systems with nice (well, somewhat nice) UX, and formal systems are great for, well, specifying details. Human text is not.
Then again, while there might be a lot of details, there are also a lot of applications where the details barely matter. So why not let a black box make all the little decisions?
The question boils down to where you want to spend more energy: developing and articulating a good conceptual model up-front, or debugging a messy system later on. And here, too, I've found programmers fall into two distinct camps, probably for the same reasons they differ in their views on LLMs.
In principle, LLM capabilities could be reasonably well-suited to the up-front thinking-oriented programming paradigm. But, in practice, none of the tools or approaches popular today—certainly none of the ones I'm familiar with—are oriented in that direction. We have a real tooling gap.
rrook|1 month ago
i'd postulate this: most people see llms as tools for thought. programmers also see llms as tools for programming. some programmers, right now, are getting very good at both, and are binding the two together.
rewilder12|1 month ago
quadrifoliate|1 month ago
The underlying point is just that while it was very cognitively expensive to back up a good design with good code back in 2000, it's much cheaper now. And therefore, making sure the design is good is the more important part. That's it really.
joenot443|1 month ago
lo_zamoyski|1 month ago
In software development, code is in a real sense less important than the understanding and models that developers carry around in their heads. The code is, to use an unflattering metaphor, a kind of excrement of the process. It means nothing without a human interpreter, even if it has operational value. The model is never part of the implementation, because software apart from human observers is a purely syntactic construct, at best (even there, I would argue it isn't even that, as syntax belongs to the mind/language).
This has consequences for LLM use.
xnorswap|1 month ago
vb-8448|1 month ago
I'm pretty sure the way I was doing things in 2005 was completely different compared to 2015. Same for 2015 and 2025. I'm not old enough to know how they were doing things in 1995, but I'm pretty sure there very different compared to 2005.
For sure, we are going through some big changes, but there is no "as it has been done for decades".
awesan|1 month ago
_ea1k|1 month ago
I think a lot of people in the industry forget just how much change has come from 30 years of incremental progress.
bryanlarsen|1 month ago
ojr|1 month ago
program_whiz|1 month ago
All to basically mimic what curses can do very easily.
ctrlmeta|1 month ago
Also credit where credit is due. Origin of this punchline:
https://nitter.net/jason_young1231/status/193518070341689789...
https://programmerhumor.io/ai-memes/code-is-cheap-show-me-th...
ekidd|1 month ago
But actually good code, with a consistent global model for what is going on, still won't come from Opus 4.5 or a Markdown plan. It still comes from a human fighting entropy.
Getting eyes on the code still matters, whether it's plain old AI slop, or fancy new Opus 4.5 "premium slop." Opus is quite smart, and it does its best.
But I've tried seriously using a number of high-profile, vibe-coded projects in the last few weeks. And good grief what unbelievable piles of shit most of them are. I spend 5% of the time using the vibe-coded tool, and 95% of the time trying to uncorrupt my data. I spend plenty of time having Opus try to look at the source to figure out what went wrong in 200,000 lines of vibe-coded Go. And even Opus is like, "This never worked! It's broken! You see, there's a race condition in the daemonization code that causes the daemon to auto-kill itself!"
And at that point, I stop caring. If someone can't be bothered to even read the code Opus generates, I can't be bothered to debug their awful software.
leecommamichael|1 month ago
I'm sorry, but this is an indicator for me that the author hasn't had a critical eye for quality in some time. There is massive overlap between "bad" and "functional." More than ever. The barrier-to-entry to programming got irresponsibly low for a time there, and it's going to get worse. The toolchains are not in a good way. Windows and macOS are degrading both in performance and usability, LLVM still takes 90% of a compiler's CPU time in unoptimized builds, Notepad has AI (and crashes,) simple social (mobile) apps are >300 MB download/installs when eight years ago they were hovering around a tenth of that, a site like Reddit only works on hardware which is only "cheap" in the top 3 GDP nations in the world... The list goes on. Whatever we're doing, it is not scaling.
atomicnature|1 month ago
I'd think there'll be a dip in code quality (compared to human) initially due to "AI machinery" due to its immaturity. But over-time on a mass-scale - we are going to see an improvement in the quality of software artifacts.
It is easier to 'discipline' the top 5 AI agents in the planet - rather than try to get a million distributed devs ("artisans") to produce high quality results.
It's like in the clothing or manufacturing industry I think. Artisans were able to produce better individual results than the average industry machinery, at least initially. But overtime - industry machinery could match the average artisan or even beat the average, while decisively beating in scale, speed, energy efficiency and so on.
CuriouslyC|1 month ago
Elegantly, agents finally give us an objective measure of what "good" code is. It's code that maximizes the likelihood that future agents will be able to successfully solve problems in this codebase. If code is "bad" it makes future problems harder.
stego-tech|1 month ago
> Thus, the extreme proponents of manic “agentic” vibe coding,[19] and the outright denouncers of LLMs, are both missing the forest for the trees. That there is a pragmatic middle path, where people who have the experience, expertise, competence, and the ability to articulate can use these tools to get the outcomes they desire with the right sets of trade-offs.
LLMs are tools. They are not gods to replace man, nor are they exclusively means of harm. It is entirely possible to denounce the blatant attempt of rent extraction in the form of OpenAI, Google Gemini, Microsoft CoPilot, Anthropic, and others, while still running Qwen and Ministral and their like on local hardware. You can, in fact, have it “both ways”.
As fun as it is to poke at cloud services to see their new features and advancements, I (in IT terms) personally could never recommend them in any serious enterprise context for the very reason that they’re fundamentally insecure; you will never, ever have full E2EE with these services because it would nullify their ability to evolve, improve, monetize, and exploit.
That said? I can truly be a one dinosaur army in an enterprise now, as a generalist with a modest Mac Mini (or Studio) and a local LLM to fill in edge cases as needed. I can query these local tools for questions on database schemas or build a one-off API integration for me, so I can focus on the substance of work in safeguarding and accelerating the enterprise. I don’t need fleets of specialists unless I’m running a huge conglomerate or have specific needs - and even then, it’s going to be cheaper to retain one or two seniors to direct the larger army of generalists when needed. The landscape has changed, and it’s why I target leadership and management roles accordingly with my sales pitch (“One senior generalist can do the work of three mid-level specialists”).
Don’t get me wrong, I still have immense grievances regarding theft of work, reductions in force, rent extraction, and the seeming attempt at destroying local general compute, but local LLMs as a tool have been in my kit for years, and that’s not going away.
z0r|1 month ago
sjsizjhaha|1 month ago
Imustaskforhelp|1 month ago
Both Code and talk are cheap. Show me the trust. Show me how I can trust you. Show me your authenticity. Show me your passion.
Code used to be the sign of authenticity. This is whats changing. You can no longer guarantee that large amounts of code let's say are now authentic, something which previously used to be the case (for the most part)
I have been shouting into the void many times about it but Trust seems to be the most important factor.
Essentially, I am speaking it from a consumer perspective but suppose that you write AI generated code and deploy it. Suppose you talked to AI or around it. Now I can do the same too and create a project sometimes (mostly?) more customizable to my needs for free/very-cheap.
So you have to justify why you are charging me. I do feel like that's only possible if there is something additional added to value. Trust, I trust the decision that you make and personally I trust people/decisions who feel like they take me or my ideas into account. So, essentially not ripping me off while actively helping. I don't know how to explain this but the most thing which I hate is the feeling of getting ripped off. So justifiable sustainable business who is open/transparent about the whole deal and what he gets and I get just gets my respect and my trust and quite frankly, I am not seeing many people do that but hopefully this changes.
I am curious now what you guys of HN think about this & what trust means to you in this (new?) ever-changing world.
Like y'know I feel like everything changes all the time but at the same time nothing changes at the same time too. We are still humans & we will always be humans & we are driven by our human instincts. Perhaps the community I envision is a more tight knit community online not complete mega-sellers.
Thoughts?
unknown|1 month ago
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jongjong|1 month ago
There is a net positive gain on the automated testing side of things but I think a bad developer, even with AI will not be able to out-compete a good 10x developer without AI. The costs of incorrect abstractions is just too high and LLMs don't really help avoid those.
You have to ask the right questions. It's a bit like in Hitchhiker's Guide to the Galaxy... Where a super-intelligent computer took millions of years to calculate the meaning of life as the number 42. The wrong question will always waste computation.
optymizer|1 month ago
After using AI to code, I came to the same conclusion myself. Interns and juniors are fully cooked:
- Companies will replace them with AI, telling seniors to use AI instead of juniors
- As a junior, AI is a click away, so why would you spend sleepless nights painstakingly acquiring those fundamentals?
Their only hope is to use AI to accelerate their own _learning_, not their performance. Performance will come after the learning phase.
If you're young, use AI as a personal TA, don't use it to write the code for you.
furyofantares|1 month ago
polytely|1 month ago
bambax|1 month ago
Yes and no. Code is not art, but software is art.
What is art, then? Not something that's "beautiful", as beauty is of course mostly subjective. Not even something that works well.
I think art is a thing that was made with great care.
It doesn't matter if some piece of software was vibe-coded in part or in full, if it was edited, tested, retried enough times for its maker to consider it "perfect". Trash is something that's done in a careless way.
If you truly love and use what you made, it's likely someone else will. If not, well... why would anyone?
jll29|1 month ago
1. To maintain it (to refactor or extend it).
2. To test it.
3. To debug it (to detect and fix flaws in it).
4. To learn (to get better by absorbing how the pros do it).
5. To verify and improve it (code review, pair programming).
6. To grade it (because a student wrote it).
7. To enjoy its beauty.
These are all I can think of right now, and they are ordered from most common to most rare case.
Personally, I have certainly read and re-read SICP code to enjoy its beauty (7), perhaps mixed in with a desire to learn (4) how to write equally beautiful code.
chrisvalleybay|1 month ago
Tolstoy argued that art is essentially the transmission of feeling from the artist to the audience. He claimed that when an artist experiences an emotion and then, through their work, evokes that same emotion in others, that is art.
jdjeeee|1 month ago
pton_xd|1 month ago
habinero|1 month ago
ares623|1 month ago
lifetimerubyist|1 month ago
Yeah...now that prompt injection is a fact of life and basically unsolvable - we can't really afford this luxury anymore.
negamax|1 month ago
How much of this is mass financial engineering than real value. Reading a lot of nudges how everyone should have Google or other AI stock in their portfolio/retirement accounts
lo_zamoyski|1 month ago
The whole narrative of "inevitability" is the stock behavior of tech companies who want to push a product onto the public. Why fight the inevitable? All you can do is accept and adapt.
And given how many companies ask vendors whether their product "has AI" without having the slightest inkling of what that even means or whether it even makes sense, as if it were some kind of magical fairy dust - yeah, the stench of hype is thick enough you could cut it with a knife.
Of course, that doesn't mean it lacks all utility.
Cthulhu_|1 month ago
xiaoape|1 month ago
funnyfoobar|1 month ago
Things have changed drastically now, engineers with these tools(like claude code) have become unstoppable.
Atleast for me, I have been able to contribute to the codebases i was unfamiliar with, even with different tech stacks. No, I am not talking about generating ai slop, but I have been enabled to write principal engineer level code unlike before.
So i don't agree with the above statement, it's actually generating real value and I have become valuable because of the tools available to me.
dbtablesorrows|1 month ago
However I think - Nadh, ronacher, the redis bro - these are people who can be trusted. I find Nadh's article (OP) quite balanced.
unknown|1 month ago
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wiseowise|1 month ago
> Proceeds to write literal books of markdown to get something meaningful
>> It requires no special training, no new language or framework to learn, and has practically no entry barriers—just good old critical thinking and foundational human skills, and competence to run the machinery.
> Wrote a paragraph about how it is important to have serious experience to understand the generated code prior to that
>> For the first time ever, good talk is exponentially more valuable than good code. The ramifications of this are significant and disruptive. This time, it is different.
> This time is different bro I swear, just one more model, just one more scale-up, just one more trillion parameters, bro we’re basically at AGI
athrowaway3z|1 month ago
We practically found one thought. The measure is: how well can an AI operate in/with your codebase.
I regularly find myself wondering if skeptics throwing around their empirical failure are obscuring their bad code/docs/setup.
Sophira|1 month ago
AI is a useful tool, agreed - but it will always be reliant upon humans writing code.
Let's take a very simple example to prove my point. Let's say that everybody is now using AI to write code, and someone develops a new programming language with it. Cool! We have a new language now.
What we don't have, however, are any examples of how that programming language is used. Nothing that the AI can learn from.
How well do you think AI is going to handle being able to code in this new language which doesn't appear at all in its training data?
draven|1 month ago
dmitrygr|1 month ago
Usually one can tell quite easily, actually...
pico303|1 month ago
SLWW|1 month ago
Also, that projects page on his website is atrocious; hate to be "that guy" but I don't trust the author's insight since "personal projects" seems to include a lot more than just his work; the first several PRs I looked at where all vibed.
I'm not interested in re-implementations of the same wheel over and over again telling me and people who know how to write real software (have been doing it since I was 12) that we are becoming unnecessary bc you can bully an extremely complex machine built on a base theory of heuristics abstracted out endlessly (perceptually) to re-invent the same specs in slightly different flavors.
> 100% human written, including emdashes. Sigh. If you can't write without emdashes, maybe you spend too much time with LLMs and not enough time reading and learning on your own. Also people can lie on the Internet, they do it all the time, and if not then I'm doing it right now.
The hubris on display is fascinating.
hellolio|1 month ago
keybored|1 month ago
What soft-skill buzzword will be the next one as the capital owners take more of the supposed productivity profits?
galaxyLogic|1 month ago
dist-epoch|1 month ago
lioeters|1 month ago
raincole|1 month ago
This quote is from Torvalds, and I'm quite sure that if he weren't able to write eloquent English no one would know Linux today.
Code is important when it's the best medium to express the essence of your thoughts. Just like a composer cannot express the music in his head with English words.
CuriouslyC|1 month ago
Imustaskforhelp|1 month ago
I just re-watched the video (currently halfway) & I feel like the point of Linux is something which you are forgetting but it was never intended to grow so much and Linux himself in the video when asked says that he never had a moment where he went like oh this went big.
In fact he talks about when the project was little. On how he had gratitude when the project had 10 people maybe 100 people working on it and then things only grow over a very large time frame (more than 25-30years? maybe now 35 just searched 34)
He talks about how he got other people's idea which he couldn't have thought of things themselves and when he first created the project he just wanted to show off to the world to look at what I did (and he did it mainly for both the end result of the project and programming itself too) and then he got introduced to open source (free software) by his friend and he just decided to have it open source.
My point is it was neither the code nor the talk. Linus is the best person to maintain Linux, why? Because he has been passionate over it for 25 years. I feel like Linux would be just as interested in talking about the code and any improvements now with maybe the same vigour as 34 years ago. He loves his creation & we love Linux too :)
Another small point I wish to add is that if talk was the only thing, then you are missing the point because Linux was created because hurd was getting delayed (so all talks no code)
Linux himself says that if the hurd kernel would've been released earlier, Linux wouldn't have been created.
So all talk no code Hurd project (which from what I hear right now is still a bit limbo as now everyone [rightfully?] uses linux) is what led to creation of linux project.
Everyone who hasn't watched Linus's ted ed should definitely watch it.
The Mind Behind Linux | Linus Torvalds | TED : https://www.youtube.com/watch?v=o8NPllzkFhE
whatever1|1 month ago
Put the agent on the wheel and observe it as it tries ruthlessly to pass the test. These days, likely it will manage to pass the tests after 3-5 loops, which I find fascinating.
Close the loop, and try an LLM. You will be surprised.
monster_truck|1 month ago
Classical indicators of good software are still very relevant and valid!
Building something substantial and material (ie not an api wrapper+gui, to-do list) that is undeniably well made, while being faster and easier than it used to be, still takes a _lot_ of work. Even though you don't have to write a line of code, it moves so fast that you are now spending 3.5-4 days of your work week reading code, using the project, running benchmarks and experimental test lanes, reviewing specs and plans, drafting specs, defining features and tests.
The level of granularity needed to get earnestly good results is more than most people are used to. It's directly centered at the intersection between spec heavy engineering work and writing requirements for a large, high quality offshore dev team that is endearingly literal in how they interpret instructions. Depending on the work, I've found that I average around one 'task' per 22-35 lines of code.
You'll discover a new sense of profound respect for the better PMs, QA Leads, Eng Directors you have worked with. Months of progress happen each week. You'll know you're doing it right when you ask an Agent to evaluate the work since last week and it assumes it is reviewing the output of a medium sized business and offers to make Jira tickets.
giancarlostoro|1 month ago
w10-1|1 month ago
The real "cost" of software is reliance: what risk do your API clients or customers take in relying on you? This is just as true for free-as-in-beer software as for SaaS with enterprise SLA's.
In software and in professions, providers have some combination of method and qualifications or authority which justifies reliance by their clients. Both education and software have reduced the reliance on naked authority, but a good track record remains the gold standard.
So providers (individuals and companies) have to ask how much of their reputation do they want to risk on any new method (AI, agile, ...)? Initially, it's always a promising boost in productivity. But then...
So the real question is what "Show me" means - for a quick meet, an enterprise sale, an enduring human-scale consumer dependence...
So, prediction: AI companies and people that can "show me" will be the winners.
(Unfortunately, we've also seen competitive advantage accrue to dystopian hiding of truth and risk, which would have the same transaction-positive effect but shift and defer the burden of risk. Let's hope...)
MyHonestOpinon|1 month ago
- A good and experienced developer who knows how to organize and structure systems will become more productive.
- An inexperienced developer will also be able to produce more code but not necessarily systems that are maintainable.
- A sloppy developer will produce more slop.
heliumtera|1 month ago
I hate this trend of using adjectives to describe systems.
Fast Secure Sandboxed Minimal Reliable Robust Production grade AI ready Let's you _____ Enables you to _____
But somewhat I agree, code is essentially free, you can shit out infinite amounts of code. Unless it's good, then show the code instead. If your code is shit, show the program. If your program is shit, your code is worse, but you still pursing an interesting idea (in your eyes), show the prompt instead of the slop generated. Or even better communicate an elaborate version of the prompt.
>One can no longer know whether such a repository was “vibe”
This is absurd. Simply false, people can spot INSTANTLY when the code is good, see: https://news.ycombinator.com/item?id=46753708
bicepjai|1 month ago
karmasimida|1 month ago
pmg101|1 month ago
datatrashfire|1 month ago
expertise and effort is and will continue to be for the forseeable future essential.
talk, like this, still cheap.
captain5123|1 month ago
unknown|1 month ago
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v3ss0n|1 month ago
api|1 month ago
I think that's always been true. The ideas and reasoning process matter. So does the end product. If you produced it with an LLM and it sucks, it still sucks.
toddmorrow|1 month ago
dbtablesorrows|1 month ago
unknown|1 month ago
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funnyfoobar|1 month ago