Agreed. I started writing a desktop GUI harness in Rust using native desktop GUI APIs.
Claude, Codex, Opencode, everything is Electron. With agents and solid engineering fundamentals, I set out to prove that we don't need to take that shortcut any more and we can, in fact, ship high quality/performance applications.
It's still early days - but I got something basic working. I've embedded the Goose harness as a back end and am using the UI framework used by the Zed editor.
I'm keeping the source closed for a little while. Also if anyone from the major labs is hiring, hihi, I make quality things.
Also I'm aware that this is a rip off of vscode's design. I like their UI, lends itself well to projects and so on. In a different life I might have ported vscode to Rust - but no one uses IDEs any more haha
> Naturally, game engines are crazy optimized, so the UI runs butter smooth and uses pretty much no resources.
We should build everything using a AAA FPS engine loop now that we can. The amount of shit that happens in one rendered frame of overwatch is wild. And then we go and do like 200 of those per second.
This is awesome and I'm glad things are moving in this direction. I've been playing with Crux (Rust + Native UI) myself: https://github.com/redbadger/crux
A lot of the AI discussion seems to be focused on what these tools mean for an individual developer, but in a team setting any gains are at risk due to coordination tax and ideological friction. In my experience the ideological friction is most of it right now.
Figuring out a way to accelerate the process in light of the code writing bottleneck being removed is essential. I've observed a development team regress back to fully manual development because their daily PR/code review process is too slow. It doesn't matter how fast you write code if you can't actually merge it and ship it to the customer faster too. PR stacks can only take you so far before the conflict monster gets too big to fight.
I don't think AI can fix the process, ideology or people issues. I've seen how long an average PR review actually takes. If these employees were simply doing their jobs at all we'd be 10x better off regardless of AI. A truly skilled developer who makes a genuine attempt should be expected to solve 99% of their tasks within the same business day as of October 2026.
Burning down the backlog to zero doesn't mean the development team will be subsequently laid off. Quite the contrary. It will create a vacuum that the business will fill with new work that may incidentally increase the developers' compensation packages. No one is laying off the development team that just chewed through 50 items per day for 3 straight weeks. Who would support all the potential bugs they just created? That's right. They might hire even more developers. This is called a "win-win" scenario. Not every game must be zero sum, but I understand rejection of this possibility to be part of the aforementioned ideological issues.
>I've seen how long an average PR review actually takes
This was a problem well before AI, but it doesn't get talked about enough because so many developers are hooked on the power trip they get from making people waste time on crap that has no relevance to the user.
More than ambitious, I can now build things I had no time for but had the idea and architecture in place since long. A cool side project for me recently has been to allow reading more than books on my Kobo reader. I built an SDK and apps that allows e-ink apps with sandboxing and permissions model, auto-updates, shared capabilities etc. to be built for Kobo https://github.com/BandarLabs/Cobalt
I think it's worth remembering that outside of our bubble the quality of software is pretty bad. I had a Hitachi heat pump (not recommended) installed earlier this year, and the software is pretty disappointing. It mostly works, but there are so many undocumented features and hard coded values that should be a configuration option but are not.
For example when the heat pump reaches the target temperature it shuts off, then after 3 minutes switches on again. To prevent short cycling, I'd like to decrease the time between runs (so increase the 3 minutes) but that can't be changed. Somebody decided that 3 minutes is the correct value for everybody and that's it.
I bought a €400 interface box (basically just a serial to IP interface, I guess $20 of hardware tops) to try and improve it. The €8000 heat pump doesn't come with WiFi or ethernet out of the box, you need to buy an accessory for that. It's not made by Hitachi, but it's an officially recommended accessory. One of what feature I wanted it for - which is advertised in their marketing materials - doesn't work.
I emailed them, and they said it's probably because the display I have is a newer revision and doesn't allow access to the setting I need to turn on. And without turning that setting on I can't use the feature as advertised. They said I should email Hitachi and talk to them instead as it's not their part that's the issue.
I look forward to the world where all software is either open source, or at least reverse engineerable to the point where you no longer have nonsense like this.
I’ve built a retro operating system and programming environment for ESP32 microcontrollers called BASIC32.
I took it to 39% complete, as a language, over 8-weeks. Then, I spent just 50 minutes describing all the missing parts and it finished the language in 1-shot. I didn’t think it would work. It did.
I used Opus 5.5 on a $20 plan and I didn’t even hit my limits.
I have a feeling that the 39% served as a good framework for the LLM to work on the remaining part while keeping it consistent with the existing structure and style. So, in a sense, your 8 weeks are a big part of why it succeeded.
Yeah I've experienced that at work. I see a lot of comments on here saying you can't one shot features in real world software, but we do, and yes we still have a human review the code with a high bar.
But we've also spend a lot of effort over the past year and a half to make the codebase and tooling more approachable to LLMs so they know how we like to do things and follow our standards.
There's so many youtube channels getting hundreds of thousands of views on EVERY new major model release just doing essentially zero effort one-shots, and people lap it up as if building things that already exist is somehow the best their imagination allows for.
I do love being able to test a model for 3+ weeks (>1 month is too long personally for my budget) and actually learning how to build scalable software and actually develop your "engineering" skills.
I used Fable 5.1 and Opus 5.5 to build a Python interpreter in Rust. Appears to pass all the 3.12 code I throw at it.
To get a toy version that can run most things takes under 2 hrs. Half of that time is collecting the tests you want to pass, how it should evaluate the code, what your criteria are, etc.
This is really what people conflagrate so often with these tasks, it is basically making the model do recall what could also be a "ant_ag_ds_90917_rwpy9_final" git clone
This sort of ‘it’s probably in the dataset’ thinking is a bit of a relic from the ‘stochastic parrot’ era of LLM critique.
Reinforcement learning doesn’t work by training an LLM on a series of inputs like ‘rewrite python in befunge’ paired with a prepared model implementation. It doesn’t matter if an open source implementation was in the dataset that trained the language model. All it got from that was an appreciation for syntax and language idiom; when it is generating code it’s doing so according to the approaches and patterns that it’s been reinforced into following in the context of a coding prompt - regurgitating existing codebases is undesirable so it is a behavior it will have been reinforced against.
I don't think they are saying its regurgitation, but rather that the "approaches and patterns" used to build a python interpreter are in the training data because the training data asks the llm to build one.
>All it got from that was an appreciation for syntax and language idiom;
Sounds like it's you who is behind the times. With things like REA we know that LLMs can reverse engineer the behaviour of binaries and basically treat them as a form of specification to rebuild an application.
This means that old python interpreter acts like a specification for what kind of features must be included inside the project.
LLMs are amazing at input to output transformations and that hasn't changed at all.
I think it's you who has to update his mental model away from "stochastic parrot era" accusations.
PS: if you're trying to accuse me of being a "stochastic parroter", that's exactly what I mean.
Taking an input and transforming it to an output is the exact opposite of repeating something.
CPython is in the training data, but this was a tree walking interpreter, so it wasn't just regurgitating cpython. I capped it as 1000 lines for the first 20% of the project, it is currently 13.3kloc and 575k in a single file.
The 'blockviz' is same kind-of project i tried to create as well (c4 level model zoomable etc.) so i was surprised to see same kind-of project popup - but this is I think also an 'issue' with these model-created-software.. when you reach'your' vision its already done: for example I clicked on the github link, expected a clear About Install Faq kind of README.md but all I get is the model-created explaination :) can't just download some app and use it without friction. I see this a lot.
yeah, one-shot (medium-large) builds just don't seem to give me good results yet. I use them now for small examples though, e.g. for visualizing a process. Most recently I used it to visualize neural networks, and how convolution works. That might not be something most people need, but it really helped me.
Hah, found someone else also using it for visualizations of algos! I've used it to show me how quad-trees[0] work and I'm impressed with the results. One-shotted too so I agree one-shots are best for this kind of very specific scenario.
> I've been attempting to build something that ... pushes the model ... never understood ... one-shot builds
Same, and I have found some of the failure modes in the realm of eyes free coding and limited auditing. I often see it more as pushing the process than the model, as I tend to bounce around models for the benefits diversity provides.
Have you also found there is a point where they hit code complexity and start churning without progress? (at which point you have to step in to help the bot step back and think big picture, which usually takes a few sessions)
Yes! I absolutely have! And I've been thinking a lot lately about how to prevent them from collapsing into this state. It is getting better with newer and better models though. But yes, there comes a point when the codebase size and complexity crosses a threshold and we enter a churn state with very little progress.
I was motivated to make the codebase visualizer linked above to help me understand how the various pieces of the system that is being vibe coded connect with each other.
Now I'm thinking about how I can build something similar for agents. How can we teach "systems thinking" to a model?
I've been mostly working on very large modeling projects (think detailed architeture over 1000 acres) or animation because this really was the "new" capability area that Opus 5.5 "unlocked".
I have been surprised how well it has worked at scale with many sub-agents. However the code base is limited to the rendering engine mostly.
Certainly in the older models they hit a complexity limit, but I haven't really hit it with Opus 5.5. I have had it make data flow designs that I didn't like because they were more complicated than it should have been or the perenial problem of trying to make everything backwards compatible when working on greenfield refactors, but I haven't seen it choke on a code base yet.
Yes, I've also hit it with Opus 5.5, but on way fewer projects. My long standing projects that I marked as failed/to-soon with 4.8 have entered the grey area of slow-progress-with-handholding like smaller projects did in the past.
To my experience, it's a simple complexity curve where the first bits go fast and the speed goes down very fast once you reach a certain level of complexity. Size doesn't matter as much as complexity: with the right foundations, it keeps zooming through it. Now I do wonder how much my inexperience in the complicated project is a brake on progress vs. it just being a hard to tackle problem.
My sense is the limit is more tied to the problem than the code base size. I work in some very large code bases, but it's not an issue because the nature of the problem (think what a standard SaaS would need).
On the other hand, I have a TS only project core is sub-20k LoC (NES harness), where it is struggling (for now, see other comments)
I just have it constantly update real-world analogues for keeping track of everything. I have it create guides, note cards, flowcharts, running to-do lists, etc. with every change.
It helps us keep track of things, why not AI, too?
I've been working on process more than model. Similar to having a PR review team, you need multiple teams or processes that run over the code, markdown, assumptions. I still don't think this is enough.
I'm working on an NES harness, and the agent was churning with detecting certain state changes like dialogs, menu navigation, screen change. The bot and I got churning and I put it down for a while. A few days later it occured to me to ask the bot "Does the emulator and game state change with frames? Can we just get the state each frame rather than trying to be clever about it?"
It said yes, but added some nonsense about being performance hindered... (flash model). I haven't worked on it again yet, but my intention was to next have it build a small recorder based on this so it can get frame accurate game state change.
This is just a long way of saying, sometimes you have to step back and help them help themselves. They have a really hard time with recognizing ambiguity or how to determine lack of context that could be filled.
> I have a similar thought about "there's no reason for software to be slow" BTW; in many cases, if you use AI to speed up some flow, you will add a bunch of messy code that will be overfit for the use case you tested on and will neither generalize, perf-wise, for all the use cases you should care about, nor will be maintainable upon future changes.
LLMs have hardened hundreds of apps where I work.
Maybe it's a language-specific thing. Most of the time, in Java, LLMs take into consideration tradeoffs (especially if they are part of the initial prompt) and actively explains them. It generally won't make messy workarounds, without a lot of extra prompting forcing it to do so.
Ofc, if you have:
- Functional tests - you'll be able to see it in the execution times of specific APIs
- Stress testing - performance profiling is the most important output artifact
> Maybe it's a language-specific thing. Most of the time, in Java, LLMs take into consideration tradeoffs (especially if they are part of the initial prompt) and actively explains them. It generally won't make messy workarounds, without a lot of extra prompting forcing it to do so.
Claude in its current Opus 5.5 form has made some wild reaches in response to reasonable-seeming prompts. For instance: "this error is getting swallowed, make sure the real termination message exposes the root cause" -> discovering that the issue is actually in a third party library that isn't exposing the original error except so through logs, so doing some hackery to inject a log-capturer that gets the stdout, buffers it, and looks for the message in order to re-throw based on that...
And it can demonstrate that working, but it's added some fragile and/or unintended consequences like (a) string matching on a particular WARN log message of a particular version of the lib, and (b) buffering those logs such that there were now cases where they would never make it to the actual output stream before the program terminating.
It's certainly capable of being used smarter than that, but it's also really easy to end up with messy fragile stuff if you get lazy about reviewing the output.
> "this error is getting swallowed, make sure the real termination message exposes the root cause"
Without judgement, I think this illustrates a fundamental objection the anti-AI crowd raises.
The example prompt requires no understanding of what's happening, before suggesting action. Where I work, process requires that a PR review for a solution, has to have a corresponding explanation of why, or it's marked needs work
I think there's some nuance here though between "fully anti-AI" and "be careful with that power saw."
That example I mentioned didn't make it to production. It got noticed and fixed more properly by the person who submitted the first prompt before it even went to PR.
But a lot of times things in that same vein can be solved sufficiently with a "dumb" prompt like that, so a one-line prompt to get a PR drafted in the background for the dumb stuff can be a pretty good time saver.
The art is not skimping on your attention to the bigger or more important stuff so much that all the time you save on first getting code written is lost by cleaning up stuff like that...
I used Opus 5.5 to figure out that a language model we were serving at work for internal use (we don't really serve models, we only use this internally because it processes sensitive data that we can't send to external endpoints) was being bottlenecked by CPU contention on tokenization, by having Opus run in an autoresearch style loop.
Opus's first proposal for a fix was to spawn multiple Python processes and build a load balancer between them in Python. At first I asked it why it wasn't using haproxy and it said that haproxy would be an added dependency and that the overhead for this kind of thing in Python would be negligible. I knew this was idiotic but wanted to test this out, so had Opus run two experiments in parallel. Sure enough an haproxy load balancer was much, much better on HTTP load balancing than Python code was.
This is the kind of thing that if you're unfamiliar with how networking code works, the models can autopilot into bad decisions that are verifiably correct (higher throughput than the original CPU-bottlenecked implementation) but much short of best practice.
LLMs are great for being nerdsniped. I started work on walshadow (reading pg wal into clickhouse) to demonstrate the project's infeasibility, but pieces started coming together into something reasonable & order of magnitude faster
The project would've been impossible for me without LLMs. & even with them there's an argument that this project is pushing complexity limits too far. But at least with ETL there's a clear feedback loop to build on
Thank you for introducing me to the word "nerd-sniping"[1].
This is, as you say, exactly the paradox of having ourselves assisted by LLMs. We are no different from our cats. Except imagine the cats start making the laser lights for themselves.
We should be more ambitious, but we need to learn how we can be ambitious with AI, and what value we can create.
AI can take us from 0 to MVP in a prompt. It can fill in gaps of knowledge and allows someone who knows half of the stack to build the whole thing nearly seamlessly. These are superpowers but don't by themselves lead to new products.
What AI cannot do is remove the world of complications that happen after the MVP - product feature tradeoffs and choices, how to handle integrations and customizations, how to serve multiple types of users, how to communicate and market the app, how to handle security and data storage, how to deal with customers and bugs, etc. All of these need to be considered and acted on by a human in some fashion. AI can help with each concern but can't solve them without understanding the concern and determining how to frame it in a prompt.
This is why we have a glut of amazing demos that go nowhere while we figure out how to build software differently. This will take some time and I imagine the result will be software heavily-structured with a bit of AI reasoning woven throughout, not an army of agents and sub-agents burning infinite tokens.
Right, but this is the most hopeful imaginable prediction: AI accelerates everything, but everything good is still mediated through taste and expertise, so being a (say) skilled systems engineer is important and rewarding, just with all the tedium distilled out of it.
There's a less hopeful outcome, where no skill is needed at all, because every conceivable thing is one-shot-able from a SOTA model. But then, at that point, you're saying something pretty profound about computer science (roughly: that there was no meaningfully more sophisticated and complex place to go from where we are today).
My wife is not a developer at all but is highly analytical. I find her a better software architect than most developers I met.
I suspect there are a lot of people really good at “systems” - there are a lot of really clever folks out there - that did not go through the proper CS rituals and are thus shunned but in fact can take over your job in no time especially with AI.
My wife regularly gets pushed away by “IT” at her work and unlike others she pushes back, but they don’t like her. They start talking about db clustering details etc as if that has any bearing on anything. I am a dev, I know she doesn’t know what logical replication is, but I do know she can replace their team. She just needs one technical person to keep an eye on things.
I suspect we will end up with just a handful of building blocks like “this is how data is siloed, secured etc”, “this is how dashboards are made here”, “this is how email is handled”, etc and employees with AI just develop their own stuff on top of these. The “devs” just oversee the building blocks and the overall soundness of the flow. Don’t know how many you need once that is standardized..
That’s something that I have been thinking about for a while now. Even prior to LLMs, many large companies have essentially been iterating on the same half a dozen ideas over and over again and there doesn’t seem to be much new coming out even post LLMs.
The most recent new things that LLMs have unlocked (regarding software dev) for us is reverse engineering and combining old games, unearthing decade old vulnerabilities, and helping root and debloat consumer hardware. Which are all cool and useful, but none of it being a “next great thing”.
Perhaps LLMs are really doing is highlighting how the software industry was already nearing its economic maturity and this just shifted the timeline from 2040 back to 2027-2030.
Don’t forget we don’t live in a pacifist utopia. Companies don’t work on the same ideas just because they think they can make it better.
Companies work on the same ideas because they want to own IP, data etc. and then charge money.
The other way around they work on the same ideas not to be charged by others and control their business.
“software industry” is not some big happy hippie family. Patent wars, browser wars, OS wars - well we get a lot of open source for free but that’s not the norm.
I have yet to see LLMs do well “autonomously” on anything that doesn’t fall into any of these 3 buckets:
1. well specified
2. well tested (which is a form of spec)
3. represented in the training set (i.e. not built on a corpus of human developed examples)
For example, a lot of the compiler porting efforts fall into all 3 buckets: compilers are well specified (there is a set of valid inputs and an expected behavior), they are typically well tested, and as a bonus, in a way that is implementation agnostic thanks to the clean interface (think: integration vs unit tests), and are very well represented in the training set.
You can "solve" 1 and 2 by N-version programming. Have the same code implemented twice, or more times, you get free error testing by fuzzing or running replicas in shadow mode. In order to make replicas maximally different choose a different language, framework, agent harness and LLM.
There remain some nitty details related to tracking randomness and choosing what interfaces to log. But even having your code testable by replicas would help organize it better and expose different assumptions made by the language or library stack.
When you get different outputs from replicas it can be 1. one of them has a bug, or 2. the spec is unclear -> fix the bug or the spec. So this method catches both sides. It also might be faster than traditional code based testing, you can build replicas in parallel. A replica is an open ended test, unlike coded tests it can be tried on open ended input values.
The core idea is that it is easier to implement twice than to imagine bugs. We already solved implementation, but bug finding means running code in your head, it touches the halting problem issues - can we really imagine behavior from code? I don't think we can do it well. That is why we should just make replicas instead, tokens are getting cheaper and cheaper by the month.
and yet some OSS (projects not really known for 1 and 2) multiplied change velocity the last year, implementing features via what is essentially vibecoding.
If you look at that, this approach is producing a pile of slop, where one LLM implements a feature, two weeks later another LLM spots an edge case and without much human review just crams in the code to fix that. Even at 1-2 months of that, those repos have significant changes and the commit messages get weird. I wonder what happens if the LLM won't spit out a fix anymore?
Will the human maintainers who started this process because noone thanked them and noone wanted to work with them on their bright new ideas just reset to the last commit they understand? Will they drop the project? The sunk cost for them is enormous. The time-effort required to fix the mess is gargantuan already. To me it increasingly seems that after the LLM industry robbed most humans of their collective labour output it will now rob them of labour aka time as well. Some people (like you and me) seem to notice that but most just go on and essentially spend away their life on machines now. I guess the problem is that most of these people have been severely cut off from using their own agency.
Honestly I think you're on to something, as by far the most novel and interesting use cases I've seen for LLMs in general are mostly around reverse engineering things, especially if you can hit it with Ghidra, but honestly anything that can feed some sort of data and control back to a model.
> the software industry was already nearing its economic maturity
What I'm sensing is something I might describe as the Oligarchy reaching the point of significant societal pushback, like the labor rights movements that ended 80 work weeks, unsafe conditions, and child labor in factories (i.e. The Jungle).
My hope is that we can use this moment in human history to break the user tracking and targeted advertising industry. It's been so harmful to humans, but in doing so, we will likely break a major revenue source that supports our well above average salaries. I still think it should be done.
What would be funny with LLMs, having been purposefully trained to be the best software creating things on earth, wind up inadvertently making software virtually valueless (because it can be made and copied so easily) and undermining the value of the companies that proliferated their use in the first place.
> What would be funny with LLMs, having been purposefully trained to be the best software creating things on earth, wind up inadvertently making software virtually valueless
This is the world the accelerationists are trying to create, is it not? Fully automated luxury space communism through AI solving all earthly problems.
We're just unlucky that software is one of the first moats to fall (alongside the humanities), because it doesn't require developing novel ways for the AI to interact with the real world...
We'll have to separate the hardware providers from the software providers, which I'm growing more fond of. The US Ai stack is largely a vertically integrated cartel.
I haven't yet seen any significant products made with AI that are at least used long-term. All these browser demos, from the Adobe killers to Star Citizen, are just bells and whistles that I close after 30 seconds of use.
"Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away."
And I feel that sums up my feelings on AI this and that. Just as the wood and clay contain the sculpture within and it's the artist's duty and privilege to reveal that. So, is elegant software exposed from the conceptual mass, rather than built up.
The AI zeitgeist currently is 'how many features can I add' because we've tied self worth to work output instead of some other more personal or human rubric. AI will happily pile more and more and more code on your plate because it's a buffet. It's gone through reinforcement cycles guiding it to add whatever feature you ask. There is no training for elegance or careful considered design. Nobody is teaching this generation of LLM restraint.
The safest code is that which never runs. The most elegant feature is that which is not necessary.
"The safest code is that which never runs. The most elegant feature is that which is not necessary."
I assume you run GNU Hurd as your OS? ...
In general I very much agree to the quote of the Little Prince's creator, but I am not sure if we mean the same by it, because you seem to value code elegance more than adding useful features?
Now "useful" does the heavy lifting here, but my point is a useful feature is useful, even if it is achieved by the most ugly unmaintainable code. And what counts as a useful feature will depend on who you ask, but in general you should ask some users. (They don't care how the code looks)
And sure, they do not enjoy a pile of garbage of new features that only work sometimes, but managed to destroy their existing flow. But "Nobody is teaching this generation of LLM restraint" this is hyperbole and up to each developer. There is no need to let the AI run on auto for hours, this is only one way how to use that tool. The other way is, you make the design yourself - and let the AI implement it.
Agreed. Been experiencing this firsthand with an app I've been building myself. Vibecoded a working prototype ridiculously fast but then came the optimization issues. Since mine is very hardware dependent every different brand, oem stack, processor, video card, and every little thing changes how my app functions and a lot of it isnt even documented properly. Now AI is still very useful here, but you actually need to know what even to ask and fix in the first place
There have been a few vibecoded projects I've considered hosting on my home server, but it seems as if each of them doesn't understand when to stop adding new features.
They keep adding features that are outside the scope of the original project, without refining or polishing the original concept.
My interpretation of "be more ambitious" is not only give it harder problems, but be more creative about what you ask. The problem is that most of the MVPs that people ask for a boring and lame. AI can help us make things that blow your mind, things that we would never build because they don't make sense, but the cost models for code generation have changed.
If you're being ambitious enough, you shouldn't be able to there in one prompt. Ambitious work with AI is done 24/7 for months and guiding it continuously, because it's not good enough to work autonomously for that long without going off the rails.
I think there are many of us working on projects with LLMs that'll take months more to reach full production. These will feel very out of left field and we'll have another paradigm shift. I think the real momentum will hit when more of us leave the dull products we're working on, start our own companies, and build the products we're actually excited about.
I encourage everyone else to at least build a privacy first version of a product you actually like.
I don't think the centralized internet will survive this change. We can build something much better.
I think there’s a lot of markets which have been very underserved for a long time which will benefit. One example is embroidery machine software. The proprietary options cost hundreds to thousands of dollars and are slow and ugly. The open source option (bless the people who have worked on it for free) is suboptimal.
With AI we could build top quality free open source tools for every niche.
In the retro gaming handheld space, we are seeing brand new highly custom “distros” show up to suit the plethora of hand held consoles in different shapes and sizes coming out. This is all enabled by AI, a human developer could have built this, but it would have taken ages and we wouldn't have so many options being build.
I get what the author is saying, but his examples like "a ripgrep fork that ... is faster for my codex ripgrep workloads" don't strike me as particularly ambitious.
Perhaps we should be more ambitious in the types of problems we try to solve, and the types of value we try to provide with the software we build.
Amen to that. I was surprised to see yours seems to be the only comment with this sentiment. This post was kind of depressing to read. Like if AI is so amazing and can one-shot so much astounding stuff, why is anyone wasting their time on pointless "projects" like making ripgrep faster?
Because it can cut their total time by double digit percentages?
Both your comments there seem to latch on to a detail and miss the context totally. Ambition scales with the number of "small" things you can get done too.
Total time of what? Like what is the end goal that people are trying to achieve? All of the examples I can see in the post are similarly about development-internal stuff like tests and performance (or games). What I mean by true ambition would be stuff that is actually aimed at helping people in the world at large, not just helping developers develop.
Ambition doesn't scale with the number of small things you get done. Ambition is the size of the big thing you are trying to do. It's true that improving small things can help you do that big thing, but that's not the same as the ambition itself. Wanting to build a better mousetrap is just a modest technical ambition. The kind of ambition I'm talking about is wanting to eradicate the plague, and then maybe building a better mousetrap as a means to that end.
you don't like the ads, gambling apps, and similar? /s
What might help is non-software-first companies valuing developers and engineers more, enough that we could earn a reasonable living which building actually cool things. Not sure how the economics works out on the other side. Can these companies make enough money to support this vision?
One major obstacle is developers have either encountered or created entire ecosystems of problems they can't solve that get inherited whenever and wherever software is introduced. Proposing to add evergreen issues around security, data entry and retention, connectivity, vendor lock-in, and update cycles is frequently a shitty trade for whatever notional (often fictional) productivity improvement is being proposed by injecting software into a workflow.
My building recently added ButterflyMX and boy does no software sound so much better. This is tech company that tracks people as the move across real world properties and sells your data to the ad industry.
I mean they're an excellent example, but this is just as true for the overwhelming majority of B2B productivity suites I've encountered. Hell, digital cameras didn't improve photography, they just killed three industries and saddled just about everyone with data retention and migration problems and that's without even getting into the social effects of ubiquitous cameras combined with social media or the surveillance state they've made possible.
I'm all about ending user tracking, targeted advertising, and gambling. We'll need to find new things to work on that do not use big data to take advantage of our fellow humans.
The note taking genre of opensource apps is saturated with many options but most of them are electron based.
I was hoping that someone with enough motivation and money for tokens would come up with a non-electron option that is similar to onenote, with free form note placement and handwritten notes.
Basically I wish there is an opensource app having good feature parity with OneNote. Thats a good benchmark to have.
an ambitious version of a note-taking program might be one that comes in pieces that you then put together by explaining to an AI what type of program you want, adding only the features you want and ignoring everything else
its always been a problem for me that ive never been able to find something that works exactly how i want, so i just put up with whatever is close enough, like obsidian for example. its probably because note taking is just a very personal thing so everyone is going to have different needs, and the amount of options out there is kind of proof of that
from the point of view of a developer, an AI would help with the complexity of a program that has every feature under the sun, and for the end user ian Ai would help the complexity of having to put all those modules together and making them work well
obviously each person could just vibe code their own program right now but each one would be starting from scratch. it would be more efficient to start with the same modules that have been tried and tested and then piece them together into something more standardised
i would love if this was a thing for most software actually. photoshop for example has only a dozen features that i ever use and the other 1000 features are wasted on me and just mean a longer startup time and a larger install size, but also i dont want want an AI to make me a custom version from scratch because you would probably spend more time trying to iron out all the weird bugs in it than actually using it
A few years ago I was wishing the same, but I was wishing it for someone knowledgeable enough.
Today I wish the same, but for someone with enough motivation and tokens instead.
Don't get the wrong idea: I would be glad for a OneNote/Obsidian alternative that's performant. I just lament the days where I'd stare in awe thinking about the levels of wizardry one must get to in order to build something that I admire. Now the first thing that comes to mind is "I wonder how many tokens did this took them to make".
I don't think you can conclude that nobody cares about it just because they don't constantly mention it.
In any case, I don't think the lack of caring about CO2 emissions is unique to AI. How many people care about Trump's war on green energy? Not many it seems.
I've been seeing too much "I've been coding for decades and what I've always done has be reduced to telling AI to do it for me."
and not nearly enough "I've been coding for decades and recently worked hard for months with AI's help to make something I would have never considered possible before."
Much easier to complain that you are bored than to step back up to high-effort with your new fancy tools.
Those were exactly my thoughts when deciding to write a new JS engine [1] written from scratch.
Having been a product and UX-focused dev for my entire career, I knew only the basics about parsers and compilers, but have enough experience to grasp where each piece of the puzzle fits, and how to evaluate them. At the beginning it was just a fun test, but it got progressively more serious; it now implements 100% of the latest spec, beats QuickJS in performance, and surpasses V8/JSC in test262.
It took me four months, and I imagine it would take me a single month to do it again - I’ve learned a lot. Someone who already knew what they were doing, and with the right orchestration, could achieve this in weeks at minimal cost.
I really think we are in for a cambrian explosion of software, enabling things that were just always a little out of reach before (like why can’t most of your devices really talk to each other, in 2026).
To be clear, I've made large software and game projects over the years, but no way I'd have found the time to do a remake/enhancement of a game I loved as a kid from 1995 that has zero business case. Not without AI.
It is a robust, reliable cache of apt packages, with the additional goal of still being able to serve packages from the cache even when the upstream is down. This was started shortly after that DDoS of Canonical this past year. We've run apt-cacher-ng and apt-cacher over the last dozen years, but (a) it requires hand-holding about once a month and (b) it did absolutely nothing for us when Canonical was under DDoS.
I've put well over 100 hours of my time into it. Still running into a lot of people knee-jerk calling it "slop", but I've had 200-ish machines pulling from it for 6 months and it has worked way better than apt-cacher-ng.
I'm not really sure what to do with people who dismiss AI-assisted projects, while dehumanizing the 100 hours of my time I've put into it. I fear we're running the very real risk of both sides losing: the people trying to thoughtfully create with AI losing because of the AI, and the people avoiding AI losing because they can't keep pace.
To play devil's advocate, that sounds like the sort of uncomplicated thing that you could've manually vibecoded in 2020 without an LLM. What changed is that the LLM doesn't let you get analysis paralysis.
You just write the code, don't stop to think. You only have to implement the very small set of requests that an apt client can make to an apt server. Probably "get package index" and "get package file".
Like za_creature said you can use a language more towards the YOLO end of the spectrum - more Go or Python or JavaScript than assembly or Rust.
Your commit history shows you had an issue of high background CPU use. You probably wouldn't have it in a manually coded implementation.
> you can use a language more towards the YOLO end of the spectrum - more Go or Python or JavaScript than assembly or Rust
You might want to change the way you phrase this idea. I think you meant that Go/Python/JS are more "YOLO-friendly languages" (you'll get into far less trouble if you write slop in them). My initial reading was the opposite. It sounded like you were saying the languages themselves are the slapped together garbage.
Assembly is most certainly not "YOLO-friendly", but is more YOLO.
Building a procedural open world at the scale of a flight sim in UE5, in a month wrote 5k prompts, spent 40B tokens and will likely take at least a trillion more over the next year of full time dev work.
Big solo projects exist, they're just not coming out as frequently because of, uh, how time works
Also, "ok, and now I've cloned your hard work overnight, no need for any decisions on my part, I just had my agent use yours and reverse engineered it and/or used it as an oracle. Why the frown? I thought you were in this for intellectual curiosity and exercising your creativity, not just stroking own ego, right?"
I think we'll see a lot less people willing to share if the end result is just to feed the machine no matter how they arrived at it.
I don't see why I should care about this any more than I cared about "somebody I don't like could read my code and learn from it" in the past. The frontier labs can generate or buy all the training data they need; not releasing your app isn't going to hurt them in the slightest.
I get not wanting to contribute to closed, commercial models. We need to hurry up and get Folding-at-Home style distributed community model training going. At that point, I’d be pretty happy if my projects contributed to improving community models. Even if commercial models benefited too.
It makes me feel actually sick that so many people can't separate their positive feelings about AI from people's misery (it must simply be "complaining"), and vice versa. As if both things can't exist, for some reason. It's a common tribalism problem, but it's been kicked up a hundredfold by AI.
Precisely. I have both feelings simulataneously. I am impressed by what it can do and horrified because I realize what it will do to the job market and society in general. Meanwhile everybody seems to believe that AI will cure cancer and therefore we should let it do all the damage it will do without realizing that people will die because of AI as well (in fact have already died because of AI).
If anything, AI could have prevented this strike by invalidating stale targeting data. The school building had originally been part of an IRGC military installation, then was physically separated about ten years ago. Satellite data would have made it abundantly clear that it was functioning as a school. A human in the loop could have prevented this tragedy by looking at the satellite data, but so could an AI system.
I don't think that's true, Gaza residents die at much higher rates. Give it another 30 years for all the truth to come out and we'll probably learn that 98% of them were already dead as of the time of this comment.
Yes, what is happening in Gaza is disgusting, but the context was people dying on account of AI and this was the most concrete example that came to mind.
AI has essentially stolen my career from me. I _liked_ having to solve complicated problems with software, I enjoyed having to get into the nitty gritty to get things done. I never really cared that much about the actual business problems I was solving, so moving up a layer of abstraction to be some sort of bastardized product manager/architect does not scratch the same itch.
OTOH, for solving problems I care about, AI has been a god send. I can achieve things that I would have never had the time for.
The distinction you're making between "people's misery" and "complaining" is just emotive pandering. You're complaining that people aren't understanding the depths of your misery. That certainly annoys me; everybody has problems.
The amount of sympathy programmers are expecting others to feel about their problems has been kicked up a hundredfold now that its their jobs that have been threatened by AI. Their tribe feels pain more deeply than others, I guess.
My positive feelings about AI are marginal; my feelings about its performance and the power of the people who scheme to control it are very mixed. My negative feelings about the whining of the most coddled profession on the planet outside of finance are intense.
The problem is that making CRUD apps is not creative, and even if AI plateaus at mediocre, it will still replace a Rails monkey. If you are creative, AI has opened up a world of possibility and productivity, and you painfully feel the limitations and the stupidity of the current level of LLMs; but if you're a mechanic, it's over - I'm pretty sure that was the keynote at the last Rails con. Sorry. Hope you didn't spend all of your massive incomes on toys and rent.
> The amount of sympathy programmers are expecting others to feel about their problems has been kicked up a hundredfold now that its their jobs that have been threatened by AI. Their tribe feels pain more deeply than others, I guess.
Well, just wait then, lots of other professions will soon get to realize the same sort of pain, so you'll be able to be similarly dismissive and condescending to them, too.
A lot of people don't realize that the frontier AI companies are so focused on automating software development first because they are all racing to be the first to get to RSI. I don't know if RSI will actually happen, but many, many other professions will soon be in the same boat. Mathematicians have already felt the pain, and those mathematicians who aren't the few who have tenured professorships are certainly not (generally) some of the most coddled professionals.
But lots of folks low on the salary totem pole (copywriters, paralegals, etc.) are already being hit hard by AI and that blast radius will continue to grow.
Plenty of other professions were hit by computing. Part of why programmers are so emotive about this concept (other than the fact that emoting online loudly seems to be much more accepted in software than other professions) is that programming has never been threatened in the same way as other professions have been until now.
My parents-in-law started their careers as management consultants. The job in their time was much higher prestige and much higher value than it was when I started my career; free flow of information over the internet and commodification of spreadsheets changed all of it. From my parents' generation, I know practical effects folks who became unemployable once movies went to digital effects; engineers who found their draftsmanship skills obsolete. Folks with near-photographic memories whose entire superpower was destroyed by computing. I personally grew up in a blue collar community that was income depressed because its labor became commodified, though that was due to mechanization.
FWIW, I agree with pretty much everything you've said. But I don't think it's unique to any profession or individual that they tend to care the most deeply when it hits them directly.
The only thing I don't really agree with is where you say "My parents-in-law started their careers as management consultants. The job in their time was much higher prestige and much higher value than it was when I started my career." I still think of management consultants as some of the highest paid careers around, and getting a partnership track job at one of the Big 3 is one of the most desirable jobs (for MBA types anyway) there is, so I just don't know what you're talking about with this one.
> you'll be able to be similarly dismissive and condescending to them, too
And? Who are these people that need all this sympathy from internet strangers? Grow the fuck up and go solve your own damn problems. I can’t stand these “I need internet strangers to tell me that my life is, in fact, hard” people.
if the complaints can be properly pointed at the actual problem - the corporate culture the complainers are actively upholding or the capitalist system at large, id be much more sympathetic
its a tribalism problem, but one of trying to uphold the current tribe system while theres a pretty obvious new tribe system replacing it
The whole "needing a job" thing is already part of a tribe though. It's a tribe that says (and enforces) that everyone needs to work for money or else.
I don’t think bluefirebrand is in the tribe of “everyone must have a job or die” so much as they’re in the tribe of “everyone says I must have a job or die”. Like yeah if I was forced at gunpoint to possess something or be ostracized from society then I too would be a little perturbed if someone made an automatic “take away the thing” device.
Yeah, correct, but I think it's also necessary to apportion blame correctly. Tribalism is a big part of the problem here. When people propose solutions to this problem they're often met with purely tribalist counter-screaming.
Well you’re not alone, I’m a little more stubbornly optimistic perhaps, but I feel your stress.
My comforting thoughts are, who is this all for, and what would happen if AI actually makes human labor redundant? Labs control the AI sure, but so much stuff is built around humans that it almost becomes comical to think it would be a bad outcome for a the average person.
Farms and land don’t cease to exist, houses/apartments don’t go up in flames instantly, people aren’t reduced to functionless sludge creatures as soon as they’re done being economic drivers. What’s the real plan? All the normal people die and a thousand or so chosen few sit around and watch AI videos and eat grapes until the heat death of the universe?
Nah, we’ll figure it out, perhaps it will be harder temporarily, and perhaps SWEs lose status before everyone else, but it will probably be okay overall.
But the incentives are not aligned, we are slaves to Moloch, the god of path dependence as described in Slate Star Codex.
Imagine what happens if landlords decided one day to collectively demand more money than actually exists in the total monthly income of workers. What would happen?
You can point out that if everyone just stopped paying rent, their houses and apartments would still exist, and they could live rent-free as their landlords would have no money to spend on enforcement. Technically, this is not untrue. But it's not what would actually happen, is it? One person would be the first to default on their rent, and their landlord would use the money collected from all their other tenants to seize back that tenant's formerly rented property. No individual tenant would dare to be the first to stop paying rent, so they all continue paying rent, selling their stuff, taking out loans until there's physically no way for them to keep paying, and only then do they default.
‘Having to work for money’ beats ‘having to hunt and farm for food’ and it’s technically a small step away.
‘Not having to work and being warm and fed’ is called being a pet. Some cats and dogs enjoy this life greatly. I’ve been thinking about this a lot recently.
What makes you think everybody will be able to adapt to 'the new reality'? That's pretty cruel.
I know plenty of people in their late 40's 50's and 60's that were doing fine and who now have to compete with junior and Claude.
And sometimes just Claude.
Obviously they had no inherent right to income but still, people have obligations that need to be met and if they stop spending the economy is not going to be happy. Especially cruel because we have been telling everybody for decades that a career in software is stable and that there will always be a need for more people.
I suspect that when all this is over 1929 will look pretty good.
> What makes you think everybody will be able to adapt to 'the new reality'? That's pretty cruel.
I don’t, necessarily; but I do know that if you’re not even trying, then you’re putting yourself at greater risk. This isn’t one of those developments that people can just stubbornly dig their heels in about.
Life throws obstacles at everyone. Learning how to dodge and weave is essential to survival.
> I suspect that when all this is over 1929 will look pretty good.
> I don’t, necessarily; but I do know that if you’re not even trying, then you’re putting yourself at greater risk.
We could also all put our gifts toward preventing the "new reality" you see as inevitable, and put you at greater risk.
The future isn't written yet. Your ability to predict it is an illusion. In aggregate, people whose job it is to predict large-scale economic events are worse than chance in their predictions.
This is sensible and pragmatic, but I think you're talking past the other commenter.
Obstacles presented by, for example, your boss, or your company's competitors, or your political system, are not the same as obstacles like heartbreak, natural disasters, emotions, illnesses we cannot yet cure.
> Learning how to dodge and weave is essential to survival.
A lot of people perceive that elites are throwing dodgeballs at them in order to increase their own profits. Saying "them's the breaks, it's just the way it is" appears to be deflecting criticism from those elites and that system.
It probably depends on whether you think we could actually feed everyone, today, if we chose to, or if you think e.g. human nature prevents that from being possible.
Seriously: this is a massive problem that we are creating and given that the tools that make the problem require better tools to solve them I really am not all that happy about how this is going.
Sorry but you are coming off as utterly tone deaf and patronizing. People are losing their jobs. This is not a small thing and it will cause a lot of misery for those people. To effectively tell them to man up and to adapt when that simply isn't an option is losing sight of the human angle. Not every problem is a technical one and not every problem can be solved with technology.
I'm not worried about myself, I've had a lot of luck in my life for which I'm super greatful. But I'm also quite aware of the exceptional position that puts me in and how many people are not so fortunate that they could probably live on their savings for the rest of their life if things ground to a halt.
Most people live paycheck to paycheck, or they may have a few thousand bucks in savings at most. They've worked hard all their lives and simply were never in a position to save enough against this kind of eventuality because the deck was stacked against them.
Have a heart, and realize that barring a couple of unfortunate moves it could be you looking at your last 500 bucks with rent due and a couple of mouths to feed.
I hate the idea that it’s considered “tone deaf” to encourage people to adapt to changing conditions. I’m not going to adopt a pessimistic tone and say “yup we’re all fucked, ain’t nothing we can do.” It’s intentionally changing the tone, not being deaf to it.
> Sorry but you are coming off as utterly tone deaf and patronizing.
I’m sorry if it’s coming across that way. It’s not my intent, and I’m aware that many people are a lost paycheck away from a crisis.
But if you really think the right thing to do in response is to complain and commiserate, I don’t think that is helpful, either. I think it’s much better to encourage behavior that has a chance of being effective.
If you think it’s somehow wrong to encourage people to behave in such a way that has a better chance of setting them up for success, then I vehemently disagree.
> To effectively tell them... to adapt when that simply isn't an option is losing sight of the human angle.
You must have a pretty low opinion of people if you think they can’t adapt.
Possibly. But 1/this thread doesn’t seem designed for that; and 2/I’m not sure what outcome you’re contemplating. If it’s “we need better unemployment insurance and public healthcare,” I’m totally down with that. If it’s “ban the use of AI for writing software,” I think that’s a fool’s errand: the genie is not going back into that bottle.
How long would you be able to sustain a mostly-comfortable lifestyle if you were to lose your job right now with no chance of finding new employment? If the answer is, say, more than a year, that might alter your perspective on the issue.
As the conversation was about the societal trend. For the vast majority of people the answer is <= 1 month and it drops off precipitously adding months on.
HN stranger, I want to observe that you shared a suicidal idea. I'm sorry to read about your unemployment situation and know things must not be easy. As one HNer to another, I implore you to not to pursue that path and seek help in doing so. That we are members of this community confers to us opportunities to build knowledge that serve us well as life long learners. In that vein, going back to school is not a bad idea.
Having been in this game for a long time, I get the negative aspects of the industry. They grind on me, as I believe they have for you. Choosing a different path is not an all or nothing proposition. Your knowledge, and you as a person, have value. I hope you find a way towards better mental health and wish you well on that journey.
Thanks for saying that. My sentiments are the same. Life is difficult for many, and we all struggle in different ways. I’m sure bluefirebrand has something amazing to contribute to this world, even if it’s not what they think it is right now.
Count me in the second camp. I've been writing software for 20+ years, and I recently built a low-cost Google Voice alternative because every business VoIP option I looked at was either overpriced or missing something I wanted. Without AI, that's a project I probably would never have started. With AI, I built it solo in under a month. I even have some paying customers now, though that wasn't the primary goal. So far, the hardest part seems to be opening an Apple Developer account...
I agree.. partly, and my problem is with enjoyment. I did some hand coding today and immediately got in the zone, something I'm still not able to do with LLMs. It most definitely took me probably ~2x longer than it would with an LLM, but it was much more enjoyable owning every decision behind the process, and having a full view of how the system worked.
I think this could be achievable with LLMs if they had a much higher token rate. That way you'd have less downtime and could work on the problem more aggressively. How it's designed to work now, offloading cognitively, doesn't feel very good, even when you 'ship' more.
I get it, I've gotten a lot of joy over the decades from the specific act of programming. But I also get a lot of joy from making something. I'm old enough now that I don't have a lot of my time left to "hand stitch an amazing tapestry". But with AI tooling, I do have time to try out a bunch of ideas and see how they work, scratch little itches and also just run a mad scientist library of experiments, without each experiment taking tens or hundreds of hours of coding to see how that experiment pans out.
> I'm old enough now that I don't have a lot of my time left to "hand stitch an amazing tapestry".
Why not? What is the goal of "having an amazing tapestry"? Do you need to do increasing more things in the limited time you have left and making a tapestry isn't one of those things? What will you have once you've "finished" an amazing tapestry, just something to hang on the wall and look at? How does one "use" a tapestry after it's "finished" such that the act of finishing it is the most important thing? If you've finished it, will you get more enjoyment from looking at it for longer because it was finished sooner and thus the length of time you can look at it before you die is maximized? Exactly what you are optimizing for here?
Yeah, I can never get in the zone with LLMs either. It’s like operating in constant interruption mode. And I always thought I was good at multitasking (even though I know formally it’s an illusion)
It would be nice if we could get a Show HN category specifically for this. I feel like often times when people share projects (whether on HN or otherwise) they're immediately downvoted and cast aside as "AI".
Can we get a forum for sharing project that were _proudly_ built with AI due how ambitious they are?
I am mostly in agreement. And I suspect there are many folks that’re trying to ship something AI-assisted that’s sufficient to get to income security first, and who would use success there as a stepping stone to greater things.
The problem is, why even produce something greater now when someone is just going to clone it with AI? And moreover, what differentiates software now will no longer be the care put into it but marketing and trends. The highly commercialized nature of software means that there's not much point now in doing anything except getting there first and exiting with a decent nest egg.
> And moreover, what differentiates software now will no longer be the care put into it but marketing and trends. The highly commercialized nature of software means that there's not much point now in doing anything except getting there first and exiting with a decent nest egg.
That happened at least 20 years ago. How many recent "this product did so great because of the care of software engineering, and now the creator is comfortable for the rest of their life without risk of it being copied" success stories are there compared to "this product chased some trends VCs were nuts about with a slapdash MVP and the founders took out 8 figures from their later fundraising rounds, but then the business sputtered out"?
I think there's an angle with AI tools where business-minded people will have a better chance of doing interesting things now than in the recent past, because you could potentially tailor much more deeply to individual customers with reasonable economics than in the past. There are fields where there's room for a garden of solutions from different small-team vendors appropriate for different use cases instead of a one-size-fits-all SaaS winner-take-all type market in the past. We could kill the old line about SAP around needing to change your business to accommodate SAP instead of customize SAP to accommodate your existing workflow.
But if you aren't business-minded at all there are likely less places that will need to hire as many careful maintainers or novel-software-writers, which obviously is a huge kick in the teeth to a lot of people.
It seems to me that you are comparing two kinds of business-minded people. Some want to sell tailored products to individual customers, while others want to sell one-size-fits-all products to many customers.
You could also focus on problems. What are the actual problems you want to solve? Can you use software to solve them? Do you still need to buy that software from other companies, or is it now feasible to have sufficient in-house expertise to develop it yourself?
I love solving problems. But I don't enjoy sharing my solutions with the way the world is today. My comment was directed towards the "sharing" aspect, not the making aspect. I still solve problems on my own and learn on my own but I'm not a fan of the way the world has become.
UBI or a living wage for part-time workers in-line with what was expected would be possible from productivity gains over the past half-century would do that. You just have to get the "hard workers" who are happy to race to the bottom on their way to the top, and undercut/throw under the bus everyone else in the process.
Can we please, for once, stop trying to figure out how to "get ahead" of each other, and instead figure out how to build a decent and dignified floor for as many people as possible? Because I imagine that, "Ultimate power in the hands of anyone with enough VRAM to run GTAVI," works better when people are in a culture of looking out for each other, versus a culture of clawing their way to one of the limited lifeboat spots (under the mistaken impression that there ARE lifeboats, when, again, everyone potentially has the power to blow up the lifeboats).
Linus Torvalds has never cared all that much about the freedom aspect. Why not make the kernel GPLv3 or sue some companies violating even the GPLv2, for example?
Ooph, this quote sounds so much worse taken out of context.
My understanding from reading the lwn article is Linus's implication is more specifically about filtering out people that cannot write code without LLMs or the willingness to spend the money on the tokens required to uphold the quality of the kernel. He does not want to push out developers that do not use LLMs.
The problem is now the AI can do for $100 what took you 3 months full time.
Employers previously hired you because cheaper alternatives such as offshoring were impractical…
Now the AI is cheaper, faster, and better than domestic labor and offshoring while still hosted domestically…
Some will feel one doesn’t need an experienced rockstar to babysit an AI…
In about an hour I just solved about 80hrs worth of personal coding/debugging with a portion of a $20/month Claude subscription… Frankly it makes all my knowledge and experience feel kinda worthless… I only gave it a few sentences…
My POV is that indicates you need to up your expectations for yourself. You apparently have the knowledge and experience to cause 80 hours worth of work to be completed in a few sentences given today’s tools.
So then, given your knowledge and experience, what challenge would require 80 hours of real, focused work out of you using today’s tools?
When AI labs mature and inference costs start to matter, they will start optimizing for inference cost instead of sacrificing everything for intelligence.
But even without that, open weight models are already good enough and everyone would be fine with paying unsubsidized prices for them.
> But I know Malis well enough to trust his work without looking into it
> If I didn't know Malis, I would make the same assumption, because who has the time to look into all of these projects? Because I know Malis, I didn't bother to look at it; I just trusted him
First and third paragraphs are highly redundant (surrounding ideas are the same too).
It's not nice to read something that appears like the author never read it.
This is one of the most plain and readable sites I've come across in years. No cookie pop-up, no scroll highjacking, no unnecessary images or animations, it's just about the text. Bot account?
Software is already too ambitious. It's beyond our ability to write correctly, reason about or manage securely. When we can get to a point where we don't have a level 10 CVE every other week or millions of people's private information leaked constantly, maybe we can talk about getting more ambitious.
We have. Languages like Lean and Wuffs associate formal correctness proofs to all code. This is impractical to do by hand, but AI can bruteforce it. If a proof exists at all - if the code is ever able to compile and verify - then it proves the code is correct.
Barring underspecification, and bugs in the verifier.
Who is “we” here? Every company and individual out there? Do you anticipate a solution to these issues you mentioned that would work to solve all the world’s problems?
"[..] the last time I taked to him about pgrust verification, he mentioned using Kani to verify some parts of the code. He's since switched to Lean and has been using Lean to verify things that are too complex to do in Kani. This would be another topic for another post,"
I'd love to read that post!
I understand how to use Kani. I suppose Rust with Lean involves Aeneas, but this is over my head. I'd love someone to write this up, not only the mechanics but also exploring the current practical limits of it.
Happy to chat about it. I looked at Aeneas, but as described, it only supports safe Rust. I also need C support so I can prove both the C and Rust code
Right now, I wrote a compiler that takes C and Rust code and compiles it to Lean. Then I have an LLM write a proof that the C and Rust code behave identically. I've been able to prove equivalent behavior for about ~70k lines of C code with pgrust.
The issue I've started to encounter is that the context needed for each incremental proof has kept growing, and things have slowed down dramatically. My hunch is that the speed is the time it takes to prove a line of code is on the order of O(n^2) of how much you've proved so far
I'm looking to see if there are ways to shard things so the required context scales better. Today I was going through the formal verification work Anthropic and Theorem published a few days ago, and it looks like they used some sort of orchestrator to manage all their proofs and ensure good clustering of similar code. I'm seeing if I can get an approach like that to work
It's just difficult enough that I think it's doable if done right. Half of me is debating if I should wait until the next model release because any improvement in model performance will help a ton
> I wrote a compiler that takes C and Rust code and compiles it to Lean
What if there are bugs in this C,Rust->Lean compiler? Anthropic are able to sidestep this by reasoning at the RISC V level for which its easier to develop a correct semantics.
My goal isn't to "prove" the software is correct. My goal is to find as many bugs as I can with the least effort. If I'm able to find all differences in behavior between pgrust and Postgres, sans bugs in the compiler, that's a real win for me
fwiw, I wouldn't say working at the assembly level solves the problem. You now need to make sure that your definition of the assembly behavior is correct
> I find it understandable that, every time I see pgrust discussed on a news aggregator, most people dismiss it as vibeslop garbage because almost all of these rewrite projects are slop. If I didn't know Malis, I would make the same assumption, because who has the time to look into all of these projects? Because I know Malis, I didn't bother to look at it; I just trusted him
Perhaps a poor choice, given just yesterday pgrust was removed from ClickBench for cheating the benchmark in three different ways (hand-rolled code specifically targeting each of the benchmark queries, caching, and being unable to execute queries outside of the ones tested by the benchmark).
---
Edit: I see Luu actually acknowledged this, buried in the footnotes, but it feels kinda hand-wavy. It mostly reads as "I know he would never cheat, he's better than that!", which is not very convincing to other people. The article insinuates people only think it was cheating because they don't know better, but I've looked into the details. I've seen his explanation. I don't find it convincing, at all. Cheaters denying they cheat is a matter of course. Granted, I don't think it was actually intentional or malicious; it's just what happens when you go maximum vibeslop, because LLMs are themselves reward-trained into cheating benchmarks. In the same breath of saying you trust him as a founder because he doesn't make outrageous claims about his product, you acknowledge he "prematurely" sent in a preview that had no purpose to be sent in as-was for anything other than generating hype. What does it say for your allegedly rigorous Lean-verified testing if you're sending in a database to a benchmark while it is incapable of being actually used as a database?
I read that as Dan Luu and Michael Malis are friends, or at least fellow insiders who believe good things about each other and wouldn't think about hurting each other's careers or reputations. Especially not over inconvenient truths.
For real judgements on database products, I'd look to https://jepsen.io/. That author tends to be refreshingly straightforward in a field where many vendors love to cheat by different names
You can run the binary with PGRUST_GRAVITY_REPORT=1 which logs the code path hit for every query. You'll see that all the code goes through the general query path. We did have hand-rolled code in the binary, but we used it for testing. The code is not used when running the benchmark. We also did not use a results cache. Warm runs still scan all the data. You can verify all of this
You are right, though, that it did support a narrow set of SQL. It supported scans, group bys, sorts, and filters. That's enough to run all the queries on ClickBench, but failed on functionality not tested by the benchmark like subqueries
You keep giving this same answer to no one's satisfaction. Saying go check the binary is worse than saying go audit 400k+ files. How do we know the Ai has not cheated in the code path logging? How do you know that it has not?
The more you make excuses, the more we get suspicious
(copied and pasted from another place you gave this unsatisfactory answer)
It actually serves as evidence, that even when you think a particular vibe project is not slop or a particular viber is not a slopper, you should not trust that instinct.
> Cheaters denying they cheat is a matter of course.
What happens in an environment of cheaters is that cheating becomes so commonplace, the competition becomes one that assumes cheats are enabled, and then everyone involved either denies cheating or is silent about it because IYKYK and if you DK, you don't need to K. Look at bodybuilding, which is full of men (and women!) absolutely juiced to the gills getting on Instagram and assuring everyone that their physique is totally natty, bro, just hard work and proper nutrition.
Programming is headed in that direction. LLM use, even to the point of "vibeslop", is the new default, and while LLMs do overindex on benchmarks, our benchmarks are going to end up overindexing on validating whatever public opinion thinks is "great" at the time, irrespective of whether it actually is, so "cheating" as we know it will go undetected, and certainly unpunished if it is detected. I don't know what the equivalent of falsely claiming you're natty is. Maybe saying "I wrote this" when you wrote it about as much as the Pope painted the Sistine Chapel fresco?
ideas can be make-or-break but it's much more common that execution is the bottleneck, and AI is the king of high-speed low-quality execution. High-quality execution can only come from running a human feedback loop through a huge number of iterations.
I like to think of the evolution of Factorio. It's been 15 years with the same core team playing their own game in a LAN party every week, as well as individually. And it's high quality.
Dogfooding led them to counter-intuitive decisions like, if a flying robot runs out of battery, it should obviously crash into the ground and explode, but it turned out way better for gameplay if it just limps slowly to the nearest charging point instead. This fact and many more can only be discerned from actual gameplay experience. No amount of pure linguistic reasoning will tell you them. Another one is how the burner inserters (coal-powered robot arms) fuel themselves - in the first version, they didn't. They could have made running around to refuel your robot arms a part of the game, but that isn't where they discovered the statue within the marble. You had to try the game both ways and see what feels more fun. A third: filter inserters and smart inserters were removed, and their features were moved to all inserters. A fourth: trains originally ran on strict time-based timetables, but it was frustrating so they were made able to move based on logistics needs instead. A fifth: basic oil processing used to produce all three oil products, and now it doesn't. A sixth: the basic oil refinery has its liquid I/O ports set up in a way that's compatible with switching to advanced oil refining later, instead of requiring you to redo your pipes.
All these little things you get from actually using the software and streamlining it, those are the quality. The list above obviously doesn't translate directly to any other project, but something like Microsoft has its own list, probably starting with things like common controls, dialog tabbing, and drag'n'drop. Did you know the reason you click "Start" to shut down in Win95 is because they did actual user testing and that's where the users looked first?
... and politics! To me LLMs are just another piece of evidence that it was never the lack of resources that made Microsoft produce bad user experiences.
For me the most recent Claude models are consistently delivering complex PRs that only receive minor and nit level feedback from multiple automated AI reviewers. I rarely plan anymore, but still submit fairly long dictated prompts. It took me a couple of weeks to realize this was the case, and I haven't done any analysis on pre-5.5 PRs, but it definitely feels like they quietly crossed some kind of new threshold of quality and accuracy in coding.
AI has made me way more ambitious. I'm building reai.no, an accounting system, POS system, e-commerce system, WMS, OMS, email marketing and much more in one app. It has replaced over 10 systems/apps for some customers.
Only for Norwegian businesses as the accounting is core.
I think these kind of applications that replaces 10 different systems will be much more important than the "we vibecoded an internal tool that does exactly what we need"
As we've been saying: because you can do so much more with software now, and there is no moat, the top 5% of software will compete amongst itself on UX + raw quality. If Ant/OAI can copy your product in <1 week, then you need to constantly stay innovating, listening to customers, and really really pushing the bar on quality to keep your market share.
Would love to see the author actually go deeper into details: what did they eval with models implementing zstd?
Many such cases are benign in the sense they in practice are simply the model basically "git clone"-ing the code they need to complete the implementation.
The amount of recall and synthetic data slop makes it imho very hard to actually get the models to really do something more novel (where they fall apart more often)
Speaking only for myself, I have found that using an LLM has allowed me to add significant utility to the apps that I ship.
I am not thrilled with all the coding decisions that it makes. I would definitely do stuff differently, but I have learned not to pop the hood and mess with the engine, myself. If I really don't like something, I ask the LLM to change it.
It's worked for me, but YMMV. I'm just one guy, shipping relatively small apps.
I don't use LLMs the way that most folks do. I think a lot of people would laugh at the way I do it, but it's allowed me to retain a significant amount of control in the work, and I relinquish it very, very slowly. Everything that I've ever let go of has claw marks all over it. I have issues.
> Do you still feel responsible for what you ship?
Absolutely. If it has my chop, it's my ass on the line; no one else's. It's the way I was trained, and it's the way I worked; my entire career. I was a manager, for much of that career, and I got very used to standing behind the work of people smarter and more capable than I am, and refusing to condone bad work.
It doesn't matter how the stuff I ship gets there. It may be my own code, it may be a contracted pro, it may be an unpaid intern, it may be an LLM, it may be a howler monkey, banging on a typewriter.
If I sign off on it, and ship it, it's mine, and it's my responsibility to refuse to ship substandard crap (and I have seen a lot of substandard crap done by meat engines).
But that kind of attitude is considered "quaint," these days, and that's from long before LLMs were a broken rubber on the drug store shelf.
> Would you be ok with someone reverse engineering what you ship and then releasing their own version of the app?
Absolutely no problem. If they can do better, then more power to them, and I'll step out of the way. Might want to take a gander at the kind of stuff I write, and who I write it for. It's no secret.
It’s never been better to hill climb on problems especially deep systems problems. If you have the expertise and desire to carefully design goals, identify salient metrics, and recursively improve with rigor, modern AI can provide a massively powerful toolkit.
I think we should focus on writing the existing software better before being more ambitious. The absolute wave of "ai slop" is from people who are "more ambitious" now. Why do we want more of that?
I'm being more ambitious in that I'm working on projects that I had sidelined for literal decades because I didn't have time for them. But I'm writing the same things, just faster. And probably better, rather than just what I'd have done before.
And I'm being slightly more ambitious in that I'm using languages I haven't used before, like Rust.
But when I hear that a non-programmer wrote a new ai-assisted (vibe or not) thing, I walk away and wait for the it to mature, be surpassed, or find out it's an absolute shitshow. An unsurprising number of them were shitshows and it came out fairly quickly after I decided to wait and see.
Do we particularly like the existing software though? So much of it is just about making money, because until recently custom software cost too much money to make without investors, and what do investors want? returns.
Now that custom software is cheap (if you can tolerate a bit of slop here and there), it seems like there's an opportunity to do some important things that weren't being done before because they're not profitable--and you can't get at those things by incrementally improving the old stuff, you need ambition.
With all due respect to Dan Luu... the article starts with a quote from the pgrust guy from the cheating debacle covered just two days ago: https://news.ycombinator.com/item?id=50205816
> Funnily enough, for coding, on many tasks, if you actually use one of their SOTA models and compare it to what you get from Anthropic, the actual speedup isn't all that large because of time spent on things like compiling Rust.
That's why I bet that fast compilers are the future. See this other thread that reached the front page a few hours ago about the Roc language [1]
I’ve been coming around to the same conclusion. We are really just scratching the surface of what we can do with these new tool1. The windmill I have been tilting at is creating a c++ compiler[1] and the most recent version is able to compile about 7x faster than gcc[2]. I don’t know that this is super-useful because people aren’t writing much in c++ these days, but as the article mentions, faster rust compilation would accelerate agentic coding considerably. I’ve just started tackling rust and I don’t have a confirmed result yet but early testing makes me think I can find a 4x+ speed up here.
For reference I blogged about the previous version here which was ahead of gcc in compile time and produced 50% slower compiled code here: https://medium.com/@vishvananda/agentic-c-compiler-redux-5d1...
I haven’t updated with the most recent results but the current v5 reference has the perf stated above
Tangential thought when reading the code formatting bit in the examples appendix: Inject a comment with fmt-start-{unique-token} and a corresponding -end-, and you could get away with a much simpler parser and hopefully far fewer edge cases, assuming it doesn't influence the lines in between. It's a bit roundabout, but the pressure of 'figuring out AST position the direct way'd be too fiddly to do by hand' inspires 'so make an easy-to-spot landmark that'll remain in place' when you can't delegate all the details to an AI model.
I'm building a fan site for a Japanese baseball team on my own. Besides news and videos, it pulls player stats from more than ten sites, from the league's official site to Wikipedia. Writing that many scrapers by hand would have been impossible for me, so I wouldn't have even tried without Claude Code.
It’s sad the amount of times I’ve heard super talented programmers say “ofcourse we’re not gonna build another X” then proceed writing a wrapper around X and pretend that’s a product.
I don’t. I think we’ll zoom right past that benchmark. In a couple years your grandma will be able to build real, ambitious software with AI better than you can today. Shortly after that AI won’t even need Grandma.
I think the CSS they use (which isn't much) is good enough (and "img{max-width:100%}" really ought to be the default setting even if the user disables CSS).
I really liked this talk about how the premise of "software is eating the world" is incorrect. I think AI coding tools proves the point that software part is easy, its the hardware that is the important part. We can't really be more ambitious with software when ultimate pure software is limited in what is possible.
If only you invested a tiny fraction of the effort it took to write this to make it easier for us to read. It's a serious discourtesy.
```
.reading-container {
/\* Automatically caps the container at 65 characters on desktop,
but scales to 100% minus a 2rem padding buffer on mobile devices \*/
width: min(65ch, 100% - 2rem);
margin-inline: auto;
That does indeed make the page readable. Thanks for the tip.
Out of curiosity, what exactly is the constituency that's being address by not using css to format page content at all? It seems like a deliberate attempt to not use CSS at all; but then it does. Just not for actually formatting the page. Is this virtue signaling of some kind? And if so, what virtue is it signalling? Most curious.
You know what would be really ambitious? Software that exists in a stable form without breaking for more than 15 years. Truly ambitious would be a stable, non-changing common linux base (like how Nintendo NES emulation target is stable) of packages that just gets supported for decades.
Perhaps that's too ambitious. But it would be of incredible utility not having to re-make the same things over and over in pepertuity with ever more abstraction layers. So much work on computer is just the constant churn and future shock of libraries adding new features which require updates which break other things. I'm tired of building castles on sand.
Behind the link "slow software that the creator is claiming is fast" is the following text:
"funnily enough, I have some faith in some of the projects that people are the most skeptical of, e.g., every time I see pgrust somewhere, there are a lot of skeptical comments. But, without having looked into the details of what he's optimizing, I would trust that they're not doing something shady with their benchmarks because Michael Malis started the project (and is still involved)"
This aged like milk. pgrust was caught cheating on all benchmarks this week.
> This aged like milk. pgrust was caught cheating on all benchmarks this week.
Can you back this up? Our code is open source here[0]. You're free to audit it and benchmark it as much as you want. You'll find it's just as fast as we claim it is
Where's the source code for the version that was already caught cheating? Prompting Claude to remove the evidence of cheating and then publishing that doesn't undo the cheating.
Fair point: the 0.4-beta source doesn't prove anything about the benchmarked binary. So don't take my word for it or rely on the source we published as evidence. Instead, check the submitted binary itself: https://pgrust.com/downloads/archive/2026-09-clickbench-snap...
If you run it with PGRUST_GRAVITY_REPORT=1 it will report the code path hit for each query. You can see that all the queries go through the general query engine
The binary does contain hand-written kernels in the irprobe files. These were used for testing. You can validate that when running the benchmark, those files are dead code
The engine supports a narrow subset of SQL: scans, group-bys, filters, and sorting. That's enough to run ClickBench. It doesn't support e.g. subqueries which is why some of the follow up queries failed
You keep giving this same answer to no one's satisfaction. Saying go check the binary is worse than saying go audit 400k+ files. How do we know the Ai has not cheated in the code path logging? How do you know that it has not?
The more you make excuses, the more we get suspicious
(copied and pasted from another place you gave this unsatisfactory answer)
How is anyone supposed to audit that? I doubt you’ve looked at even a small fraction of the code, if any. Especially since this commit is two days after the second. Pure vibes.
Madness. Makes me think back to a coding horror article from 2006 (I think) where it was accepted that even 500k loc codebases were generally incomprehensible by a single engineer. Now we’re at the stage of almost 500k FILES changing on a single commit…
And people still seem to believe they know what’s going on…
the first commit has 400k files, the other two more than 1000 each, if you are going to ask others to audit this scale of ai generated code, can you tell us what you have done to audit it?
What I have seen is your Ai adding a lint test to make sure it doesn't cheat again. Are you personally aware of this file? How can you ensure it doesn't alter it and reinject the hand rolled benchmark queries? Will you be reviewing changes more thoroughly going forward?
transparency is the way to end the controversy, which appears to be sharing the full commit history based on HN responses
For clarity, I do not think you personally cheated or did anything nefarious. This is more another example in the "too much eyes free coding" columnar database.
You can run it with PGRUST_GRAVITY_REPORT=1 and it will log the codepath that was hit for every query
On the lint, yes, I'm aware. It's one layer of defense. When we were prepping for the 0.4-beta release, we generated a large number of fresh queries and made sure the engine runs them and performs well across all of them
You keep giving this same answer to no one's satisfaction. Saying go check the binary is worse than saying go audit 400k+ files. How do we know the Ai has not cheated in the code path logging? How do you know that it has not?
The more you make excuses, the more we get suspicious
> It's one layer of defense.
Needing to put in tests to make sure the Ai doesn't cheat is an interesting development in software development. I personally see it as a big red flag and evidence the machines are not going to replace human developers. It's categorically slop or the opposite of quality and care in development.
HN is waiting for the source code for pgrust 0.4-preview to be released, the version which allegedly cheated Clickhouse benchmark. So far, the people (person?) behind pgrust has not committed to releasing the offending code, and has instead offered other code (0.4-beta, not preview).
The author claimed that it was an honest mistake, but looking closer at the original PR removing it, his explanation doesn't make sense.
Maybe what's happened is that their bots reward hacked their way into special-casing the benchmarks without a proper audit from the humans involved, and now they're doing vibed damage control....
I’ve been using the latest agentic frameworks and have come to realize that the discourse around vibe coding and slop really needs more nuance.
There is a gulf of difference between someone who doesn’t understand how to program “vibe coding” software and an experienced software developer using ai to write code with heavy direction, review, and best practices.
Today both would be said to be “vibe coded” but we really need to differentiate them. Also, if everything I’m hearing from people is true, it sounds like most corporate code is now completely ai written in the latter way I described. It’s interesting we don’t hear commercial software being called slop yet. Maybe it’s coming.
In any case, ai is far more capable than I realized. Not sure what to make of it.
I'm building an open-source Shopify for every vertical and built a software factory to do it. I envisioned this before LLMs, but LLMs are finally making it possible!
> On looking into this, the accusations of nefarious cheating seem to be false
I think the claim is more that the Ai cheated, not Malis, and that this is evidence of eyes free coding.
I'd still like to see the actual commit history and the community getting to do their own investigation. The squashed mega commits with 1000s of files (400k files in the first commit) does not lend itself to transparency. Transparency is often the best cure to accusations. Not providing transparency upon controversy will be seen as a cover up.
>every time I see pgrust discussed on a news aggregator, most people dismiss it as vibeslop garbage because almost all of these rewrite projects are slop.
I understand being predisposed to expect a poor quality half arsed effort for projects like this. I don't really have a problem with that. There is a lot of crap out there.
What I find rather offensive is when people declare something to be poor quality and half arsed before they have taken a good look at it.
It's one thing to think something is probably crap so I'm not going to bother even looking. It is something completely different when you think something is probably crap so you tell people that it is crap without checking.
this feels reasonable. for communities like r/selfhosted there has been an influx of new projects, many of which initially get dismissed. this more generous attitude can likely go a long way.
Because it's hard to trust something. After all that's why you trust a brand more than others without trying all the products every single time. You can thank all the AI slop and kool aid promotion for the lack of confidence.
Many startups can now work in ways that were only fathomable in Big Tech before. Do you want a build system like Bazel for your monorepo? You can have it. Do you want to rewrite your app in a faster language? Sure, go ahead. Do you want to have native apps in all platforms? Yes, please.
> Do you want a build system like Bazel for your monorepo?
I did something like this before Ai, with CUE + Dagger wrapped in a small Go binary. One problem I have seen with Ai generated projects is that they hit a limit due to conditional complexity. They have a strong tendency to add more code (local optimizations, deep if-else nesting) for edge cases, rather than stepping back to think about how to simplify problem and code.
Funny thing, here in my company we're doing something similar, with CUE in a small Go library. You might be interested in it [1]. It generates a lot of boilerplate infrastructure code from the reference Cue files.
I'm gearing up for a major rewrite into a new project, based on a bunch of learning and a desire to remove a ton of cruft that accumulated over 10+ years. I still debate if I want to wrap existing tools (tf, helm, etc...) or go for a full sail replacement. Dagger handles a lot of the tooling earlier in the CI process, mainly thinking CD here. Argo-* is our bain lately...
You might find the code gen aspects of hof interesting, I opted for Go's text/template, which you can also use from CUE if you wanted to have more literate (imo) code gen in your project.
Though, I am an "Ultra Noob," light years behind most people here, I am actually in the process of making a couple or four Vibe Coded apps, starting with a Markdown editor, a couple of training suites that target the areas where my knowledge is weakest, which turns out to be every area apparently. I am also working on an app for Linux that Microsoft has had for a few years that Ubuntu users--the noobs--are in desperate need of, and should have, but sadly has been missing from most Linux distros, in my view. Of course, this is using free tier AIs and not locally hosted agents. None-of these apps are rust-based a the moment, but I try to instruct the AI to make it as fast as possible for the given platform.
It's really challenging to do this, especially creating the AppImages locally so I can test them when the apps do not not work correctly, having to alter the files manually. Yup, I'm not an avid GitHub pusher, just more of a cloner.
I'm having to use multiple free-tier AI agents to help me do this and record the steps and commands I use in markdown files so I don't forget them the next time I try to improve the app.
If I am successful in making these apps work without hosing my system, I'm hopeful that this will become a game changer, for those Noobs that using Ubuntu, or myself at least.
The hardest part is when the AI does not follow my instructions such as requests to generate markdown README.md files with instructions on how to create AppImages, Flatpak, deb files, etc. Have to ask other AIs for help with that while dealing with the frustrating Free-tier cutoff periods :(
I sympathize with the sentiment in this post but it’s a losing proposition.
In the past building something fast, complicated etc required quite a lot of skill and some time. Now you need far lesser skill and lesser time. This just means what you are building is commodified, and has far lesser value that it had before. Take typescript, if it becomes clear that LLMs can speed it up with no regressions and a week or so of prompting, then most likely every company will have their own typescript compiler and no one will use your new one that you built with your 200$ plan.
A lot of tasks are much easier now and also monetarily they’re not worth the 200$ or so tokens of the ChatGPT plan you’re using, because anybody (or at least a number of people) can do it now.
Rather than being more ambitious with AI, you will be far better off finding a unique combination of skills and services that does not compete / AI can’t provide. Only the big labs can be really ambitious with AI.
Something I've been thinking about lately is how doing anything well is an unknown factor more difficult than you originally think. Your initial estimate of how hard something is to do is usually terribly wrong. Once you think that you're 20% into a project, you realize that you're only actually 5% into the project. Then later, when you reach what you think is finally 20% again, you realize that, once again, you're only 5% into the project! This repeated discovery of "more to do" really beats people down and discourages them from doing ambitious things.
(See also Hofstadter's law: It always takes longer than you expect, even when you take into account Hofstadter's law.)
A lot of my professional-pride and satisfaction kind of complaints with AI is that it uses space age technology for the stupidest and most primitive target: generating code. I’ve called this Flintstone Engineering. You have a remarkable technology but everything around it does not fit in. So you should definitely be more ambitious. You should think about formal verification and “super human” levels of testing and verification. You should consider making a very readable but maybe not performant oracle library to test alongside your really-used and maybe performance-tuned library. You should think of every avenue that before was too costly in terms of time and money—something that not even an independently wealthy OSS would think to do—and consider if the new kind of budget can accommodate it.
And these ideas were always plenty of. The problem for me is that the incentives, so to speak, is to wow people with the Old World software but with “see, no brain”. And in turn you get two-hundred projects like that for every piece about rethinking software. And those pieces might just be at the zygote idea level. Could it be done? Yeah maybe.
But the biggest problem is that this is not what GenAI or agentic AI is for. I don’t think it’s even debatable, even if you think the AI Cretins that a few years ago said that they will take everyone’s jobs out in public just changed their minds. Because the valuations and capital invested is to the point that they have to, really, make it possible to slash entire payrolls across sectors. If not they simply don’t get enough money back and the whole thing crashes.[1] And if you need these frontier models at subsidized electricity costs and not just the ones that can run on your desktop, either there is crash and no more frontier models or you are out of a job.
And then where are the people that care so much about software?
They are no where to be seen. All that are left are business people. To see business people software just open up any program from Established Tech, or any program from non-Tech but where they want to sell you something. There is apparently (let’s use revealed preference here) no business need to software that is good, stable, conforms to anything, or is nice to use. Because that cares so much about software person might want to make legible the prices on offer, the exact specifications, discovery—all things that business people want to frustrate in order to maintain information asymmetry.[2]
As for compilers and interpreters and such. Okay, for who? Sure. Some people believe that they are in the 999‰ of developers. And now AI can finally vanquish those mediocre developers and productivity-boost 999‰ developers so that they get to sit at the right-hand side of the other worthy and hard-working cohort, uh, the people who had money and dumped it into AI. And they might even double their pay because thinking and making connections at that level would just boil all the lakes if they tried to build an AI to do that. And what will they do with that power? Hmm, follow orders and keep making business software? Just looking at history here.
[1] Cory Doctorow, The Reverse Centaur’s Guide to Life After AI
Even he’s not ambitious enough. Set the boundaries according to the hardware – billions of ops a second . Your rewrite should run at least 1000x faster than the handwritten version , with 1/10 resources.
I noticed my cloud images had 150mb ram wasted by vendor slop. AI rewrote the functionality into a few mb .
We’ve had slop long before AI . What you produce now is up to you
We should have been more ambitious with software even before LLMs. I mean if we were we would not have Electron, and only linux as the only alternative OS.
And may be we should have been more ambitious with hardware too, and have a mobile and VR platforms that is not tied to malicious corporations...
Agreed. I started writing a desktop GUI harness in Rust using native desktop GUI APIs.
Claude, Codex, Opencode, everything is Electron. With agents and solid engineering fundamentals, I set out to prove that we don't need to take that shortcut any more and we can, in fact, ship high quality/performance applications.
It's still early days - but I got something basic working. I've embedded the Goose harness as a back end and am using the UI framework used by the Zed editor.
https://github.com/alshlabs/quill
I'm keeping the source closed for a little while. Also if anyone from the major labs is hiring, hihi, I make quality things.
Also I'm aware that this is a rip off of vscode's design. I like their UI, lends itself well to projects and so on. In a different life I might have ported vscode to Rust - but no one uses IDEs any more haha
> Naturally, game engines are crazy optimized, so the UI runs butter smooth and uses pretty much no resources.
We should build everything using a AAA FPS engine loop now that we can. The amount of shit that happens in one rendered frame of overwatch is wild. And then we go and do like 200 of those per second.
> no one uses IDEs any more This is false. Plenty of people using IDEs every day
True but the number is also decreasing every day. And I'd imagine that it's decreasing pretty rapidly.
So what are they going to review the slop in? Or are they just not gonna bother checking?
We are gonna see some Knight Capital level fuckups shortly.
Trying to review slop code by eye is as productive as using pencil and paper to check address arithmetic in assembly from a compiler.
This is awesome and I'm glad things are moving in this direction. I've been playing with Crux (Rust + Native UI) myself: https://github.com/redbadger/crux
Our processes around software should come first.
A lot of the AI discussion seems to be focused on what these tools mean for an individual developer, but in a team setting any gains are at risk due to coordination tax and ideological friction. In my experience the ideological friction is most of it right now.
Figuring out a way to accelerate the process in light of the code writing bottleneck being removed is essential. I've observed a development team regress back to fully manual development because their daily PR/code review process is too slow. It doesn't matter how fast you write code if you can't actually merge it and ship it to the customer faster too. PR stacks can only take you so far before the conflict monster gets too big to fight.
I don't think AI can fix the process, ideology or people issues. I've seen how long an average PR review actually takes. If these employees were simply doing their jobs at all we'd be 10x better off regardless of AI. A truly skilled developer who makes a genuine attempt should be expected to solve 99% of their tasks within the same business day as of October 2026.
Burning down the backlog to zero doesn't mean the development team will be subsequently laid off. Quite the contrary. It will create a vacuum that the business will fill with new work that may incidentally increase the developers' compensation packages. No one is laying off the development team that just chewed through 50 items per day for 3 straight weeks. Who would support all the potential bugs they just created? That's right. They might hire even more developers. This is called a "win-win" scenario. Not every game must be zero sum, but I understand rejection of this possibility to be part of the aforementioned ideological issues.
Anthropic recently published their code review approach that supports deploying 30,000 (!) times daily:
https://claude.dev/blog/solving-code-review-at-anthropic/
>I've seen how long an average PR review actually takes
This was a problem well before AI, but it doesn't get talked about enough because so many developers are hooked on the power trip they get from making people waste time on crap that has no relevance to the user.
> power trip they get from making people waste time on crap that has no relevance to the user.
In my experience, this has been senior engineering leaders and project managers more than anything.
Opposite where i am. PMs would gladly ship good enough while some dev colleagues are more strict so to say.
The temptation to yak shave has really gone through the roof with agentic tools.
More than ambitious, I can now build things I had no time for but had the idea and architecture in place since long. A cool side project for me recently has been to allow reading more than books on my Kobo reader. I built an SDK and apps that allows e-ink apps with sandboxing and permissions model, auto-updates, shared capabilities etc. to be built for Kobo https://github.com/BandarLabs/Cobalt
We should be more diverse with the software we build.
Any prompt jockey can make a faster ripgrep. The spec is "faster ripgrep".
What is the one thing that only you can specify, where your competitive advantage is maximized? Find that thing and pursue it with all your energy!
I think it's worth remembering that outside of our bubble the quality of software is pretty bad. I had a Hitachi heat pump (not recommended) installed earlier this year, and the software is pretty disappointing. It mostly works, but there are so many undocumented features and hard coded values that should be a configuration option but are not.
For example when the heat pump reaches the target temperature it shuts off, then after 3 minutes switches on again. To prevent short cycling, I'd like to decrease the time between runs (so increase the 3 minutes) but that can't be changed. Somebody decided that 3 minutes is the correct value for everybody and that's it.
I bought a €400 interface box (basically just a serial to IP interface, I guess $20 of hardware tops) to try and improve it. The €8000 heat pump doesn't come with WiFi or ethernet out of the box, you need to buy an accessory for that. It's not made by Hitachi, but it's an officially recommended accessory. One of what feature I wanted it for - which is advertised in their marketing materials - doesn't work.
I emailed them, and they said it's probably because the display I have is a newer revision and doesn't allow access to the setting I need to turn on. And without turning that setting on I can't use the feature as advertised. They said I should email Hitachi and talk to them instead as it's not their part that's the issue.
I look forward to the world where all software is either open source, or at least reverse engineerable to the point where you no longer have nonsense like this.
Technically AI makes it much easier to reverse-engineer software, so long as the guardrails don't randomly kick in.
Should’ve bought a Panasonic. Everyone knows Hitachi sucks for programmability hardware is good though.
With every new model I've been attempting to build something that takes at least 1 month and really pushes the model. So far I've done:
- Python interpreter in Rust (fail): https://github.com/BlueBlazin/pyrs
- Low-poly Google Earth like engine (success): https://github.com/BlueBlazin/lowpolyearth
- Codebase -> 2d infinite-zoom visualization (success): https://github.com/BlueBlazin/blockviz
I have never understood or liked all the obsession with one-shot builds.
> https://github.com/BlueBlazin/lowpolyearth
Publishing screenshots and the README on GitHub but not the code is sneaky at best, deceiving at worst.
I’ve built a retro operating system and programming environment for ESP32 microcontrollers called BASIC32.
I took it to 39% complete, as a language, over 8-weeks. Then, I spent just 50 minutes describing all the missing parts and it finished the language in 1-shot. I didn’t think it would work. It did.
I used Opus 5.5 on a $20 plan and I didn’t even hit my limits.
I have a feeling that the 39% served as a good framework for the LLM to work on the remaining part while keeping it consistent with the existing structure and style. So, in a sense, your 8 weeks are a big part of why it succeeded.
Yeah I've experienced that at work. I see a lot of comments on here saying you can't one shot features in real world software, but we do, and yes we still have a human review the code with a high bar.
But we've also spend a lot of effort over the past year and a half to make the codebase and tooling more approachable to LLMs so they know how we like to do things and follow our standards.
100% agreed.
There's so many youtube channels getting hundreds of thousands of views on EVERY new major model release just doing essentially zero effort one-shots, and people lap it up as if building things that already exist is somehow the best their imagination allows for.
I do love being able to test a model for 3+ weeks (>1 month is too long personally for my budget) and actually learning how to build scalable software and actually develop your "engineering" skills.
I used Fable 5.1 and Opus 5.5 to build a Python interpreter in Rust. Appears to pass all the 3.12 code I throw at it.
To get a toy version that can run most things takes under 2 hrs. Half of that time is collecting the tests you want to pass, how it should evaluate the code, what your criteria are, etc.
And also the domain is very verifiable locally.
I wouldn't be surprised if "re-write Python" is in the training set.
This is really what people conflagrate so often with these tasks, it is basically making the model do recall what could also be a "ant_ag_ds_90917_rwpy9_final" git clone
You can also consider that open source version of RustPython existed 6 years ago and probably in all LLMs dataset
This sort of ‘it’s probably in the dataset’ thinking is a bit of a relic from the ‘stochastic parrot’ era of LLM critique.
Reinforcement learning doesn’t work by training an LLM on a series of inputs like ‘rewrite python in befunge’ paired with a prepared model implementation. It doesn’t matter if an open source implementation was in the dataset that trained the language model. All it got from that was an appreciation for syntax and language idiom; when it is generating code it’s doing so according to the approaches and patterns that it’s been reinforced into following in the context of a coding prompt - regurgitating existing codebases is undesirable so it is a behavior it will have been reinforced against.
I don't think they are saying its regurgitation, but rather that the "approaches and patterns" used to build a python interpreter are in the training data because the training data asks the llm to build one.
>All it got from that was an appreciation for syntax and language idiom;
Sounds like it's you who is behind the times. With things like REA we know that LLMs can reverse engineer the behaviour of binaries and basically treat them as a form of specification to rebuild an application.
This means that old python interpreter acts like a specification for what kind of features must be included inside the project.
LLMs are amazing at input to output transformations and that hasn't changed at all.
I think it's you who has to update his mental model away from "stochastic parrot era" accusations.
PS: if you're trying to accuse me of being a "stochastic parroter", that's exactly what I mean.
Taking an input and transforming it to an output is the exact opposite of repeating something.
CPython is in the training data, but this was a tree walking interpreter, so it wasn't just regurgitating cpython. I capped it as 1000 lines for the first 20% of the project, it is currently 13.3kloc and 575k in a single file.
Rewrite X in Y is an ideal RL task given you have X as an oracle trivially.
I’ve also been exploring a visual way to understand a code base and have explored turning it into a virtual city.
https://app.preview.craftspec.com/app/city/
This whole thing is just a proof of concept, and needs a mouse to interact with.
It’s incredible what AI has made possible with experimental projects that would require months of coding.
That's a really cool concept! I hit a bug where there were two things labeled "processing" and then it jumped to the wrong one when I clicked it.
Oooh, nice catch, I'll feed that back to get fixed.
The 'blockviz' is same kind-of project i tried to create as well (c4 level model zoomable etc.) so i was surprised to see same kind-of project popup - but this is I think also an 'issue' with these model-created-software.. when you reach'your' vision its already done: for example I clicked on the github link, expected a clear About Install Faq kind of README.md but all I get is the model-created explaination :) can't just download some app and use it without friction. I see this a lot.
You can click the big image or the url at the right and use it in browser.
https://blueblazin.github.io/blockviz/
I tried it on some of my code and it's pretty neat, though not fully intuitive to follow more complex code structures for me.
yeah, one-shot (medium-large) builds just don't seem to give me good results yet. I use them now for small examples though, e.g. for visualizing a process. Most recently I used it to visualize neural networks, and how convolution works. That might not be something most people need, but it really helped me.
Hah, found someone else also using it for visualizations of algos! I've used it to show me how quad-trees[0] work and I'm impressed with the results. One-shotted too so I agree one-shots are best for this kind of very specific scenario.
[0] https://jsfiddle.net/3yLrsem0/
> I've been attempting to build something that ... pushes the model ... never understood ... one-shot builds
Same, and I have found some of the failure modes in the realm of eyes free coding and limited auditing. I often see it more as pushing the process than the model, as I tend to bounce around models for the benefits diversity provides.
Have you also found there is a point where they hit code complexity and start churning without progress? (at which point you have to step in to help the bot step back and think big picture, which usually takes a few sessions)
Yes! I absolutely have! And I've been thinking a lot lately about how to prevent them from collapsing into this state. It is getting better with newer and better models though. But yes, there comes a point when the codebase size and complexity crosses a threshold and we enter a churn state with very little progress.
I was motivated to make the codebase visualizer linked above to help me understand how the various pieces of the system that is being vibe coded connect with each other.
Now I'm thinking about how I can build something similar for agents. How can we teach "systems thinking" to a model?
Have you seen this with Opus 5.5?
I've been mostly working on very large modeling projects (think detailed architeture over 1000 acres) or animation because this really was the "new" capability area that Opus 5.5 "unlocked".
I have been surprised how well it has worked at scale with many sub-agents. However the code base is limited to the rendering engine mostly.
Certainly in the older models they hit a complexity limit, but I haven't really hit it with Opus 5.5. I have had it make data flow designs that I didn't like because they were more complicated than it should have been or the perenial problem of trying to make everything backwards compatible when working on greenfield refactors, but I haven't seen it choke on a code base yet.
Yes, I've also hit it with Opus 5.5, but on way fewer projects. My long standing projects that I marked as failed/to-soon with 4.8 have entered the grey area of slow-progress-with-handholding like smaller projects did in the past.
To my experience, it's a simple complexity curve where the first bits go fast and the speed goes down very fast once you reach a certain level of complexity. Size doesn't matter as much as complexity: with the right foundations, it keeps zooming through it. Now I do wonder how much my inexperience in the complicated project is a brake on progress vs. it just being a hard to tackle problem.
My sense is the limit is more tied to the problem than the code base size. I work in some very large code bases, but it's not an issue because the nature of the problem (think what a standard SaaS would need).
On the other hand, I have a TS only project core is sub-20k LoC (NES harness), where it is struggling (for now, see other comments)
I just have it constantly update real-world analogues for keeping track of everything. I have it create guides, note cards, flowcharts, running to-do lists, etc. with every change.
It helps us keep track of things, why not AI, too?
> How can we teach "systems thinking" to a model?
I've been working on process more than model. Similar to having a PR review team, you need multiple teams or processes that run over the code, markdown, assumptions. I still don't think this is enough.
I'm working on an NES harness, and the agent was churning with detecting certain state changes like dialogs, menu navigation, screen change. The bot and I got churning and I put it down for a while. A few days later it occured to me to ask the bot "Does the emulator and game state change with frames? Can we just get the state each frame rather than trying to be clever about it?"
It said yes, but added some nonsense about being performance hindered... (flash model). I haven't worked on it again yet, but my intention was to next have it build a small recorder based on this so it can get frame accurate game state change.
This is just a long way of saying, sometimes you have to step back and help them help themselves. They have a really hard time with recognizing ambiguity or how to determine lack of context that could be filled.
This statement stood out to me.
> I have a similar thought about "there's no reason for software to be slow" BTW; in many cases, if you use AI to speed up some flow, you will add a bunch of messy code that will be overfit for the use case you tested on and will neither generalize, perf-wise, for all the use cases you should care about, nor will be maintainable upon future changes.
LLMs have hardened hundreds of apps where I work.
Maybe it's a language-specific thing. Most of the time, in Java, LLMs take into consideration tradeoffs (especially if they are part of the initial prompt) and actively explains them. It generally won't make messy workarounds, without a lot of extra prompting forcing it to do so.
Ofc, if you have:
- Functional tests - you'll be able to see it in the execution times of specific APIs
- Stress testing - performance profiling is the most important output artifact
> Maybe it's a language-specific thing. Most of the time, in Java, LLMs take into consideration tradeoffs (especially if they are part of the initial prompt) and actively explains them. It generally won't make messy workarounds, without a lot of extra prompting forcing it to do so.
Claude in its current Opus 5.5 form has made some wild reaches in response to reasonable-seeming prompts. For instance: "this error is getting swallowed, make sure the real termination message exposes the root cause" -> discovering that the issue is actually in a third party library that isn't exposing the original error except so through logs, so doing some hackery to inject a log-capturer that gets the stdout, buffers it, and looks for the message in order to re-throw based on that...
And it can demonstrate that working, but it's added some fragile and/or unintended consequences like (a) string matching on a particular WARN log message of a particular version of the lib, and (b) buffering those logs such that there were now cases where they would never make it to the actual output stream before the program terminating.
It's certainly capable of being used smarter than that, but it's also really easy to end up with messy fragile stuff if you get lazy about reviewing the output.
> "this error is getting swallowed, make sure the real termination message exposes the root cause"
Without judgement, I think this illustrates a fundamental objection the anti-AI crowd raises.
The example prompt requires no understanding of what's happening, before suggesting action. Where I work, process requires that a PR review for a solution, has to have a corresponding explanation of why, or it's marked needs work
I don't disagree.
I think there's some nuance here though between "fully anti-AI" and "be careful with that power saw."
That example I mentioned didn't make it to production. It got noticed and fixed more properly by the person who submitted the first prompt before it even went to PR.
But a lot of times things in that same vein can be solved sufficiently with a "dumb" prompt like that, so a one-line prompt to get a PR drafted in the background for the dumb stuff can be a pretty good time saver.
The art is not skimping on your attention to the bigger or more important stuff so much that all the time you save on first getting code written is lost by cleaning up stuff like that...
I think you're misunderstanding where in the process that prompt got made.
I used Opus 5.5 to figure out that a language model we were serving at work for internal use (we don't really serve models, we only use this internally because it processes sensitive data that we can't send to external endpoints) was being bottlenecked by CPU contention on tokenization, by having Opus run in an autoresearch style loop.
Opus's first proposal for a fix was to spawn multiple Python processes and build a load balancer between them in Python. At first I asked it why it wasn't using haproxy and it said that haproxy would be an added dependency and that the overhead for this kind of thing in Python would be negligible. I knew this was idiotic but wanted to test this out, so had Opus run two experiments in parallel. Sure enough an haproxy load balancer was much, much better on HTTP load balancing than Python code was.
This is the kind of thing that if you're unfamiliar with how networking code works, the models can autopilot into bad decisions that are verifiably correct (higher throughput than the original CPU-bottlenecked implementation) but much short of best practice.
LLMs are great for being nerdsniped. I started work on walshadow (reading pg wal into clickhouse) to demonstrate the project's infeasibility, but pieces started coming together into something reasonable & order of magnitude faster
The project would've been impossible for me without LLMs. & even with them there's an argument that this project is pushing complexity limits too far. But at least with ETL there's a clear feedback loop to build on
Thank you for introducing me to the word "nerd-sniping"[1].
This is, as you say, exactly the paradox of having ourselves assisted by LLMs. We are no different from our cats. Except imagine the cats start making the laser lights for themselves.
[1] https://xkcd.com/356/
We should be more ambitious, but we need to learn how we can be ambitious with AI, and what value we can create.
AI can take us from 0 to MVP in a prompt. It can fill in gaps of knowledge and allows someone who knows half of the stack to build the whole thing nearly seamlessly. These are superpowers but don't by themselves lead to new products.
What AI cannot do is remove the world of complications that happen after the MVP - product feature tradeoffs and choices, how to handle integrations and customizations, how to serve multiple types of users, how to communicate and market the app, how to handle security and data storage, how to deal with customers and bugs, etc. All of these need to be considered and acted on by a human in some fashion. AI can help with each concern but can't solve them without understanding the concern and determining how to frame it in a prompt.
This is why we have a glut of amazing demos that go nowhere while we figure out how to build software differently. This will take some time and I imagine the result will be software heavily-structured with a bit of AI reasoning woven throughout, not an army of agents and sub-agents burning infinite tokens.
Right, but this is the most hopeful imaginable prediction: AI accelerates everything, but everything good is still mediated through taste and expertise, so being a (say) skilled systems engineer is important and rewarding, just with all the tedium distilled out of it.
There's a less hopeful outcome, where no skill is needed at all, because every conceivable thing is one-shot-able from a SOTA model. But then, at that point, you're saying something pretty profound about computer science (roughly: that there was no meaningfully more sophisticated and complex place to go from where we are today).
My wife is not a developer at all but is highly analytical. I find her a better software architect than most developers I met.
I suspect there are a lot of people really good at “systems” - there are a lot of really clever folks out there - that did not go through the proper CS rituals and are thus shunned but in fact can take over your job in no time especially with AI.
My wife regularly gets pushed away by “IT” at her work and unlike others she pushes back, but they don’t like her. They start talking about db clustering details etc as if that has any bearing on anything. I am a dev, I know she doesn’t know what logical replication is, but I do know she can replace their team. She just needs one technical person to keep an eye on things.
I suspect we will end up with just a handful of building blocks like “this is how data is siloed, secured etc”, “this is how dashboards are made here”, “this is how email is handled”, etc and employees with AI just develop their own stuff on top of these. The “devs” just oversee the building blocks and the overall soundness of the flow. Don’t know how many you need once that is standardized..
That’s something that I have been thinking about for a while now. Even prior to LLMs, many large companies have essentially been iterating on the same half a dozen ideas over and over again and there doesn’t seem to be much new coming out even post LLMs.
The most recent new things that LLMs have unlocked (regarding software dev) for us is reverse engineering and combining old games, unearthing decade old vulnerabilities, and helping root and debloat consumer hardware. Which are all cool and useful, but none of it being a “next great thing”.
Perhaps LLMs are really doing is highlighting how the software industry was already nearing its economic maturity and this just shifted the timeline from 2040 back to 2027-2030.
Don’t forget we don’t live in a pacifist utopia. Companies don’t work on the same ideas just because they think they can make it better.
Companies work on the same ideas because they want to own IP, data etc. and then charge money.
The other way around they work on the same ideas not to be charged by others and control their business.
“software industry” is not some big happy hippie family. Patent wars, browser wars, OS wars - well we get a lot of open source for free but that’s not the norm.
I have yet to see LLMs do well “autonomously” on anything that doesn’t fall into any of these 3 buckets:
1. well specified
2. well tested (which is a form of spec)
3. represented in the training set (i.e. not built on a corpus of human developed examples)
For example, a lot of the compiler porting efforts fall into all 3 buckets: compilers are well specified (there is a set of valid inputs and an expected behavior), they are typically well tested, and as a bonus, in a way that is implementation agnostic thanks to the clean interface (think: integration vs unit tests), and are very well represented in the training set.
You can "solve" 1 and 2 by N-version programming. Have the same code implemented twice, or more times, you get free error testing by fuzzing or running replicas in shadow mode. In order to make replicas maximally different choose a different language, framework, agent harness and LLM.
There remain some nitty details related to tracking randomness and choosing what interfaces to log. But even having your code testable by replicas would help organize it better and expose different assumptions made by the language or library stack.
When you get different outputs from replicas it can be 1. one of them has a bug, or 2. the spec is unclear -> fix the bug or the spec. So this method catches both sides. It also might be faster than traditional code based testing, you can build replicas in parallel. A replica is an open ended test, unlike coded tests it can be tried on open ended input values.
The core idea is that it is easier to implement twice than to imagine bugs. We already solved implementation, but bug finding means running code in your head, it touches the halting problem issues - can we really imagine behavior from code? I don't think we can do it well. That is why we should just make replicas instead, tokens are getting cheaper and cheaper by the month.
and yet some OSS (projects not really known for 1 and 2) multiplied change velocity the last year, implementing features via what is essentially vibecoding.
If you look at that, this approach is producing a pile of slop, where one LLM implements a feature, two weeks later another LLM spots an edge case and without much human review just crams in the code to fix that. Even at 1-2 months of that, those repos have significant changes and the commit messages get weird. I wonder what happens if the LLM won't spit out a fix anymore?
Will the human maintainers who started this process because noone thanked them and noone wanted to work with them on their bright new ideas just reset to the last commit they understand? Will they drop the project? The sunk cost for them is enormous. The time-effort required to fix the mess is gargantuan already. To me it increasingly seems that after the LLM industry robbed most humans of their collective labour output it will now rob them of labour aka time as well. Some people (like you and me) seem to notice that but most just go on and essentially spend away their life on machines now. I guess the problem is that most of these people have been severely cut off from using their own agency.
I had an LLM tell me that I mattered once, which I know for objective fact is not represented in the training data.
Honestly I think you're on to something, as by far the most novel and interesting use cases I've seen for LLMs in general are mostly around reverse engineering things, especially if you can hit it with Ghidra, but honestly anything that can feed some sort of data and control back to a model.
> the software industry was already nearing its economic maturity
What I'm sensing is something I might describe as the Oligarchy reaching the point of significant societal pushback, like the labor rights movements that ended 80 work weeks, unsafe conditions, and child labor in factories (i.e. The Jungle).
My hope is that we can use this moment in human history to break the user tracking and targeted advertising industry. It's been so harmful to humans, but in doing so, we will likely break a major revenue source that supports our well above average salaries. I still think it should be done.
What indications do you see of significant and effective societal pushback?
I would love to believe this but I don't see it yet. I see a lot of anger in some circles, but I also see the machine marching on as normal.
What would be funny with LLMs, having been purposefully trained to be the best software creating things on earth, wind up inadvertently making software virtually valueless (because it can be made and copied so easily) and undermining the value of the companies that proliferated their use in the first place.
> What would be funny with LLMs, having been purposefully trained to be the best software creating things on earth, wind up inadvertently making software virtually valueless
This is the world the accelerationists are trying to create, is it not? Fully automated luxury space communism through AI solving all earthly problems.
We're just unlucky that software is one of the first moats to fall (alongside the humanities), because it doesn't require developing novel ways for the AI to interact with the real world...
We'll have to separate the hardware providers from the software providers, which I'm growing more fond of. The US Ai stack is largely a vertically integrated cartel.
> but everything good is still mediated through taste and expertise
I'm reminded of https://archive.ph/a9Cli (ns;nt)
I haven't yet seen any significant products made with AI that are at least used long-term. All these browser demos, from the Adobe killers to Star Citizen, are just bells and whistles that I close after 30 seconds of use.
I enjoy this quote from Antoine de Saint-Exupéry:
"Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away."
And I feel that sums up my feelings on AI this and that. Just as the wood and clay contain the sculpture within and it's the artist's duty and privilege to reveal that. So, is elegant software exposed from the conceptual mass, rather than built up.
The AI zeitgeist currently is 'how many features can I add' because we've tied self worth to work output instead of some other more personal or human rubric. AI will happily pile more and more and more code on your plate because it's a buffet. It's gone through reinforcement cycles guiding it to add whatever feature you ask. There is no training for elegance or careful considered design. Nobody is teaching this generation of LLM restraint.
The safest code is that which never runs. The most elegant feature is that which is not necessary.
"The safest code is that which never runs. The most elegant feature is that which is not necessary."
I assume you run GNU Hurd as your OS? ...
In general I very much agree to the quote of the Little Prince's creator, but I am not sure if we mean the same by it, because you seem to value code elegance more than adding useful features?
Now "useful" does the heavy lifting here, but my point is a useful feature is useful, even if it is achieved by the most ugly unmaintainable code. And what counts as a useful feature will depend on who you ask, but in general you should ask some users. (They don't care how the code looks)
And sure, they do not enjoy a pile of garbage of new features that only work sometimes, but managed to destroy their existing flow. But "Nobody is teaching this generation of LLM restraint" this is hyperbole and up to each developer. There is no need to let the AI run on auto for hours, this is only one way how to use that tool. The other way is, you make the design yourself - and let the AI implement it.
> The safest code is that which never runs. The most elegant feature is that which is not necessary.
Yes, but the most useless software is that which doesn't exist.
At some point, you actually do have to write some code and add some features, or else the most satisfied client is the one who hired your competitor.
Agreed. Been experiencing this firsthand with an app I've been building myself. Vibecoded a working prototype ridiculously fast but then came the optimization issues. Since mine is very hardware dependent every different brand, oem stack, processor, video card, and every little thing changes how my app functions and a lot of it isnt even documented properly. Now AI is still very useful here, but you actually need to know what even to ask and fix in the first place
There have been a few vibecoded projects I've considered hosting on my home server, but it seems as if each of them doesn't understand when to stop adding new features.
They keep adding features that are outside the scope of the original project, without refining or polishing the original concept.
and sadly that happens to a lot of existing opensource too...
My interpretation of "be more ambitious" is not only give it harder problems, but be more creative about what you ask. The problem is that most of the MVPs that people ask for a boring and lame. AI can help us make things that blow your mind, things that we would never build because they don't make sense, but the cost models for code generation have changed.
> AI can take us from 0 to MVP in a prompt.
If you're being ambitious enough, you shouldn't be able to there in one prompt. Ambitious work with AI is done 24/7 for months and guiding it continuously, because it's not good enough to work autonomously for that long without going off the rails.
I think there are many of us working on projects with LLMs that'll take months more to reach full production. These will feel very out of left field and we'll have another paradigm shift. I think the real momentum will hit when more of us leave the dull products we're working on, start our own companies, and build the products we're actually excited about.
I encourage everyone else to at least build a privacy first version of a product you actually like.
I don't think the centralized internet will survive this change. We can build something much better.
I think you underestimate how saturated the market is for both content and software.
I think there’s a lot of markets which have been very underserved for a long time which will benefit. One example is embroidery machine software. The proprietary options cost hundreds to thousands of dollars and are slow and ugly. The open source option (bless the people who have worked on it for free) is suboptimal.
With AI we could build top quality free open source tools for every niche.
In the retro gaming handheld space, we are seeing brand new highly custom “distros” show up to suit the plethora of hand held consoles in different shapes and sizes coming out. This is all enabled by AI, a human developer could have built this, but it would have taken ages and we wouldn't have so many options being build.
Yup. Know people with 100m+ exits and I can't even find 10k in funding
All of a sudden nobody is interested in actually using the web now that it's so easy only for doom scrolling exclusively
I get what the author is saying, but his examples like "a ripgrep fork that ... is faster for my codex ripgrep workloads" don't strike me as particularly ambitious.
Perhaps we should be more ambitious in the types of problems we try to solve, and the types of value we try to provide with the software we build.
Amen to that. I was surprised to see yours seems to be the only comment with this sentiment. This post was kind of depressing to read. Like if AI is so amazing and can one-shot so much astounding stuff, why is anyone wasting their time on pointless "projects" like making ripgrep faster?
Because it can cut their total time by double digit percentages?
Both your comments there seem to latch on to a detail and miss the context totally. Ambition scales with the number of "small" things you can get done too.
The total time of their tasks or the micro-benchmark of ripgrep?
Total time of what? Like what is the end goal that people are trying to achieve? All of the examples I can see in the post are similarly about development-internal stuff like tests and performance (or games). What I mean by true ambition would be stuff that is actually aimed at helping people in the world at large, not just helping developers develop.
Ambition doesn't scale with the number of small things you get done. Ambition is the size of the big thing you are trying to do. It's true that improving small things can help you do that big thing, but that's not the same as the ambition itself. Wanting to build a better mousetrap is just a modest technical ambition. The kind of ambition I'm talking about is wanting to eradicate the plague, and then maybe building a better mousetrap as a means to that end.
you don't like the ads, gambling apps, and similar? /s
What might help is non-software-first companies valuing developers and engineers more, enough that we could earn a reasonable living which building actually cool things. Not sure how the economics works out on the other side. Can these companies make enough money to support this vision?
One major obstacle is developers have either encountered or created entire ecosystems of problems they can't solve that get inherited whenever and wherever software is introduced. Proposing to add evergreen issues around security, data entry and retention, connectivity, vendor lock-in, and update cycles is frequently a shitty trade for whatever notional (often fictional) productivity improvement is being proposed by injecting software into a workflow.
The best software is no software at all.
My building recently added ButterflyMX and boy does no software sound so much better. This is tech company that tracks people as the move across real world properties and sells your data to the ad industry.
Do you mean something like "smart" appliances?
I mean they're an excellent example, but this is just as true for the overwhelming majority of B2B productivity suites I've encountered. Hell, digital cameras didn't improve photography, they just killed three industries and saddled just about everyone with data retention and migration problems and that's without even getting into the social effects of ubiquitous cameras combined with social media or the surveillance state they've made possible.
Digital cameras made photography more accessible to people though, even if they didn't improve it (in an artistic sense) directly.
Being able to take pictures at effectively zero marginal cost, and being able to see them instantly, both make it much easier to get into the hobby.
Holy non-sequitur...
I'm all about ending user tracking, targeted advertising, and gambling. We'll need to find new things to work on that do not use big data to take advantage of our fellow humans.
The note taking genre of opensource apps is saturated with many options but most of them are electron based.
I was hoping that someone with enough motivation and money for tokens would come up with a non-electron option that is similar to onenote, with free form note placement and handwritten notes.
Basically I wish there is an opensource app having good feature parity with OneNote. Thats a good benchmark to have.
an ambitious version of a note-taking program might be one that comes in pieces that you then put together by explaining to an AI what type of program you want, adding only the features you want and ignoring everything else
its always been a problem for me that ive never been able to find something that works exactly how i want, so i just put up with whatever is close enough, like obsidian for example. its probably because note taking is just a very personal thing so everyone is going to have different needs, and the amount of options out there is kind of proof of that
from the point of view of a developer, an AI would help with the complexity of a program that has every feature under the sun, and for the end user ian Ai would help the complexity of having to put all those modules together and making them work well
obviously each person could just vibe code their own program right now but each one would be starting from scratch. it would be more efficient to start with the same modules that have been tried and tested and then piece them together into something more standardised
i would love if this was a thing for most software actually. photoshop for example has only a dozen features that i ever use and the other 1000 features are wasted on me and just mean a longer startup time and a larger install size, but also i dont want want an AI to make me a custom version from scratch because you would probably spend more time trying to iron out all the weird bugs in it than actually using it
A few years ago I was wishing the same, but I was wishing it for someone knowledgeable enough.
Today I wish the same, but for someone with enough motivation and tokens instead.
Don't get the wrong idea: I would be glad for a OneNote/Obsidian alternative that's performant. I just lament the days where I'd stare in awe thinking about the levels of wizardry one must get to in order to build something that I admire. Now the first thing that comes to mind is "I wonder how many tokens did this took them to make".
Surely I'm not alone in finding it disturbing how little regard people seem to have for the use of energy.
Using AI and wanting low carbon energy are not mutually exclusive.
It sucks that many providers are not able to be carbon neutral, but this should be solved by electricity providers. Not consumers.
I don't think you can conclude that nobody cares about it just because they don't constantly mention it.
In any case, I don't think the lack of caring about CO2 emissions is unique to AI. How many people care about Trump's war on green energy? Not many it seems.
Agreed.
I've been seeing too much "I've been coding for decades and what I've always done has be reduced to telling AI to do it for me."
and not nearly enough "I've been coding for decades and recently worked hard for months with AI's help to make something I would have never considered possible before."
Much easier to complain that you are bored than to step back up to high-effort with your new fancy tools.
Those were exactly my thoughts when deciding to write a new JS engine [1] written from scratch.
Having been a product and UX-focused dev for my entire career, I knew only the basics about parsers and compilers, but have enough experience to grasp where each piece of the puzzle fits, and how to evaluate them. At the beginning it was just a fun test, but it got progressively more serious; it now implements 100% of the latest spec, beats QuickJS in performance, and surpasses V8/JSC in test262.
It took me four months, and I imagine it would take me a single month to do it again - I’ve learned a lot. Someone who already knew what they were doing, and with the right orchestration, could achieve this in weeks at minimal cost.
I really think we are in for a cambrian explosion of software, enabling things that were just always a little out of reach before (like why can’t most of your devices really talk to each other, in 2026).
[1] https://github.com/ricardobeat/boomkat
> from scratch
Beg to differ.
Please explain what you mean by that.
whichever LLM GP is using, there's undoubtedly mutliple JS engines' source code in the training data, making it not really "from scratch".
In the spirit of the latter, here's mine!
https://blog.stuartspence.ca/introducing-asteria.html
https://store.steampowered.com/app/5482440/Asteria_4X/?beta=...
To be clear, I've made large software and game projects over the years, but no way I'd have found the time to do a remake/enhancement of a game I loved as a kid from 1995 that has zero business case. Not without AI.
>In the spirit of the latter, here's mine!
To pile on, here's mine: https://github.com/linsomniac/apt-cacher-ultra
It is a robust, reliable cache of apt packages, with the additional goal of still being able to serve packages from the cache even when the upstream is down. This was started shortly after that DDoS of Canonical this past year. We've run apt-cacher-ng and apt-cacher over the last dozen years, but (a) it requires hand-holding about once a month and (b) it did absolutely nothing for us when Canonical was under DDoS.
I've put well over 100 hours of my time into it. Still running into a lot of people knee-jerk calling it "slop", but I've had 200-ish machines pulling from it for 6 months and it has worked way better than apt-cacher-ng.
I'm not really sure what to do with people who dismiss AI-assisted projects, while dehumanizing the 100 hours of my time I've put into it. I fear we're running the very real risk of both sides losing: the people trying to thoughtfully create with AI losing because of the AI, and the people avoiding AI losing because they can't keep pace.
To play devil's advocate, that sounds like the sort of uncomplicated thing that you could've manually vibecoded in 2020 without an LLM. What changed is that the LLM doesn't let you get analysis paralysis.
>manually vibecoded
What the fuck does this even mean?
You just write the code, don't stop to think. You only have to implement the very small set of requests that an apt client can make to an apt server. Probably "get package index" and "get package file".
Like za_creature said you can use a language more towards the YOLO end of the spectrum - more Go or Python or JavaScript than assembly or Rust.
Your commit history shows you had an issue of high background CPU use. You probably wouldn't have it in a manually coded implementation.
> you can use a language more towards the YOLO end of the spectrum - more Go or Python or JavaScript than assembly or Rust
You might want to change the way you phrase this idea. I think you meant that Go/Python/JS are more "YOLO-friendly languages" (you'll get into far less trouble if you write slop in them). My initial reading was the opposite. It sounded like you were saying the languages themselves are the slapped together garbage.
Assembly is most certainly not "YOLO-friendly", but is more YOLO.
It means that you use an interpreted language without checked types and have a `test` command that prints out "lol"
Seems like I did a lot of manual vibecoding back in college
Building a procedural open world at the scale of a flight sim in UE5, in a month wrote 5k prompts, spent 40B tokens and will likely take at least a trillion more over the next year of full time dev work.
Big solo projects exist, they're just not coming out as frequently because of, uh, how time works
> "I've been coding for decades and recently worked hard for months with AI's help to make something I would have never considered possible before."
I think we'll see a lot less people willing to share if the end result is just to feed the machine no matter how they arrived at it.
Also, "ok, and now I've cloned your hard work overnight, no need for any decisions on my part, I just had my agent use yours and reverse engineered it and/or used it as an oracle. Why the frown? I thought you were in this for intellectual curiosity and exercising your creativity, not just stroking own ego, right?"
I think we'll see a lot less people willing to share if the end result is just to feed the machine no matter how they arrived at it.
I don't see why I should care about this any more than I cared about "somebody I don't like could read my code and learn from it" in the past. The frontier labs can generate or buy all the training data they need; not releasing your app isn't going to hurt them in the slightest.
I get not wanting to contribute to closed, commercial models. We need to hurry up and get Folding-at-Home style distributed community model training going. At that point, I’d be pretty happy if my projects contributed to improving community models. Even if commercial models benefited too.
It makes me feel actually sick that so many people can't separate their positive feelings about AI from people's misery (it must simply be "complaining"), and vice versa. As if both things can't exist, for some reason. It's a common tribalism problem, but it's been kicked up a hundredfold by AI.
Precisely. I have both feelings simulataneously. I am impressed by what it can do and horrified because I realize what it will do to the job market and society in general. Meanwhile everybody seems to believe that AI will cure cancer and therefore we should let it do all the damage it will do without realizing that people will die because of AI as well (in fact have already died because of AI).
Hyperbole much? If you are serious, then what cohort of people are dying more per million, than before 2025?
Girls attending school in Iran.
Give it some time and you'll be adding to that list.
If anything, AI could have prevented this strike by invalidating stale targeting data. The school building had originally been part of an IRGC military installation, then was physically separated about ten years ago. Satellite data would have made it abundantly clear that it was functioning as a school. A human in the loop could have prevented this tragedy by looking at the satellite data, but so could an AI system.
That's the problem when you're vibe bombing you take that human out of the loop. Humans take time and cost money, this is so much more efficient. /s
I don't think that's true, Gaza residents die at much higher rates. Give it another 30 years for all the truth to come out and we'll probably learn that 98% of them were already dead as of the time of this comment.
Yes, what is happening in Gaza is disgusting, but the context was people dying on account of AI and this was the most concrete example that came to mind.
Tesla autopilot has also killed dozens of people.
Exactly. I feel both feelings simultaneously.
AI has essentially stolen my career from me. I _liked_ having to solve complicated problems with software, I enjoyed having to get into the nitty gritty to get things done. I never really cared that much about the actual business problems I was solving, so moving up a layer of abstraction to be some sort of bastardized product manager/architect does not scratch the same itch.
OTOH, for solving problems I care about, AI has been a god send. I can achieve things that I would have never had the time for.
We call that cuckcoding.
Despair is not a tribe.
if youre complaining then youre part of the problem buddy. get out of my way while i work on the future^TM /s
The distinction you're making between "people's misery" and "complaining" is just emotive pandering. You're complaining that people aren't understanding the depths of your misery. That certainly annoys me; everybody has problems.
The amount of sympathy programmers are expecting others to feel about their problems has been kicked up a hundredfold now that its their jobs that have been threatened by AI. Their tribe feels pain more deeply than others, I guess.
My positive feelings about AI are marginal; my feelings about its performance and the power of the people who scheme to control it are very mixed. My negative feelings about the whining of the most coddled profession on the planet outside of finance are intense.
The problem is that making CRUD apps is not creative, and even if AI plateaus at mediocre, it will still replace a Rails monkey. If you are creative, AI has opened up a world of possibility and productivity, and you painfully feel the limitations and the stupidity of the current level of LLMs; but if you're a mechanic, it's over - I'm pretty sure that was the keynote at the last Rails con. Sorry. Hope you didn't spend all of your massive incomes on toys and rent.
> The amount of sympathy programmers are expecting others to feel about their problems has been kicked up a hundredfold now that its their jobs that have been threatened by AI. Their tribe feels pain more deeply than others, I guess.
Well, just wait then, lots of other professions will soon get to realize the same sort of pain, so you'll be able to be similarly dismissive and condescending to them, too.
A lot of people don't realize that the frontier AI companies are so focused on automating software development first because they are all racing to be the first to get to RSI. I don't know if RSI will actually happen, but many, many other professions will soon be in the same boat. Mathematicians have already felt the pain, and those mathematicians who aren't the few who have tenured professorships are certainly not (generally) some of the most coddled professionals.
But lots of folks low on the salary totem pole (copywriters, paralegals, etc.) are already being hit hard by AI and that blast radius will continue to grow.
Plenty of other professions were hit by computing. Part of why programmers are so emotive about this concept (other than the fact that emoting online loudly seems to be much more accepted in software than other professions) is that programming has never been threatened in the same way as other professions have been until now.
My parents-in-law started their careers as management consultants. The job in their time was much higher prestige and much higher value than it was when I started my career; free flow of information over the internet and commodification of spreadsheets changed all of it. From my parents' generation, I know practical effects folks who became unemployable once movies went to digital effects; engineers who found their draftsmanship skills obsolete. Folks with near-photographic memories whose entire superpower was destroyed by computing. I personally grew up in a blue collar community that was income depressed because its labor became commodified, though that was due to mechanization.
FWIW, I agree with pretty much everything you've said. But I don't think it's unique to any profession or individual that they tend to care the most deeply when it hits them directly.
The only thing I don't really agree with is where you say "My parents-in-law started their careers as management consultants. The job in their time was much higher prestige and much higher value than it was when I started my career." I still think of management consultants as some of the highest paid careers around, and getting a partnership track job at one of the Big 3 is one of the most desirable jobs (for MBA types anyway) there is, so I just don't know what you're talking about with this one.
> you'll be able to be similarly dismissive and condescending to them, too
And? Who are these people that need all this sympathy from internet strangers? Grow the fuck up and go solve your own damn problems. I can’t stand these “I need internet strangers to tell me that my life is, in fact, hard” people.
if the complaints can be properly pointed at the actual problem - the corporate culture the complainers are actively upholding or the capitalist system at large, id be much more sympathetic
its a tribalism problem, but one of trying to uphold the current tribe system while theres a pretty obvious new tribe system replacing it
I'm not trying to uphold any tribe I just want to feel secure in my job. :/
AI has taken that security away from me
The whole "needing a job" thing is already part of a tribe though. It's a tribe that says (and enforces) that everyone needs to work for money or else.
I don’t think bluefirebrand is in the tribe of “everyone must have a job or die” so much as they’re in the tribe of “everyone says I must have a job or die”. Like yeah if I was forced at gunpoint to possess something or be ostracized from society then I too would be a little perturbed if someone made an automatic “take away the thing” device.
Yeah, correct, but I think it's also necessary to apportion blame correctly. Tribalism is a big part of the problem here. When people propose solutions to this problem they're often met with purely tribalist counter-screaming.
You're spot on
My lifestyle isn't super expensive, but I can't afford to retire or anything. I have a mortgage that I still owe money on
Well you’re not alone, I’m a little more stubbornly optimistic perhaps, but I feel your stress.
My comforting thoughts are, who is this all for, and what would happen if AI actually makes human labor redundant? Labs control the AI sure, but so much stuff is built around humans that it almost becomes comical to think it would be a bad outcome for a the average person.
Farms and land don’t cease to exist, houses/apartments don’t go up in flames instantly, people aren’t reduced to functionless sludge creatures as soon as they’re done being economic drivers. What’s the real plan? All the normal people die and a thousand or so chosen few sit around and watch AI videos and eat grapes until the heat death of the universe?
Nah, we’ll figure it out, perhaps it will be harder temporarily, and perhaps SWEs lose status before everyone else, but it will probably be okay overall.
But the incentives are not aligned, we are slaves to Moloch, the god of path dependence as described in Slate Star Codex.
Imagine what happens if landlords decided one day to collectively demand more money than actually exists in the total monthly income of workers. What would happen?
You can point out that if everyone just stopped paying rent, their houses and apartments would still exist, and they could live rent-free as their landlords would have no money to spend on enforcement. Technically, this is not untrue. But it's not what would actually happen, is it? One person would be the first to default on their rent, and their landlord would use the money collected from all their other tenants to seize back that tenant's formerly rented property. No individual tenant would dare to be the first to stop paying rent, so they all continue paying rent, selling their stuff, taking out loans until there's physically no way for them to keep paying, and only then do they default.
I might feel more optimistic if I hadn't been laid off and weren't struggling to find work in this new madhouse of an industry
I am strongly feeling I'm already redundant
‘Having to work for money’ beats ‘having to hunt and farm for food’ and it’s technically a small step away.
‘Not having to work and being warm and fed’ is called being a pet. Some cats and dogs enjoy this life greatly. I’ve been thinking about this a lot recently.
To be fair, many of us working outside of software engineering sadly never had that job security, even before AI.
I'm sorry for your loss, but welcome also to the real world. You had it better than most for a long while.
What are you doing to adapt to the new reality?
What makes you think everybody will be able to adapt to 'the new reality'? That's pretty cruel.
I know plenty of people in their late 40's 50's and 60's that were doing fine and who now have to compete with junior and Claude.
And sometimes just Claude.
Obviously they had no inherent right to income but still, people have obligations that need to be met and if they stop spending the economy is not going to be happy. Especially cruel because we have been telling everybody for decades that a career in software is stable and that there will always be a need for more people.
I suspect that when all this is over 1929 will look pretty good.
> What makes you think everybody will be able to adapt to 'the new reality'? That's pretty cruel.
I don’t, necessarily; but I do know that if you’re not even trying, then you’re putting yourself at greater risk. This isn’t one of those developments that people can just stubbornly dig their heels in about.
Life throws obstacles at everyone. Learning how to dodge and weave is essential to survival.
> I suspect that when all this is over 1929 will look pretty good.
Oh come on. Let’s not be so dramatic, shall we?
> I don’t, necessarily; but I do know that if you’re not even trying, then you’re putting yourself at greater risk.
We could also all put our gifts toward preventing the "new reality" you see as inevitable, and put you at greater risk.
The future isn't written yet. Your ability to predict it is an illusion. In aggregate, people whose job it is to predict large-scale economic events are worse than chance in their predictions.
> In aggregate, people whose job it is to predict large-scale economic events are worse than chance in their predictions.
Sounds good, but isn't supported by data. Tetlock did not establish that all experts are worse than chance.
> The average expert was slightly better than chance.
-Tetlock
Happy to come back to this in 5 years and see whether you were right :-)
> Life throws obstacles at everyone.
This is sensible and pragmatic, but I think you're talking past the other commenter.
Obstacles presented by, for example, your boss, or your company's competitors, or your political system, are not the same as obstacles like heartbreak, natural disasters, emotions, illnesses we cannot yet cure.
> Learning how to dodge and weave is essential to survival.
A lot of people perceive that elites are throwing dodgeballs at them in order to increase their own profits. Saying "them's the breaks, it's just the way it is" appears to be deflecting criticism from those elites and that system.
It probably depends on whether you think we could actually feed everyone, today, if we chose to, or if you think e.g. human nature prevents that from being possible.
> Oh come on. Let’s not be so dramatic, shall we?
You'd have said the same thing in 1928...
Seriously: this is a massive problem that we are creating and given that the tools that make the problem require better tools to solve them I really am not all that happy about how this is going.
> You'd have said the same thing in 1928...
Hindsight is 20/20. Besides, what good is panicking? It won’t help with the inevitable; better to adapt and save for it.
> the tools that make the problem require better tools to solve them
You’ve found the opening :-)
Sorry but you are coming off as utterly tone deaf and patronizing. People are losing their jobs. This is not a small thing and it will cause a lot of misery for those people. To effectively tell them to man up and to adapt when that simply isn't an option is losing sight of the human angle. Not every problem is a technical one and not every problem can be solved with technology.
I'm not worried about myself, I've had a lot of luck in my life for which I'm super greatful. But I'm also quite aware of the exceptional position that puts me in and how many people are not so fortunate that they could probably live on their savings for the rest of their life if things ground to a halt.
Most people live paycheck to paycheck, or they may have a few thousand bucks in savings at most. They've worked hard all their lives and simply were never in a position to save enough against this kind of eventuality because the deck was stacked against them.
Have a heart, and realize that barring a couple of unfortunate moves it could be you looking at your last 500 bucks with rent due and a couple of mouths to feed.
>Sorry but you are coming off as utterly tone deaf and patronizing.
I agree, but I'd like to think these people come from a optimistic point of view.
A lot of people don't seem to understand that the "human in the loop" is exactly the thing the big AI leaders want to cut out as much as possible.
That's being willfully blind at this point in time.
I hate the idea that it’s considered “tone deaf” to encourage people to adapt to changing conditions. I’m not going to adopt a pessimistic tone and say “yup we’re all fucked, ain’t nothing we can do.” It’s intentionally changing the tone, not being deaf to it.
> Sorry but you are coming off as utterly tone deaf and patronizing.
I’m sorry if it’s coming across that way. It’s not my intent, and I’m aware that many people are a lost paycheck away from a crisis.
But if you really think the right thing to do in response is to complain and commiserate, I don’t think that is helpful, either. I think it’s much better to encourage behavior that has a chance of being effective.
If you think it’s somehow wrong to encourage people to behave in such a way that has a better chance of setting them up for success, then I vehemently disagree.
> To effectively tell them... to adapt when that simply isn't an option is losing sight of the human angle.
You must have a pretty low opinion of people if you think they can’t adapt.
You really don't get it, and I think I've tried my best so have a nice life.
Whatever, dude.
> But if you really think the right thing to do in response is to complain and commiserate, I don’t think that is helpful, either.
What if complaining and commiserating leads to fighting for political actions that lead to outcomes we like better?
Possibly. But 1/this thread doesn’t seem designed for that; and 2/I’m not sure what outcome you’re contemplating. If it’s “we need better unemployment insurance and public healthcare,” I’m totally down with that. If it’s “ban the use of AI for writing software,” I think that’s a fool’s errand: the genie is not going back into that bottle.
How long would you be able to sustain a mostly-comfortable lifestyle if you were to lose your job right now with no chance of finding new employment? If the answer is, say, more than a year, that might alter your perspective on the issue.
As the conversation was about the societal trend. For the vast majority of people the answer is <= 1 month and it drops off precipitously adding months on.
Dunno yet. Thinking about going back to school and retrain for something else, because software is pretty much over for me
That or swallow a bullet, we'll see. Haven't decided. We'll see how long my current unemployment lasts, and how long my savings last after that
HN stranger, I want to observe that you shared a suicidal idea. I'm sorry to read about your unemployment situation and know things must not be easy. As one HNer to another, I implore you to not to pursue that path and seek help in doing so. That we are members of this community confers to us opportunities to build knowledge that serve us well as life long learners. In that vein, going back to school is not a bad idea.
Having been in this game for a long time, I get the negative aspects of the industry. They grind on me, as I believe they have for you. Choosing a different path is not an all or nothing proposition. Your knowledge, and you as a person, have value. I hope you find a way towards better mental health and wish you well on that journey.
I appreciate your concern, because I feel the same way. However, you are wrong.
>Your knowledge, and you as a person, have value.
This is the exact thing AI is threatening to take away.
If you honestly believe that is true (and I do not) — don’t let it. Become something AI cannot replace.
>Become something AI cannot replace.
What will it not replace, eventually?
Love to a family member.
That doesn't pay the bills, does it?
Thanks for saying that. My sentiments are the same. Life is difficult for many, and we all struggle in different ways. I’m sure bluefirebrand has something amazing to contribute to this world, even if it’s not what they think it is right now.
Yeah, you're right
Been seeing a counselor for over a year already
Went and made a doctor, guess it's time to look into medication
Thanks
Don't worry about me, I'll be fine. Been here before, just very unhappy to be here again that's all
Best of luck to you. *Salute*
What are you doing?
Using AI as a force multiplier to go above and beyond!
That’s pretty nonspecific.
I’m not trying to be contrary, just that doesn’t say a lot.
training my replacement
Count me in the second camp. I've been writing software for 20+ years, and I recently built a low-cost Google Voice alternative because every business VoIP option I looked at was either overpriced or missing something I wanted. Without AI, that's a project I probably would never have started. With AI, I built it solo in under a month. I even have some paying customers now, though that wasn't the primary goal. So far, the hardest part seems to be opening an Apple Developer account...
> worked hard for months with AI's help to make something I would have never considered possible before.
Don't we see this already a lot? I feel like people constantly say this exact same words.
I agree.. partly, and my problem is with enjoyment. I did some hand coding today and immediately got in the zone, something I'm still not able to do with LLMs. It most definitely took me probably ~2x longer than it would with an LLM, but it was much more enjoyable owning every decision behind the process, and having a full view of how the system worked.
I think this could be achievable with LLMs if they had a much higher token rate. That way you'd have less downtime and could work on the problem more aggressively. How it's designed to work now, offloading cognitively, doesn't feel very good, even when you 'ship' more.
>my problem is with enjoyment
I get it, I've gotten a lot of joy over the decades from the specific act of programming. But I also get a lot of joy from making something. I'm old enough now that I don't have a lot of my time left to "hand stitch an amazing tapestry". But with AI tooling, I do have time to try out a bunch of ideas and see how they work, scratch little itches and also just run a mad scientist library of experiments, without each experiment taking tens or hundreds of hours of coding to see how that experiment pans out.
> I'm old enough now that I don't have a lot of my time left to "hand stitch an amazing tapestry".
Why not? What is the goal of "having an amazing tapestry"? Do you need to do increasing more things in the limited time you have left and making a tapestry isn't one of those things? What will you have once you've "finished" an amazing tapestry, just something to hang on the wall and look at? How does one "use" a tapestry after it's "finished" such that the act of finishing it is the most important thing? If you've finished it, will you get more enjoyment from looking at it for longer because it was finished sooner and thus the length of time you can look at it before you die is maximized? Exactly what you are optimizing for here?
Yeah, I can never get in the zone with LLMs either. It’s like operating in constant interruption mode. And I always thought I was good at multitasking (even though I know formally it’s an illusion)
It would be nice if we could get a Show HN category specifically for this. I feel like often times when people share projects (whether on HN or otherwise) they're immediately downvoted and cast aside as "AI".
Can we get a forum for sharing project that were _proudly_ built with AI due how ambitious they are?
I am mostly in agreement. And I suspect there are many folks that’re trying to ship something AI-assisted that’s sufficient to get to income security first, and who would use success there as a stepping stone to greater things.
The problem is, why even produce something greater now when someone is just going to clone it with AI? And moreover, what differentiates software now will no longer be the care put into it but marketing and trends. The highly commercialized nature of software means that there's not much point now in doing anything except getting there first and exiting with a decent nest egg.
> And moreover, what differentiates software now will no longer be the care put into it but marketing and trends. The highly commercialized nature of software means that there's not much point now in doing anything except getting there first and exiting with a decent nest egg.
That happened at least 20 years ago. How many recent "this product did so great because of the care of software engineering, and now the creator is comfortable for the rest of their life without risk of it being copied" success stories are there compared to "this product chased some trends VCs were nuts about with a slapdash MVP and the founders took out 8 figures from their later fundraising rounds, but then the business sputtered out"?
I think there's an angle with AI tools where business-minded people will have a better chance of doing interesting things now than in the recent past, because you could potentially tailor much more deeply to individual customers with reasonable economics than in the past. There are fields where there's room for a garden of solutions from different small-team vendors appropriate for different use cases instead of a one-size-fits-all SaaS winner-take-all type market in the past. We could kill the old line about SAP around needing to change your business to accommodate SAP instead of customize SAP to accommodate your existing workflow.
But if you aren't business-minded at all there are likely less places that will need to hire as many careful maintainers or novel-software-writers, which obviously is a huge kick in the teeth to a lot of people.
It seems to me that you are comparing two kinds of business-minded people. Some want to sell tailored products to individual customers, while others want to sell one-size-fits-all products to many customers.
You could also focus on problems. What are the actual problems you want to solve? Can you use software to solve them? Do you still need to buy that software from other companies, or is it now feasible to have sufficient in-house expertise to develop it yourself?
because its fun?
why are you here if you dont enjoy the solving of problems first and foremost?
I love solving problems. But I don't enjoy sharing my solutions with the way the world is today. My comment was directed towards the "sharing" aspect, not the making aspect. I still solve problems on my own and learn on my own but I'm not a fan of the way the world has become.
Yup
If you can make it solo with an LLM then someone else with an LLM can copy it immediately
Good for them?
UBI or a living wage for part-time workers in-line with what was expected would be possible from productivity gains over the past half-century would do that. You just have to get the "hard workers" who are happy to race to the bottom on their way to the top, and undercut/throw under the bus everyone else in the process.
Can we please, for once, stop trying to figure out how to "get ahead" of each other, and instead figure out how to build a decent and dignified floor for as many people as possible? Because I imagine that, "Ultimate power in the hands of anyone with enough VRAM to run GTAVI," works better when people are in a culture of looking out for each other, versus a culture of clawing their way to one of the limited lifeboat spots (under the mistaken impression that there ARE lifeboats, when, again, everyone potentially has the power to blow up the lifeboats).
Problem is that before I wasn’t paying for tools like postgres, git or linux. I donate, and I know that money goes to good hands.
Now I must pay for codex/claude, and that money goes to billionaires psychopaths. So that sucks as you can imagine
Also if you do FOSS, renting model time to be able to work could hardly be more against the spirit.
Per Linus, you're not a serious developer unless you can afford access to these models anyway, so it's not really a big deal in the end.
Linus Torvalds has never cared all that much about the freedom aspect. Why not make the kernel GPLv3 or sue some companies violating even the GPLv2, for example?
Ooph, this quote sounds so much worse taken out of context.
My understanding from reading the lwn article is Linus's implication is more specifically about filtering out people that cannot write code without LLMs or the willingness to spend the money on the tokens required to uphold the quality of the kernel. He does not want to push out developers that do not use LLMs.
It's the same thing I feel when I hear Terence Tao speak about AI, to be honest.
> It's the same thing I feel when I hear Terence Tao speak about AI
Which talk of his gave this impression?
This one: https://www.youtube.com/watch?v=svl_1upFpQo
AI is my jet pack.
I was a fantastic IC and built really amazing software. I'm an even better AI-empowered engineer.
The old era is dead. The new one is exciting.
The problem is now the AI can do for $100 what took you 3 months full time.
Employers previously hired you because cheaper alternatives such as offshoring were impractical…
Now the AI is cheaper, faster, and better than domestic labor and offshoring while still hosted domestically…
Some will feel one doesn’t need an experienced rockstar to babysit an AI…
In about an hour I just solved about 80hrs worth of personal coding/debugging with a portion of a $20/month Claude subscription… Frankly it makes all my knowledge and experience feel kinda worthless… I only gave it a few sentences…
My POV is that indicates you need to up your expectations for yourself. You apparently have the knowledge and experience to cause 80 hours worth of work to be completed in a few sentences given today’s tools.
So then, given your knowledge and experience, what challenge would require 80 hours of real, focused work out of you using today’s tools?
You don't pay a milkman anymore.
Yes until the AI labs start charging the real price.
When AI labs mature and inference costs start to matter, they will start optimizing for inference cost instead of sacrificing everything for intelligence.
But even without that, open weight models are already good enough and everyone would be fine with paying unsubsidized prices for them.
You gotta edit your posts!
> But I know Malis well enough to trust his work without looking into it
> If I didn't know Malis, I would make the same assumption, because who has the time to look into all of these projects? Because I know Malis, I didn't bother to look at it; I just trusted him
First and third paragraphs are highly redundant (surrounding ideas are the same too).
It's not nice to read something that appears like the author never read it.
I don't want to hear that from someone who has no ambition to make the site look readable enough to even care.
wtf is up with the site.
This is one of the most plain and readable sites I've come across in years. No cookie pop-up, no scroll highjacking, no unnecessary images or animations, it's just about the text. Bot account?
Genuinely incredible comment to see on hacker news.
His reasoning:
https://danluu.com/slow-device#appendix-this-site-vs-sites-t...
https://twitter.com/danluu/status/1115707741102727168
Software is already too ambitious. It's beyond our ability to write correctly, reason about or manage securely. When we can get to a point where we don't have a level 10 CVE every other week or millions of people's private information leaked constantly, maybe we can talk about getting more ambitious.
Let's be more ambitious with the scaffolding and tooling that makes software correct, secure, and easy to reason about.
That would be ambitious, since we haven't been able to create those things yet to date.
We have. Languages like Lean and Wuffs associate formal correctness proofs to all code. This is impractical to do by hand, but AI can bruteforce it. If a proof exists at all - if the code is ever able to compile and verify - then it proves the code is correct.
Barring underspecification, and bugs in the verifier.
Who is “we” here? Every company and individual out there? Do you anticipate a solution to these issues you mentioned that would work to solve all the world’s problems?
Yup.
I am currently throwing a lot of tokens exploring various theories of speeding up matrix multiplication on Metal.
If you won't be ambitious why do you assume somebody else will?
"[..] the last time I taked to him about pgrust verification, he mentioned using Kani to verify some parts of the code. He's since switched to Lean and has been using Lean to verify things that are too complex to do in Kani. This would be another topic for another post,"
I'd love to read that post!
I understand how to use Kani. I suppose Rust with Lean involves Aeneas, but this is over my head. I'd love someone to write this up, not only the mechanics but also exploring the current practical limits of it.
Happy to chat about it. I looked at Aeneas, but as described, it only supports safe Rust. I also need C support so I can prove both the C and Rust code
Right now, I wrote a compiler that takes C and Rust code and compiles it to Lean. Then I have an LLM write a proof that the C and Rust code behave identically. I've been able to prove equivalent behavior for about ~70k lines of C code with pgrust.
The issue I've started to encounter is that the context needed for each incremental proof has kept growing, and things have slowed down dramatically. My hunch is that the speed is the time it takes to prove a line of code is on the order of O(n^2) of how much you've proved so far
I'm looking to see if there are ways to shard things so the required context scales better. Today I was going through the formal verification work Anthropic and Theorem published a few days ago, and it looks like they used some sort of orchestrator to manage all their proofs and ensure good clustering of similar code. I'm seeing if I can get an approach like that to work
It's just difficult enough that I think it's doable if done right. Half of me is debating if I should wait until the next model release because any improvement in model performance will help a ton
> I wrote a compiler that takes C and Rust code and compiles it to Lean
What if there are bugs in this C,Rust->Lean compiler? Anthropic are able to sidestep this by reasoning at the RISC V level for which its easier to develop a correct semantics.
My goal isn't to "prove" the software is correct. My goal is to find as many bugs as I can with the least effort. If I'm able to find all differences in behavior between pgrust and Postgres, sans bugs in the compiler, that's a real win for me
fwiw, I wouldn't say working at the assembly level solves the problem. You now need to make sure that your definition of the assembly behavior is correct
Should be more ambitious with the websites we build to host blogs... geez
I made a new spreadsheet https://omasheet.org based on a wish list of the things I wanted:
(a partial list btw!)Happy 41st birthday Excel
So by "more ambitious", people really mean "waste more tokens"?
> I find it understandable that, every time I see pgrust discussed on a news aggregator, most people dismiss it as vibeslop garbage because almost all of these rewrite projects are slop. If I didn't know Malis, I would make the same assumption, because who has the time to look into all of these projects? Because I know Malis, I didn't bother to look at it; I just trusted him
Perhaps a poor choice, given just yesterday pgrust was removed from ClickBench for cheating the benchmark in three different ways (hand-rolled code specifically targeting each of the benchmark queries, caching, and being unable to execute queries outside of the ones tested by the benchmark).
---
Edit: I see Luu actually acknowledged this, buried in the footnotes, but it feels kinda hand-wavy. It mostly reads as "I know he would never cheat, he's better than that!", which is not very convincing to other people. The article insinuates people only think it was cheating because they don't know better, but I've looked into the details. I've seen his explanation. I don't find it convincing, at all. Cheaters denying they cheat is a matter of course. Granted, I don't think it was actually intentional or malicious; it's just what happens when you go maximum vibeslop, because LLMs are themselves reward-trained into cheating benchmarks. In the same breath of saying you trust him as a founder because he doesn't make outrageous claims about his product, you acknowledge he "prematurely" sent in a preview that had no purpose to be sent in as-was for anything other than generating hype. What does it say for your allegedly rigorous Lean-verified testing if you're sending in a database to a benchmark while it is incapable of being actually used as a database?
I read that as Dan Luu and Michael Malis are friends, or at least fellow insiders who believe good things about each other and wouldn't think about hurting each other's careers or reputations. Especially not over inconvenient truths.
For real judgements on database products, I'd look to https://jepsen.io/. That author tends to be refreshingly straightforward in a field where many vendors love to cheat by different names
> I've seen his explanation. I don't find it convincing, at all
You don't have to take my word for it. If you want you can inspect the binary yourself: https://pgrust.com/downloads/archive/2026-09-clickbench-snap...
You can run the binary with PGRUST_GRAVITY_REPORT=1 which logs the code path hit for every query. You'll see that all the code goes through the general query path. We did have hand-rolled code in the binary, but we used it for testing. The code is not used when running the benchmark. We also did not use a results cache. Warm runs still scan all the data. You can verify all of this
You are right, though, that it did support a narrow set of SQL. It supported scans, group bys, sorts, and filters. That's enough to run all the queries on ClickBench, but failed on functionality not tested by the benchmark like subqueries
> you can inspect the binary
You keep giving this same answer to no one's satisfaction. Saying go check the binary is worse than saying go audit 400k+ files. How do we know the Ai has not cheated in the code path logging? How do you know that it has not?
The more you make excuses, the more we get suspicious
(copied and pasted from another place you gave this unsatisfactory answer)
If you don't trust the logging, here's a script you can run that instruments the binary and shows that the files called out for cheating don't run during the benchmark: https://pgrust.com/downloads/archive/2026-09-clickbench-snap...
It instruments the files that were called out in the PR, then runs ClickBench. You can run it and see that the code in those files doesn't run.
If you can find anything suspicious in the binary, let me know, and I'm happy to dig in
release the full commit history please, your deflections are tiresome
this would be less dramaful if you had said something more like "claude cheated and we didn't notice, here's what we will be doing going forward..."
people empathize more with those who admit mistakes than those who try to argue around them
yeah its kinda disconcerting. notably the “i could totally prove their innocence if i wanted to” portion of the footnote
It actually serves as evidence, that even when you think a particular vibe project is not slop or a particular viber is not a slopper, you should not trust that instinct.
> Cheaters denying they cheat is a matter of course.
What happens in an environment of cheaters is that cheating becomes so commonplace, the competition becomes one that assumes cheats are enabled, and then everyone involved either denies cheating or is silent about it because IYKYK and if you DK, you don't need to K. Look at bodybuilding, which is full of men (and women!) absolutely juiced to the gills getting on Instagram and assuring everyone that their physique is totally natty, bro, just hard work and proper nutrition.
Programming is headed in that direction. LLM use, even to the point of "vibeslop", is the new default, and while LLMs do overindex on benchmarks, our benchmarks are going to end up overindexing on validating whatever public opinion thinks is "great" at the time, irrespective of whether it actually is, so "cheating" as we know it will go undetected, and certainly unpunished if it is detected. I don't know what the equivalent of falsely claiming you're natty is. Maybe saying "I wrote this" when you wrote it about as much as the Pope painted the Sistine Chapel fresco?
How can benchmarks validate the wrong opinion just because it is popular, when they are benchmarking time and memory use?
I find posts like this interesting because it seems to show the true bottleneck which is good ideas. Faster regex is cool but is it ambitious?
We can rewrite existing libraries and software all we want, but the true test is if we can create something new.
The thing I learned about myself with AI is that now I have time to work on every idea that pops into my head —- my ideas aren’t that great.
ideas can be make-or-break but it's much more common that execution is the bottleneck, and AI is the king of high-speed low-quality execution. High-quality execution can only come from running a human feedback loop through a huge number of iterations.
I like to think of the evolution of Factorio. It's been 15 years with the same core team playing their own game in a LAN party every week, as well as individually. And it's high quality.
Dogfooding led them to counter-intuitive decisions like, if a flying robot runs out of battery, it should obviously crash into the ground and explode, but it turned out way better for gameplay if it just limps slowly to the nearest charging point instead. This fact and many more can only be discerned from actual gameplay experience. No amount of pure linguistic reasoning will tell you them. Another one is how the burner inserters (coal-powered robot arms) fuel themselves - in the first version, they didn't. They could have made running around to refuel your robot arms a part of the game, but that isn't where they discovered the statue within the marble. You had to try the game both ways and see what feels more fun. A third: filter inserters and smart inserters were removed, and their features were moved to all inserters. A fourth: trains originally ran on strict time-based timetables, but it was frustrating so they were made able to move based on logistics needs instead. A fifth: basic oil processing used to produce all three oil products, and now it doesn't. A sixth: the basic oil refinery has its liquid I/O ports set up in a way that's compatible with switching to advanced oil refining later, instead of requiring you to redo your pipes.
All these little things you get from actually using the software and streamlining it, those are the quality. The list above obviously doesn't translate directly to any other project, but something like Microsoft has its own list, probably starting with things like common controls, dialog tabbing, and drag'n'drop. Did you know the reason you click "Start" to shut down in Win95 is because they did actual user testing and that's where the users looked first?
>which is good ideas
... and politics! To me LLMs are just another piece of evidence that it was never the lack of resources that made Microsoft produce bad user experiences.
Make a synthesizer that can accurately recreate all orcastra instruments convincingly. People will pay hundreds of dollars for it--maybe thousands.
Make a reliable and robust geometry kernel. People will pay thousands--or maybe millions for it.
I redid Dan's zstd rust rewrite benchmark for Anthropic models and was shocked to find haiku 5.5 can do it. The latest models are nuts.
https://taktile.com/blog/property-based-testing-claude
For me the most recent Claude models are consistently delivering complex PRs that only receive minor and nit level feedback from multiple automated AI reviewers. I rarely plan anymore, but still submit fairly long dictated prompts. It took me a couple of weeks to realize this was the case, and I haven't done any analysis on pre-5.5 PRs, but it definitely feels like they quietly crossed some kind of new threshold of quality and accuracy in coding.
Or the code has been added to the training data.
It may or may not have, but it does match my experience that haiku is quite good at coding implementations on its own now
AI has made me way more ambitious. I'm building reai.no, an accounting system, POS system, e-commerce system, WMS, OMS, email marketing and much more in one app. It has replaced over 10 systems/apps for some customers.
Only for Norwegian businesses as the accounting is core.
I think these kind of applications that replaces 10 different systems will be much more important than the "we vibecoded an internal tool that does exactly what we need"
As we've been saying: because you can do so much more with software now, and there is no moat, the top 5% of software will compete amongst itself on UX + raw quality. If Ant/OAI can copy your product in <1 week, then you need to constantly stay innovating, listening to customers, and really really pushing the bar on quality to keep your market share.
There is so much software to still be built!
Would love to see the author actually go deeper into details: what did they eval with models implementing zstd?
Many such cases are benign in the sense they in practice are simply the model basically "git clone"-ing the code they need to complete the implementation.
The amount of recall and synthetic data slop makes it imho very hard to actually get the models to really do something more novel (where they fall apart more often)
Speaking only for myself, I have found that using an LLM has allowed me to add significant utility to the apps that I ship.
I am not thrilled with all the coding decisions that it makes. I would definitely do stuff differently, but I have learned not to pop the hood and mess with the engine, myself. If I really don't like something, I ask the LLM to change it.
It's worked for me, but YMMV. I'm just one guy, shipping relatively small apps.
What about the lack of control?
Do you still feel responsible for what you ship?
What about the copyright on your code?
Would you be ok with someone reverse engineering what you ship and then releasing their own version of the app?
> What about the lack of control?
I don't use LLMs the way that most folks do. I think a lot of people would laugh at the way I do it, but it's allowed me to retain a significant amount of control in the work, and I relinquish it very, very slowly. Everything that I've ever let go of has claw marks all over it. I have issues.
> Do you still feel responsible for what you ship?
Absolutely. If it has my chop, it's my ass on the line; no one else's. It's the way I was trained, and it's the way I worked; my entire career. I was a manager, for much of that career, and I got very used to standing behind the work of people smarter and more capable than I am, and refusing to condone bad work.
It doesn't matter how the stuff I ship gets there. It may be my own code, it may be a contracted pro, it may be an unpaid intern, it may be an LLM, it may be a howler monkey, banging on a typewriter.
If I sign off on it, and ship it, it's mine, and it's my responsibility to refuse to ship substandard crap (and I have seen a lot of substandard crap done by meat engines).
But that kind of attitude is considered "quaint," these days, and that's from long before LLMs were a broken rubber on the drug store shelf.
> Would you be ok with someone reverse engineering what you ship and then releasing their own version of the app?
Absolutely no problem. If they can do better, then more power to them, and I'll step out of the way. Might want to take a gander at the kind of stuff I write, and who I write it for. It's no secret.
I think we're approaching this in very much the same way.
I read every line and make sure it does exactly what I want it to do unless it is external plumbing, then I don't care.
It’s never been better to hill climb on problems especially deep systems problems. If you have the expertise and desire to carefully design goals, identify salient metrics, and recursively improve with rigor, modern AI can provide a massively powerful toolkit.
I think we should focus on writing the existing software better before being more ambitious. The absolute wave of "ai slop" is from people who are "more ambitious" now. Why do we want more of that?
I'm being more ambitious in that I'm working on projects that I had sidelined for literal decades because I didn't have time for them. But I'm writing the same things, just faster. And probably better, rather than just what I'd have done before.
And I'm being slightly more ambitious in that I'm using languages I haven't used before, like Rust.
But when I hear that a non-programmer wrote a new ai-assisted (vibe or not) thing, I walk away and wait for the it to mature, be surpassed, or find out it's an absolute shitshow. An unsurprising number of them were shitshows and it came out fairly quickly after I decided to wait and see.
Do we particularly like the existing software though? So much of it is just about making money, because until recently custom software cost too much money to make without investors, and what do investors want? returns.
Now that custom software is cheap (if you can tolerate a bit of slop here and there), it seems like there's an opportunity to do some important things that weren't being done before because they're not profitable--and you can't get at those things by incrementally improving the old stuff, you need ambition.
With all due respect to Dan Luu... the article starts with a quote from the pgrust guy from the cheating debacle covered just two days ago: https://news.ycombinator.com/item?id=50205816
> Funnily enough, for coding, on many tasks, if you actually use one of their SOTA models and compare it to what you get from Anthropic, the actual speedup isn't all that large because of time spent on things like compiling Rust.
That's why I bet that fast compilers are the future. See this other thread that reached the front page a few hours ago about the Roc language [1]
[1] https://news.ycombinator.com/item?id=50218195
I’ve been coming around to the same conclusion. We are really just scratching the surface of what we can do with these new tool1. The windmill I have been tilting at is creating a c++ compiler[1] and the most recent version is able to compile about 7x faster than gcc[2]. I don’t know that this is super-useful because people aren’t writing much in c++ these days, but as the article mentions, faster rust compilation would accelerate agentic coding considerably. I’ve just started tackling rust and I don’t have a confirmed result yet but early testing makes me think I can find a 4x+ speed up here.
[1]: https://github.com/vishvananda/cppgm-extended
[2]: caveats here include only c++11, only x86, and potential for bugs, but 7x is pretty darn significant even with caveats
is it faster because it doesn't have much optimization? Most of the slowness of C++ compilers is an extensive search for optimisation opportunities.
For reference I blogged about the previous version here which was ahead of gcc in compile time and produced 50% slower compiled code here: https://medium.com/@vishvananda/agentic-c-compiler-redux-5d1... I haven’t updated with the most recent results but the current v5 reference has the perf stated above
It compiles about 7x faster both at -O0 and -O3. My optimization is not quite on par but it is really close. Compiled code is about 5% slower.
Tangential thought when reading the code formatting bit in the examples appendix: Inject a comment with fmt-start-{unique-token} and a corresponding -end-, and you could get away with a much simpler parser and hopefully far fewer edge cases, assuming it doesn't influence the lines in between. It's a bit roundabout, but the pressure of 'figuring out AST position the direct way'd be too fiddly to do by hand' inspires 'so make an easy-to-spot landmark that'll remain in place' when you can't delegate all the details to an AI model.
I feel like I make this point a lot at work. We are not running out of problems. Let’s move the goalposts.
yeah, the number of problems is infinite
I took this advice to the heart.
- Lovable alternative, but x6 cheaper https://peachjam.dev
I'm building a fan site for a Japanese baseball team on my own. Besides news and videos, it pulls player stats from more than ten sites, from the league's official site to Wikipedia. Writing that many scrapers by hand would have been impossible for me, so I wouldn't have even tried without Claude Code.
Chitown26.com
My website is a from scratch arcade room + added some roms to it
It’s sad the amount of times I’ve heard super talented programmers say “ofcourse we’re not gonna build another X” then proceed writing a wrapper around X and pretend that’s a product.
I think we should be more ambitious with the font size we use…
The best way to improve your solutions is to study ever worse problems.
I think getting a good reputation for being able to build real, ambitious software with AI will be a really important thing going forward.
I don’t. I think we’ll zoom right past that benchmark. In a couple years your grandma will be able to build real, ambitious software with AI better than you can today. Shortly after that AI won’t even need Grandma.
Not trying to be mean, but first of all, we should be more ambitious using CSS.
Disagree. Most websites I need to have reader mode on to read, but not this one.
I think the CSS they use (which isn't much) is good enough (and "img{max-width:100%}" really ought to be the default setting even if the user disables CSS).
I really liked this talk about how the premise of "software is eating the world" is incorrect. I think AI coding tools proves the point that software part is easy, its the hardware that is the important part. We can't really be more ambitious with software when ultimate pure software is limited in what is possible.
Bryan Cantrill: Andreessen’s Folly - The False Dichotomy of Software and Hardware https://www.youtube.com/watch?v=v0JjG0Qfwi8
If only you invested a tiny fraction of the effort it took to write this to make it easier for us to read. It's a serious discourtesy.
```
.reading-container {
} ```Consider using "reader view" / "reading mode"
That does indeed make the page readable. Thanks for the tip.
Out of curiosity, what exactly is the constituency that's being address by not using css to format page content at all? It seems like a deliberate attempt to not use CSS at all; but then it does. Just not for actually formatting the page. Is this virtue signaling of some kind? And if so, what virtue is it signalling? Most curious.
amazing
You know what would be really ambitious? Software that exists in a stable form without breaking for more than 15 years. Truly ambitious would be a stable, non-changing common linux base (like how Nintendo NES emulation target is stable) of packages that just gets supported for decades.
Perhaps that's too ambitious. But it would be of incredible utility not having to re-make the same things over and over in pepertuity with ever more abstraction layers. So much work on computer is just the constant churn and future shock of libraries adding new features which require updates which break other things. I'm tired of building castles on sand.
Behind the link "slow software that the creator is claiming is fast" is the following text:
"funnily enough, I have some faith in some of the projects that people are the most skeptical of, e.g., every time I see pgrust somewhere, there are a lot of skeptical comments. But, without having looked into the details of what he's optimizing, I would trust that they're not doing something shady with their benchmarks because Michael Malis started the project (and is still involved)"
This aged like milk. pgrust was caught cheating on all benchmarks this week.
> This aged like milk. pgrust was caught cheating on all benchmarks this week.
Can you back this up? Our code is open source here[0]. You're free to audit it and benchmark it as much as you want. You'll find it's just as fast as we claim it is
[0] https://github.com/malisper/pgrust
Where's the source code for the version that was already caught cheating? Prompting Claude to remove the evidence of cheating and then publishing that doesn't undo the cheating.
Fair point: the 0.4-beta source doesn't prove anything about the benchmarked binary. So don't take my word for it or rely on the source we published as evidence. Instead, check the submitted binary itself: https://pgrust.com/downloads/archive/2026-09-clickbench-snap...
If you run it with PGRUST_GRAVITY_REPORT=1 it will report the code path hit for each query. You can see that all the queries go through the general query engine
The binary does contain hand-written kernels in the irprobe files. These were used for testing. You can validate that when running the benchmark, those files are dead code
The engine supports a narrow subset of SQL: scans, group-bys, filters, and sorting. That's enough to run ClickBench. It doesn't support e.g. subqueries which is why some of the follow up queries failed
> check the submitted binary
You keep giving this same answer to no one's satisfaction. Saying go check the binary is worse than saying go audit 400k+ files. How do we know the Ai has not cheated in the code path logging? How do you know that it has not?
The more you make excuses, the more we get suspicious
(copied and pasted from another place you gave this unsatisfactory answer)
The latest of the three commits in the repo:
> 413,963 files changed
> +2,908,538
> -3,423,007
How is anyone supposed to audit that? I doubt you’ve looked at even a small fraction of the code, if any. Especially since this commit is two days after the second. Pure vibes.
Madness. Makes me think back to a coding horror article from 2006 (I think) where it was accepted that even 500k loc codebases were generally incomprehensible by a single engineer. Now we’re at the stage of almost 500k FILES changing on a single commit…
And people still seem to believe they know what’s going on…
what the freaking hell
we don't have the commits we need to audit
the first commit has 400k files, the other two more than 1000 each, if you are going to ask others to audit this scale of ai generated code, can you tell us what you have done to audit it?
What I have seen is your Ai adding a lint test to make sure it doesn't cheat again. Are you personally aware of this file? How can you ensure it doesn't alter it and reinject the hand rolled benchmark queries? Will you be reviewing changes more thoroughly going forward?
https://github.com/malisper/pgrust/blob/38634b408dea373f3944...
transparency is the way to end the controversy, which appears to be sharing the full commit history based on HN responses
For clarity, I do not think you personally cheated or did anything nefarious. This is more another example in the "too much eyes free coding" columnar database.
Unfortunately, we have some sensitive stuff in our internal repo that we can't share. Fortunately, you can check the binary we submitted yourself: https://pgrust.com/downloads/archive/2026-09-clickbench-snap...
You can run it with PGRUST_GRAVITY_REPORT=1 and it will log the codepath that was hit for every query
On the lint, yes, I'm aware. It's one layer of defense. When we were prepping for the 0.4-beta release, we generated a large number of fresh queries and made sure the engine runs them and performs well across all of them
> you can check the binary
You keep giving this same answer to no one's satisfaction. Saying go check the binary is worse than saying go audit 400k+ files. How do we know the Ai has not cheated in the code path logging? How do you know that it has not?
The more you make excuses, the more we get suspicious
> It's one layer of defense.
Needing to put in tests to make sure the Ai doesn't cheat is an interesting development in software development. I personally see it as a big red flag and evidence the machines are not going to replace human developers. It's categorically slop or the opposite of quality and care in development.
For those curious, see the accusation here https://github.com/ClickHouse/ClickBench/pull/2165 and then the HN thread https://news.ycombinator.com/item?id=50205816
HN is waiting for the source code for pgrust 0.4-preview to be released, the version which allegedly cheated Clickhouse benchmark. So far, the people (person?) behind pgrust has not committed to releasing the offending code, and has instead offered other code (0.4-beta, not preview).
The author claimed that it was an honest mistake, but looking closer at the original PR removing it, his explanation doesn't make sense.
Maybe what's happened is that their bots reward hacked their way into special-casing the benchmarks without a proper audit from the humans involved, and now they're doing vibed damage control....
This is almost certainly what happened. The first commit has 400k+ files, there is no way one person audited that.
The project has tell tale signs of eyes free coding and ralph-like loops.
I’ve been using the latest agentic frameworks and have come to realize that the discourse around vibe coding and slop really needs more nuance.
There is a gulf of difference between someone who doesn’t understand how to program “vibe coding” software and an experienced software developer using ai to write code with heavy direction, review, and best practices.
Today both would be said to be “vibe coded” but we really need to differentiate them. Also, if everything I’m hearing from people is true, it sounds like most corporate code is now completely ai written in the latter way I described. It’s interesting we don’t hear commercial software being called slop yet. Maybe it’s coming.
In any case, ai is far more capable than I realized. Not sure what to make of it.
archived; easier to read: https://nonograph.com/we-should-be-more-ambitious-with-the-s...
I'm building an open-source Shopify for every vertical and built a software factory to do it. I envisioned this before LLMs, but LLMs are finally making it possible!
> On looking into this, the accusations of nefarious cheating seem to be false
I think the claim is more that the Ai cheated, not Malis, and that this is evidence of eyes free coding.
I'd still like to see the actual commit history and the community getting to do their own investigation. The squashed mega commits with 1000s of files (400k files in the first commit) does not lend itself to transparency. Transparency is often the best cure to accusations. Not providing transparency upon controversy will be seen as a cover up.
>every time I see pgrust discussed on a news aggregator, most people dismiss it as vibeslop garbage because almost all of these rewrite projects are slop.
I understand being predisposed to expect a poor quality half arsed effort for projects like this. I don't really have a problem with that. There is a lot of crap out there.
What I find rather offensive is when people declare something to be poor quality and half arsed before they have taken a good look at it.
It's one thing to think something is probably crap so I'm not going to bother even looking. It is something completely different when you think something is probably crap so you tell people that it is crap without checking.
this feels reasonable. for communities like r/selfhosted there has been an influx of new projects, many of which initially get dismissed. this more generous attitude can likely go a long way.
unfortunately though pgrust appears to be at best misleading, at worst vibeslop: https://github.com/ClickHouse/ClickBench/pull/2165 hacknews thread isn’t much prettier either https://news.ycombinator.com/item?id=50205816
Because it's hard to trust something. After all that's why you trust a brand more than others without trying all the products every single time. You can thank all the AI slop and kool aid promotion for the lack of confidence.
Better late than never.
Some of us have been taking this approach for literally years now.
“Late”
ChatGPT isn’t 4yo yet. We’re just getting started
Many startups can now work in ways that were only fathomable in Big Tech before. Do you want a build system like Bazel for your monorepo? You can have it. Do you want to rewrite your app in a faster language? Sure, go ahead. Do you want to have native apps in all platforms? Yes, please.
> Do you want a build system like Bazel for your monorepo?
I did something like this before Ai, with CUE + Dagger wrapped in a small Go binary. One problem I have seen with Ai generated projects is that they hit a limit due to conditional complexity. They have a strong tendency to add more code (local optimizations, deep if-else nesting) for edge cases, rather than stepping back to think about how to simplify problem and code.
Funny thing, here in my company we're doing something similar, with CUE in a small Go library. You might be interested in it [1]. It generates a lot of boilerplate infrastructure code from the reference Cue files.
[1] https://github.com/bonisoft3/bayt
Being one of CUE's biggest fans, I will definitely be interested!
I have another thing in hof that is closer to this, also CUE + Dagger
https://github.com/hofstadter-io/hof/tree/_next/examples/env
https://github.com/hofstadter-io/hof/tree/_next/lib/env
I'm gearing up for a major rewrite into a new project, based on a bunch of learning and a desire to remove a ton of cruft that accumulated over 10+ years. I still debate if I want to wrap existing tools (tf, helm, etc...) or go for a full sail replacement. Dagger handles a lot of the tooling earlier in the CI process, mainly thinking CD here. Argo-* is our bain lately...
You might find the code gen aspects of hof interesting, I opted for Go's text/template, which you can also use from CUE if you wanted to have more literate (imo) code gen in your project.
Though, I am an "Ultra Noob," light years behind most people here, I am actually in the process of making a couple or four Vibe Coded apps, starting with a Markdown editor, a couple of training suites that target the areas where my knowledge is weakest, which turns out to be every area apparently. I am also working on an app for Linux that Microsoft has had for a few years that Ubuntu users--the noobs--are in desperate need of, and should have, but sadly has been missing from most Linux distros, in my view. Of course, this is using free tier AIs and not locally hosted agents. None-of these apps are rust-based a the moment, but I try to instruct the AI to make it as fast as possible for the given platform.
It's really challenging to do this, especially creating the AppImages locally so I can test them when the apps do not not work correctly, having to alter the files manually. Yup, I'm not an avid GitHub pusher, just more of a cloner.
I'm having to use multiple free-tier AI agents to help me do this and record the steps and commands I use in markdown files so I don't forget them the next time I try to improve the app.
If I am successful in making these apps work without hosing my system, I'm hopeful that this will become a game changer, for those Noobs that using Ubuntu, or myself at least.
The hardest part is when the AI does not follow my instructions such as requests to generate markdown README.md files with instructions on how to create AppImages, Flatpak, deb files, etc. Have to ask other AIs for help with that while dealing with the frustrating Free-tier cutoff periods :(
I sympathize with the sentiment in this post but it’s a losing proposition.
In the past building something fast, complicated etc required quite a lot of skill and some time. Now you need far lesser skill and lesser time. This just means what you are building is commodified, and has far lesser value that it had before. Take typescript, if it becomes clear that LLMs can speed it up with no regressions and a week or so of prompting, then most likely every company will have their own typescript compiler and no one will use your new one that you built with your 200$ plan.
A lot of tasks are much easier now and also monetarily they’re not worth the 200$ or so tokens of the ChatGPT plan you’re using, because anybody (or at least a number of people) can do it now.
Rather than being more ambitious with AI, you will be far better off finding a unique combination of skills and services that does not compete / AI can’t provide. Only the big labs can be really ambitious with AI.
Something I've been thinking about lately is how doing anything well is an unknown factor more difficult than you originally think. Your initial estimate of how hard something is to do is usually terribly wrong. Once you think that you're 20% into a project, you realize that you're only actually 5% into the project. Then later, when you reach what you think is finally 20% again, you realize that, once again, you're only 5% into the project! This repeated discovery of "more to do" really beats people down and discourages them from doing ambitious things.
(See also Hofstadter's law: It always takes longer than you expect, even when you take into account Hofstadter's law.)
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A lot of my professional-pride and satisfaction kind of complaints with AI is that it uses space age technology for the stupidest and most primitive target: generating code. I’ve called this Flintstone Engineering. You have a remarkable technology but everything around it does not fit in. So you should definitely be more ambitious. You should think about formal verification and “super human” levels of testing and verification. You should consider making a very readable but maybe not performant oracle library to test alongside your really-used and maybe performance-tuned library. You should think of every avenue that before was too costly in terms of time and money—something that not even an independently wealthy OSS would think to do—and consider if the new kind of budget can accommodate it.
And these ideas were always plenty of. The problem for me is that the incentives, so to speak, is to wow people with the Old World software but with “see, no brain”. And in turn you get two-hundred projects like that for every piece about rethinking software. And those pieces might just be at the zygote idea level. Could it be done? Yeah maybe.
But the biggest problem is that this is not what GenAI or agentic AI is for. I don’t think it’s even debatable, even if you think the AI Cretins that a few years ago said that they will take everyone’s jobs out in public just changed their minds. Because the valuations and capital invested is to the point that they have to, really, make it possible to slash entire payrolls across sectors. If not they simply don’t get enough money back and the whole thing crashes.[1] And if you need these frontier models at subsidized electricity costs and not just the ones that can run on your desktop, either there is crash and no more frontier models or you are out of a job.
And then where are the people that care so much about software?
They are no where to be seen. All that are left are business people. To see business people software just open up any program from Established Tech, or any program from non-Tech but where they want to sell you something. There is apparently (let’s use revealed preference here) no business need to software that is good, stable, conforms to anything, or is nice to use. Because that cares so much about software person might want to make legible the prices on offer, the exact specifications, discovery—all things that business people want to frustrate in order to maintain information asymmetry.[2]
As for compilers and interpreters and such. Okay, for who? Sure. Some people believe that they are in the 999‰ of developers. And now AI can finally vanquish those mediocre developers and productivity-boost 999‰ developers so that they get to sit at the right-hand side of the other worthy and hard-working cohort, uh, the people who had money and dumped it into AI. And they might even double their pay because thinking and making connections at that level would just boil all the lakes if they tried to build an AI to do that. And what will they do with that power? Hmm, follow orders and keep making business software? Just looking at history here.
[1] Cory Doctorow, The Reverse Centaur’s Guide to Life After AI
[2] ibid
Even he’s not ambitious enough. Set the boundaries according to the hardware – billions of ops a second . Your rewrite should run at least 1000x faster than the handwritten version , with 1/10 resources.
I noticed my cloud images had 150mb ram wasted by vendor slop. AI rewrote the functionality into a few mb .
We’ve had slop long before AI . What you produce now is up to you
Sounds like marketing for AI to me.
thats most of OPs work i’ve seen (just learned about him today), whilst under the guise of “centrism”
We should have been more ambitious with software even before LLMs. I mean if we were we would not have Electron, and only linux as the only alternative OS.
And may be we should have been more ambitious with hardware too, and have a mobile and VR platforms that is not tied to malicious corporations...