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I also take my shoes and off and find it gross when people don’t.

That said, I don’t think it’s really rational. Our houses are full of bacteria and dirt one way or another anyway. It’s impossible to avoid that without having some kind of airlock equipped with a shower in your porch.


I think it has or had practical reasons. It rains a lot in Japan, and its prime occupation used to be flooded field rice farming. So it is/was normal for shoes coming home to be in a somewhat gross state.

Old farmer style houses in Japan have an entrance area behind the main sliding doors in bare soil[1], and a wooden platform at waist height between it to hallways. The platform can be sat on to take off shoes or to drop off bags of produces, and then hallways and tatami matted areas are further raised an inch or two - the walking floor level of houses are therefore give or take a whole feet off the ground. These together create multiple mental boundaries for dirtiness.

Modern houses have it miniaturized into just a cinder-block high gap or sometimes just industrial colored tiles before a bump. But IMO it's still nice being able to leave wet shoes and umbrellas there.

1: 土間 or doma, meaning soil-space. Oddly this transliteration coincides with "home" in Russian(and of course rhymes with Latin domus).


I think these practices come from more rural but also tropical origins?

One part is purely practical, making it easier to keep the living space clean when you are coming in from the farm etc. Places with messy winters have similar concepts for muddy boots, snow boots, etc.

Some regions also have (or historically had) real risk of parasite transmission from soil and short grass. Taking off shoes reduces the chance of bringing their eggs or tiny larva into your living space.

I can imagine some cultural practices here being early memetic/evolutionary in nature, much like some religions codifying what are essentially food-safety rules from a time before microbiology was scientifically understood. We think about the parts we can see, but also have some instincts and practices that seem aligned with threats we can't actually sense.


> That said, I don’t think it’s really rational. Our houses are full of bacteria and dirt one way or another anyway.

True, but I don't know about you, but we don't have literal rocks, sediment, dirt pee, or literal poop on our floors in our home, anywhere. But shoes do occasionally step on stuff like that no matter how small, and neither of those things I want inside of my house on the floor.

But you're right that there still is bacteria or dirt all over the place, no doubt. But still, I don't step on something slightly soft with my socks in the living room and then inspect my foot to find poop stuck to it, and I think I'm gonna continue to prefer this way.


> rocks, sediment, dirt pee, or literal poop

This is basically what dust is. It’s everywhere.


>> rocks, sediment, dirt pee, or literal poop

> This is basically what dust is. It’s everywhere.

What?

> Dust in homes is composed of about 20–50% dead skin cells.[2] The rest, and in offices and other built environments, is composed of small amounts of plant pollen, human hairs, animal fur, textile fibers, paper fibers, minerals from outdoor soil, burnt meteorite particles, and many other materials which may be found in the local environment.[3]

* https://en.wikipedia.org/wiki/Dust

Further: dust is floating in the air and can be removed with decent (MERV ≥11) air filters in your HVAC system. Stuff on the bottom of your shoe makes contact with your floor and stick around until you wash it (and for much longer in the fibre of carpet or rugs).


Where do you live, where dust and pee/poop is the same? I'm fine with having small amount of the former inside, it's unavoidable, but the second is avoidable by removing your shoes.

Your HN username should be in the dictionary under “Dunning-Kruger”.


loooool


Slop


It is ok that you feel this way. As explicitly stated the report is _generated_ and id does require a different mindset to read AI generated reports. It contains quite a bit of information about attacker behavior and details of the timeline. It also linkes to a story that is now largely human narrated and I´ll keep improving on that as I find time. Having to juggle three separate issues yesterday did not leave much time for manual writeups.


I don't want to read AI articles, but this isn't an article, this is one step up from a log file.


1.5 billion commits of worthless slop


> I’ve stopped caring about code readability for a few months now. […] I don’t trust it with code anyway

If you don’t trust it with code, surely you need the code to be readable so you can understand what it is writing?


Possibly the most interesting article on LLMs I have read in recent months


Why wouldn’t it?


How do you expect us to take your views on LLM code quality and durability seriously when a) you don’t even look at the code and b) you’ve only been doing this for two months?


I've been working on the app for four months, and I am clearly not talking about code quality.

I am talking about product quality and maintainability. Both are more than adequate.

I know this because I have worked on it for an estimated 300 hours. Has the author practiced a similar approach for even a week? I doubt it.


2 months simply isn't enough time for evolving system needs. You don't get to know if your code is maintainable until the use cases have expanded and usually other devs will come on board, and what guarantee is there that they will direct the ai the same way? Your core features today may be solid, but expanding and adding cases coupled with debugability is what shows off maintainable code. Two months simply isn't enough time. Two years, maybe. I have maintained the same aggressively growing software from start up to public company to begin acquired. Two months is literally nothing in the maintenance lifecycle


I work on my project for 2 years now and using an LLM always came back to bite me. Learning how something works is needed, slow and painful - but pain is gain.

If this works for you - awesome. Until it doesn't.

As always there is 0 code or link. All talk.


And when do you expect my approach will stop to work? The core features are complete and the codebase is already sizable.

I will not publish my app on GitHub for free. It's a paid app, and I am putting in the hours not for your approval, but for commercial gain.

I also do not think it wise to link my HN account to my real name and expose my opinions and comments to my employer and colleagues.


Then you may as well said you've solved P=NP.

We do not require links to your app. What people are expecting is a description of your approach and sample outputs. So that someone else can try it and have the same standard of output. That's how you make a point that your approach is good.

When we buy books like "The Practice of Programming" or "The Pragmatic Programmer", it's because we are hoping to learn useful and productive behaviors. It isn't to hear boasts about how good the authors are good at using tools.

Even self-help books follow this pattern: Do this, expect that. They're not "Have you tried this too" or "I don't know about you, but I've got good results myself".


I am here to discuss my opinions on AI for software development because it's interesting. Not because I am selling a book or to prove anything to you.

If I had any special approach, I would be reluctant to share it with my potential competitors.

That said, I do not. It just works.

Meanwhile people here are posting the thesis that agentic development without careful code review results in an unmaintainable application.

I theorize that this is not something they experienced in practice, because it did not happen for me.


> Meanwhile people here are posting the thesis that agentic development without careful code review results in an unmaintainable application.

> I theorize that this is not something they experienced in practice, because it did not happen for me.

Are you currently maintaining the application? Like it's in production with paying users? You've only been on the app for 4 months. Compare that to something like Emacs that has been going for 40+ years. You can make a better case when you've been on prod for a few years.


By that standard, we could have AGI tomorrow, and I should still not comment.

No, my app is not published yet. It will probably take another month, with hopefully no complications arising out of the AppStore review process.

Then, I hope the ad campaign financials work out to compete with old apps of a lower quality that already boast no less than a million reviews.

I get it, you want me to make a case that can objectively convince you of the usefulness of agentic development without code review.

From my perspective, I have no interest in doing so, and I can only share my experience so far. In a few months time we will know more objectively whether my ambitions paid off.

Until then, you will either have to take my word for the quality of the product, or spend tens to hundreds of hours of effort in trying the approach for yourself. OP's article does not contain any specifics for where and how supposedly agentic development failed him either.


But can't you see how coming out with a strong statement like "i've been doing this, it works" before your app even has a single user and before you've had to contend with any externally filed bug reports and keep the app stable as you fix those and add new features isn't very reasonable?

If anything there are clear counter example to your claim, such as the major provider agent harnesses which are all almost always fully vibe coded, and riddled with bugs and regressions that make using them painful for users. The only reason people put up with it is because competition in the space is still limited.


Don't you think I've fixed bugs and kept the app stable during the 300 hours I have been working on it?

That's why I can say with full confidence that it works.

I doubt it will magically all fall apart the moment an external user touches it, or that I will expand the scope dramatically in the near future.

The agent harnesses are an interesting topic. I believe they have large teams shipping a ton of changes weekly. In that environment, is it realistic to expect rock solid software with such a feature set to be developed in a few months and shipped to 10M users?


> The agent harnesses are an interesting topic. I believe they have large teams shipping a ton of changes weekly. In that environment, is it realistic to expect rock solid software with such a feature set to be developed in a few months and shipped to 10M users?

Yes, the whole argument is that LLMs make shipping quality software at scale in months possible. You're arguing out of two sides of your mouth now. On the one hand, agents have enabled you to build a bullet-proof high quality app in a few months as a solo dev. On the other hand it's supposedly unreasonable to expect a team of engineers with lots of funding and lots of expertise to use those same LLMs to build high quality software in a few months.

The main difference is you are still working in a vacuum and the harness teams have actually shipped to users. Once you do that, you face significantly more challenges than you do tinkering in isolation. Don't claim a methodology works until you've actually proven so. "My personal closed source pet project that no one but me has ever seen works" is not convincing evidence. My pet dragon who is definitely real but that I can't show anyone else agrees.


> the one hand, agents have enabled you to build a bullet-proof high quality app in a few months as a solo dev. On the other hand it's supposedly unreasonable to expect a team of engineers with lots of funding and lots of expertise to use those same LLMs to build high quality software in a few months

I think you understand well that there is a major difference between developing a mobile app solo and 10-20 people working on a coding agent harness of vastly larger scope.

I don't intent to prove anything to you. I am telling you that it works for my mobile app development. Your arguments to the contrary are rather weak.


> you will either have to take my word for the quality of the product, or spend tens to hundreds of hours of effort in trying the approach for yourself

You're acting like everyone here doesn't have hundreds of hours of experience with LLM coding. We all do, we all know what it's like.

You're simply either lying or wrong. If it's the former, I don't care, you're just an asshole on the internet. If it's the latter, you'll learn eventually and it will be quite painful for you.


I doubt that.

I believe many of you use it at work, where you need to get code through review, or voluntarily review the generated code.

Otherwise I have no explanation as to how agentic development is failing for you, while it continues to work on my side in a large code base.


>You're acting like everyone here doesn't have hundreds of hours of experience with LLM coding. We all do, we all know what it's like.

But the opinions expressed are basically polar opposites, so there's clearly something to this.

The easy explanation IMO is that it takes some time to learn how to use LLM's effectively for system development. It's still skilled work, just different skills.

Some put in that effort and see results, others are annoyed that the reality doesn't match the hype and bail.

>You're simply either lying or wrong.

Surely it's possible that he was able to make it work even though you didn't?


more talk


> worked on it for an estimated 300 hours

If humans aren't needed why have you had to spend 300 hours?

I upvoted your comment BTW because I think you might be right, but I'm not sure. I still see people doing a lot of work, despite LLMs.


It's still a lot of work.

I have to prompt for the features, test them, then iterate until the UX is acceptable before I merge.

Usually I would juggle 2-5 topics in parallel, unless one of them demands more of my attention.

While there is no more code review involved, it is a lot of QA work and testing on device.

The bottleneck is that the AI does not have taste, does not know what the product should be, and would happily ship horrible slop without my intervention.

Other than the implementation itself there are other things that need to be handled: researching competitors, keywords, pricing, AppStore preparation, TOS and privacy policy, when do you show the rating prompt, translations, etc.

AI still helps with a lot of it, but it takes time and effort.


Not enough AI slop


“Wasteful desert paradise” and the author is a “bootstrapped SaaS finder”. Not exactly the greatest leap of imagination


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