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Comment by maegul | Hacker News Reader

> Ironically, the best answer to many of the article's suggestions (thousands rather than millions, easy to modify, etc.) is to write your own software with LLMs.

Not sure exactly irony you mean here, but I’ll bite on the anti-LLM bait …

Surely it matters where the LLM sits against these values, no? Even if you’ve got your own program from the LLM that’s yours, so long as you may need alterations, maintenance, debugging or even understanding its nuances, the nature of the originating LLM, as a program, matters too … right?

And in that sense, are we at all likely to get to a place where LLMs aren’t simply the new mega-platforms (while we await the year of the local-only/open-weights AI)?

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> Surely it matters where the LLM sits against these values, no?

Yes, I agree, but it's all trade-offs. The core problem is this:

1. Software is very expensive to write

2. So, you need to sell to as many people as possible

3. So, you need to add lots of features to attract as many people as possible

4. And you need to monetize it with ads, data-selling, and SaaS subscriptions.

5. But that makes software complicated, brittle, and frustrating.

LLMs can break the cycle if they make it cheap to write software. Instead of buying a mass-market product with 10x more features than you need, you create custom software that does exactly what you need and no more.

But aren't we trading one master of another? Instead of bowing down to Microsoft/Meta/Google, we bow down to OpenAI/Anthropic/Meta/Google? Maybe, but when an LLM writes code for you, you own the code. The code runs outside of the LLM (usually) on an open platform.

But what if you have to modify the code? Then you ask an LLM (maybe not the original LLM) to modify the code. That's far easier than asking Google to modify Gmail.

If you believe in the suggestions of the author, then I don't think there is a better answer than LLMs. We don't live in a world where everyone can solve their software problems by forking some code, much less modifying it themselves.

And the reason I think it's ironic is because I suspect the author hates LLMs.

> 1. Software is very expensive to write

I disagree with this, right at the start. I think software is cheap to write but expensive to maintain when you try to sell to as many people as possible. It's the OpEx that kills you, not the CapEx. I go into this more in the current state of https://akkartik.name/about

So I wrote OP to encourage more exploration of the alternative path. If you build something and don't keep adding features to it in a futile attempt at land-grabbing "users" who will for the most part fail to pay you back for the over-investment your current VC-based milieu causes you to think is the only way to feel a sense of meaning from creating software -- if you don't keep adding features to it and you build on a substrate that's similarly not adding features and putting you on a perpetual treadmill of autoupdates, then software can be much less expensive.

I plan to just put small durable things out into the world, and to take a small measure of satisfaction in their accumulation over the course of my life. The ideal is a rock: it just sits inert until you pick it up, and it remains true to its nature when you do pick it up.

> LLMs can break the cycle if they make it cheap to write software. Instead of buying a mass-market product with 10x more features than you need, you create custom software that does exactly what you need and no more.

That's the critical question, isn't it. Will LLMs yield custom software that does exactly what you need and stabilizes? Or will they addict people to needing to endlessly tweak their output so AI companies can juice their revenue streams?

What skills does it take to nudge an LLM to create something durable for you? How much do people need to know, what skills do they need to develop? I don't know, but I feel certain that we will need new skills most people don't currently have.

Another way to rephrase the critical question: do you trust the real AIs here, the tech companies selling LLMs to you. Will the LLMs they peddle continue to work in 10 years time as well as they do today? If they enshittify, will you be prepared? Me, I'm deeply cynical about these companies even as LLMs themselves feel like a radical advance. I hope the world will not suffer from the value capture of AI companies the way it has suffered from the value capture of internet companies.

Lots of interesting questions here.

> I think software is cheap to write but expensive to maintain

OK, but I think you're agreeing with me. Regardless of why it is expensive, it drives companies to bloat their products (to increase their market) and to exploit dark patterns (to increase unit revenue).

If software were very cheap to create and maintain, then it would break that cycle.

> if you don't keep adding features to it and you build on a substrate that's similarly not adding features and putting you on a perpetual treadmill of autoupdates, then software can be much less expensive

In the 90s Microsoft found that people only used 10% of the features of Microsoft Excel. Unfortunately, everyone used a different 10%. At the limit, you would have to create a separate product for each feature permutation to cover the whole market.

And of course, creating and maintaining 10 different products is more expensive than 1 product with all the features.

> I plan to just put small durable things out into the world

This is great! Actions speak louder than words and you'll learn a lot in the process.

> Will LLMs yield custom software that does exactly what you need and stabilizes?

I agree that this is the critical question. No one knows (certainly I don't). But let's say the goal is to create custom software that does exactly what you need. Is there a practical path to that other than via LLMs? I don't think so.

> do you trust the real AIs here, the tech companies selling LLMs to you

I think this is orthogonal to whether the tech works at all. But, in general, yes, I trust most tech companies to provide value greater than the cost of their products. Pretty much by definition, for all the software I pay for, I trust the companies to deliver greater value. When that changes, I stop paying and switch.

And, of course, I support all the usual government regulators and public/private watchdogs to hold corporations accountable.

I think the differing stances towards tech companies might be the crucial axiomatic difference between our positions. I've just lived through 30 years of reduced regulation of Tech, and it's hard to imagine a world that reliably prevents that from recurring.

> In the 90s Microsoft found that people only used 10% of the features of Microsoft Excel. Unfortunately, everyone used a different 10%. At the limit, you would have to create a separate product for each feature permutation to cover the whole market.

They were approaching this from the other side, though, of already having built a ton of features and then trying to fragment a unified market. It doesn't work because from Microsoft's perspective the goal of Excel is market control at the cheapest price, and giving each user their 10% is more expensive.

But if you shift perspective to the users of Excel, you don't need to care about market control. If everyone starts out focusing on just the 10% they care about, it might be tractable to just build that for themselves. The total cost in the market is greater, particularly because I'm not imagining everyone using the same 10% is banding together in a single fork. But that becomes this totally fake metric that nobody cares about.

My approach involves throwing an order of magnitude more attention at the problem than people currently devote to computing. But a single order of magnitude feels doable and positive ROI. If everyone needs to become a programmer, that's many orders of magnitude and likely negative ROI. That's not what I'm aiming for.

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