Comment by m_ke | Hacker News Reader

Comment by m_ke | Hacker News Reader

I've been thinking about this a bunch and here's what I think will happen as cost of writing software approaches 0:

1. There will be way more software

2. Most people / companies will be able to opt out of predatory VC funded software and just spin up their own custom versions that do exactly what they want without having to worry about being spied on or rug pulled. I already do this with chrome extensions, with the help of claude I've been able to throw together things like time based website blocker in a few minutes.

3. The best software will be open source, since it's easier for LLMs to edit and is way more trustworthy than a random SaaS tool. It will also be way easier to customize to your liking

4. Companies will hire way less and probably mostly engineers to automate routine tasks that would have previously be done by humans (ex: bookkeeping, recruiting, sales outreach, HR, copywriting / design). I've heard this is already happening with a lot of new startups.

EDIT: for people who are not convinced that these models will be better than them soon, look over these sets of slides from NeurIPS:

- https://michal.io/notes/ml/conferences/2024-NeurIPS#neurips-...

- https://michal.io/notes/ml/conferences/2024-NeurIPS#fine-tun...

- https://michal.io/notes/ml/conferences/2024-NeurIPS#math-ai-...

> that do exactly what they want

This presumes that they know exactly what they want.

My brother works for a company and they just ran into this issue. They target customer retention as a metric. The result is that all of their customers are the WORST, don't make them any money, but they stay around a long time.

The company is about to run out of money and crash into the ground.

If people knew exactly what they wanted 99% of all problems in the world wouldn't exist. This is one of the jobs of a developer, to explore what people actually want with them and then implement it.

The first bit is WAY harder than the second bit, and LLMs only do the second bit.

Sure, but without an LLM, measuring customer retention might require sending a request over to your data scientist because they know how to make dashboards, then they have to balance it with their other work, so who knows when it gets done. You can do this sort of thing faster with an LLM, and the communication cost will be less. So even if you choose the wrong statistic, you can get it built sooner, and find out sooner that it's wrong, and hopefully course-correct sooner as well.

except how do you know that the llm is actually telling you things that are factual and not hallucinating numbers?

>3. The best software will be open source, since it's easier for LLMs to edit and is way more trustworthy than a random SaaS tool. It will also be way easier to customize to your liking

From working in a non-software place, I see the opposite occurring. Non-software management doesn't buy closed source software because they think it's 'better', they buy closed source software because there's a clear path of liability.

Who pays if the software messes up? Who takes the blame? LLMs make this even worse. Anthropic is not going to pay your business damages because the LLM produced bad code.

Good points - my company has already committed to #2

What's the equivalent of @justsayinmice for NeurIPS papers? A lot of things in papers don't pan out in the real world.

There's a lot of work showing that we can reliably get to or above human level performance on tasks where it's easy to sample at scale and the solution is cheap to verify.

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