Technology

This is a sane way to use LLM. Also, pick your poison, some bots are better than others for a specific task. It's kinda fascinating to see how other people solve coding problems and that is essentially on tap with a bot, it will churn out as many examples as you want. It's a really useful tool for learning syntax and libraries of unfamiliar languages.

On one extreme side of LLM there is this insane hype and at the other extreme a great pessimism but in the middle is a nice labour saving educational tool.

It regurgitates old code, it cannot come up with new stuff.

The trick is, most of what you write is basically old code in new wrapping. In most projects, I'd say the new and novel part is maybe 10% of the code. The rest is things like setting up db models, connecting them to base logic, set up views, api endpoints, decoding the message on the ui part, displaying it to user, handling input back, threading things so UI doesn't hang, error handling, input data verification, basic unit tests, set up settings, support reading them from a file or env vars, making UI look not horrible, add translatable text, and so on and on and on. All that has been written in some variation a million times before. All can be written (and verified) by a half-asleep competent coder.

The actual new interesting part is gonna be a small small percentage of the total code.

Yea, I use it for home assistant, it's amazingly powerful... And so incredibly dumb

It will take my if and statements, and shrunk it to 1/3 the length, while being twice as to robust... While missing that one of the arguments is entirely in the wrong place.

I mean, originally they thought they had come upon a magic bullet. Turns out it wasn't the case, and now they're going to suffer for it.

From my experience, AI just seems to be a lesson in overfitment. You can't use it to do things nobody has done before. Furthermore, you only really get good responses from prompts related to Javascript

I think right now companies are competing until they're only 1 or 2 that clearly own the majority of the market.

Afterwards they will devolve back into the same thing search engines are now. A cesspool of sponsored ads and links to useless SEO blogs.

They'll just become gate keepers of information again and the only ones that will be heard are the ones who pay a fee or game the system.

Maybe not though, I'm usually pretty cynical when it comes to what the incentives of businesses are.

This struck upon one of the greatest wishes of all corporations. A way to get work without having to pay people for it.

From what I've seen and heard, there are a few factors to this.

One is that the tech industry right now is built on venture capital. In order to survive, they need to act like they're at the forefront of the Next Big Thing in order to keep bringing investment money in.

Another is that LLMs are uniquely suited to extending the honeymoon period.

The initial impression you get from an LLM chatbot is significant. This is a chatbot that actually talks like a person. A VC mogul sitting down to have a conversation with ChatGPT, when it was new, was a mind-blowing experience. This is a computer program that, at first blush, appears to be able to do most things humans can do, as long as those things primarily consist of reading things and typing things out - which a VC, and mid/upper management, does a lot of. This gives the impression that AI is capable of automating a lot of things that previously needed a live, thinking person - which means a lot of savings for companies who can shed expensive knowledge workers.

The problem is that the limits of LLMs are STILL poorly understood by most people. Despite constructing huge data centers and gobbling up vast amounts of electricity, LLMs still are bad at actually being reliable. This makes LLMs worse at practically any knowledge work than the lowest, greenest intern - because at least the intern can be taught to say they don't know something instead of feeding you BS.

It was also assumed that bigger, hungrier LLMs would provide better results. Although they do, the gains are getting harder and harder to reach. There needs to be an efficiency breakthrough (and a training breakthrough) before the wonderful world of AI can actually come to pass because as it stands, prompts are still getting more expensive to run for higher-quality results. It took a while to make that discovery, so the hype train was able to continue to build steam for the last couple years.

Now, tech companies are doing their level best to hide these shortcomings from their customers (and possibly even themselves). The longer they keep the wool over everyone's eyes, the more money continues to roll in. So, the bubble keeps building.

AI is a financial scam. Basically companies that are already mature promise great future profits thanks to this new technological miracle, which makes their stock more valuable than it otherwise would be. Cory Doctorow has written eloquently about this.

When the AI bubble bursts, even janitors and nurses will lose their jobs. Financial institutions will go bust.

for me it typically don't cause syntax errors, but the main thing it fucks up is what you specifically told them to do, where the output straight up does not perform the way your specification requires. If it's just some syntax errors at least the compiler can catch them, this you won't even know if you don't bother testing the output.

I've used Claude code to fix some bugs and add some new features to some of my old, small programs and websites. Not things I can't do myself, but things I can't be arsed to sit down and actually do.

It's actually gone really well, with clean and solid code. easily readable, correct, with error handling and even comments explaining things. It even took a gui stream processing program I had and wrote a server / webapp with the same functionality, and was able to extend it with a few new features I've been thinking to add.

These are not complex things, but a few of them were 20+ files big, and it manage to not only navigate the code, but understand it well enough to add features with the changes touching multiple files (model, logic, view layer for example, or refactor a too big class and update all references to use the new classes).

So it's absolutely useful and capable of writing good code.

I've seen and used AI for snippets of code and it's pretty decent at that.

With my colleagues I always compare it to a battery powered drill. It's very powerful and can make shit a lot easier. But you'd not try to build furniture from scratch with only a battery powered drill.

You need the knowledge to use it - and also saws, screws, the proper bits for those screws and so on and so forth.