Badabinski

OpenAI has a trillion dollars in financial obligations they need to meet by 2030. I doubt Clear Channel’s financial obligations were in the same order of magnitude.

I’ll say that given the way OpenAI and Anthropic have hideously overextended themselves (they have over a trillion dollars of financial commitments to companies like Oracle), it’s not impossible that the current crop of American LLM providers do just kinda… poof away. Traditional banks want nothing more to do with them, they’re getting majorly spooked. All that needs to happen is for private credit to lose confidence in them, which is already happening. When they’re out of cash, they’ll be on the hook for an absolute ridiculous amount of money and they’ll probably just get liquidated.

I’m sure there will be new companies that pop up, but they’re going to have to charge 10x what Anthropic is making enterprise customers pay, since inference likely still isn’t profitable at the price Anthropic is charging.

I don’t use LLMs as a knowledge base because if the problem is bad enough for me, I’m likely just grepping through kubernetes source code or something. That being said, I don’t necessarily have an issue with folks using an LLM that way as long as they fully understand exactly how bad it is at what it does. You’ll be fine if you lose access to LLMs, and that’s the number one thing in my book. Your friend? Not so much.

(As a fun bonus to all of this, Oracle is very likely to die if OpenAI can’t meet its commitments. Either way, Larry Ellison will probably stop being a billionaire, since almost all of his wealth is in Oracle stock).

The speed and ease at which LLMs allow you to generate code is a bug, not a feature in my opinion. In my org, a group of 3 very junior engineers wrote a 5k line shell script for building k8s clusters according to our business specs and it’s fucking awful. The actual time to get it out the door was short, but now it’s basically impossible to change it without fucking up like 20 different things. The fucking thing will randomly quit because the shit ass LLM thinks set -e is a good thing to use, and it’s full of unused variables everywhere. I had to add a feature to it (which is how I learned of its existence), and I spent a miserable week just reading the entire fucking thing so I could ensure that my change wouldn’t cause an oil refinery in the North Sea to explode due to a butterfly-effect series of bullshit.

The frustration and toil you feel as a software dev is a feature. If something is making you mad and is taking forever to write, that’s a sign you probably need to change your approach. If you’re using an LLM to write a bunch of boilerplate, why not just eliminate the boilerplate or like, make a factory to spit out a bunch of it or something? Your discomfort is a powerful tool and you are not best served by ignoring it. Those junior devs would have written something much better if they had been forced to experience the true toil and suffering of writing a 5k line shell script.