Wrong. These are always humblebrags about how good their ability to learn from their mistakes is, and how robust they were before, and how they are even more robust now.
The ones that are "deeply embarrassing" simply aren't posted.
> letting AI do what it's good at, while constraining the overall system to follow the right practices, is like the ideal combo
What constraints? What right practices? What ideal combo? Maybe this whooshed over your head but I was sarcastically pointing out that just because you can do something doesn't mean it's a reasonable engineering practice or, uh, an "ideal combo."
This is really good - miles ahead of almost all other math writing I have read. One particular thing I really liked was the explanation of the determinant. When I was in college I spent a very long time trying to get some intuitive explanation for a determinant of a matrix and the best I could get is that you just multiplied and subtracted some numbers and poof there you go. I KNEW there had to be some more comprehensible explanation and it drove me crazy that people just parroted textbooks without any real understanding.
This reminds me of that silly video everyone was shown in middle school about inverting a sphere :-)
I am very curious how it was written (will there be a write up to the write up?!). It feels likely AI assisted, but this seems to me to be the best possible use of AI -- crunching out a bunch of visualizations of complex ideas so that they are easy to understand just by looking. The writing also feels a little AI written but definitely feels very human-assisted.
But surely at some point you need to stop, right? Most web developers are perfectly capable without understanding the intricacies of the file system or OS, even though the browser sits on top them. Most engineers don’t know assembly, or transistors or electrical engineering. Steve Jobs didn’t know every line of Objective-C that went into OSX. I don’t think Michelangelo collected all his paint materials by hand when painting the Sistine Chapel. In some sense I don’t understand a lot of the panic around AI when the entire career progression of what it means to be a software engineer has simply been to deal with ever-increasing levels of abstraction.
> Most web developers are perfectly capable without understanding the intricacies of the file system or OS, even though the browser sits on top them.
This will mess you up if you ever need to store a significant amount of files on the file system directly, or even deal with resource usage for batch processes, or have to dig into non-trivial transaction handling when dealing with DBs without having learnt enough about them, or even the whole domain of SQL and query optimization that ORMs will not protect you from and so many other things.
I don't think you need to know everything, but you definitely need to learn.
> But surely at some point you need to stop, right?
I guess, but typically due to your own lack of curiosity or mental exhaustion, or even limited time to spend on something, rather than the new knowledge and skills not being good to have. At least knowing when AI is heading in the wrong direction for any given domain will save your bacon.
The issue is reliability. I don't need to know the implementation of the database or the lower levels of the network tasks because I trust that they works well. A bug that affects me has a very low chance of occurring and the main risk is me not reading or understanding the docs.
With AI generated systems, no one knows what's going on. Not even the AI. When an issue pops up (which has a very good chance to happen because of the complexity of integrations), debugging it can be like reverse engineering obfuscated assembly code.
To be blunt the degree to which I take these projects seriously is basically the same as how extensive their eval suite is. A single guided refactor is better than nothing, but one success could just be a fluke. I want to see hundreds, if not thousands, of evals to convince me you’re a project worth looking into.
The AI generated text is also not doing you any favors.
I see a pretty big gap between finding software vulnerabilities and “the world is about to end”. It is literally true that AI models are finding software vulnerabilities. It is also to my mind a reasonable thing that you’d want to be cautious about rolling out a model that can find more vulnerabilities. So what is the objection you have to these sources?
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