Well, it's not like it never happened to me to "burn tokens" with some lifetime issue. :D But yeah, if you're working in Rust on something with sharp edges, LLM will get get hurt. I just don't tend to have these in my projects.

Even more basic failure mode. I told it to convert/copy a bit (1k LOC) of blocking code into a new module and convert to async. It just couldn't do a proper 1:1 logical _copy_. But when I manually `cp <src> <dst>` the file and then told it to convert that to async and fix issues, it did it 100% correct. Because fundamentally it's just non-deterministic pattern generator.

Not that I have seen, which is probably a big part of the disconnect. Mostly it's tribal knowledge. I learned through experimentation, but I've seen tips here and there. Here's my workflow (roughly)

> Create a CLAUDE.md for a c++ application that uses libraries x/y/z

[Then I edit it, adding general information about the architecture]

> Analyze the library in the xxx directory, and produce a xxx_architecture.md describing the major components and design

> /agent [let claude make the agent, but when it asks what you want it to do, explain that you want it to specialize in subsystem xxx, and refer to xxx_architecture.md

Then repeat until you have the major components covered. Then:

> Using the files named with architecture.md analyze the entire system and update CLAUDE.md to use refer to them and use the specialized agents.

Now, when you need to do something, put it in planning mode and say something like:

> There's a bug in the xxx part of the application, where when I do yyy, it does zzz, but it should do aaa. Analyze the problem and come up with a plan to fix it, and automated tests you can perform if possible.

Then, iterate on the plan with it if you need to, or just approve it.

One of the most important things you can do when dealing with something complex is let it come up with a test case so it can fix or implement something and then iterate until it's done. I had an image processing problem and I gave it some sample data, then it iterated (looking at the output image) until it fixed it. It spent at least an hour, but I didn't have to touch it while it worked.

> if you did /init in a new code base, that Claude would set itself up to maximize its own understanding of the code.

This is definitely not the case, and the reason anthropic doesnt make claude do this is because its quality degrades massively as you use up its context. So the solution is to let users manage the context themselves in order to minimize the amount that is "wasted" on prep work. Context windows have been increasing quite a bit so I suspect that by 2030 this will no longer be an issue for any but the largest codebases, but for now you need to be strategic.

Actually, 10000th

https://www.bridgemeister.com/fulllist.htm

I think it's also that the potential is far from being realized yet we're constantly bombarded by braindead marketers trying to convince us that it's the best thing ever already. This is tiring especially when the leadership (not held back by any technical knowledge) believes them.

I'm sure AI will get there, I also think it's not very good yet.

Respectfully, it's absolutely important to "gatekeep" a title that has an established definition and certain expectations attached to the title.

OP says, "BUT YOU DON’T KNOW HOW THE CODE WORKS.. No I don’t. I have a vague idea, but you are right - I do not know how the applications are actually assembled." This is not what I would call an engineer. Or a programmer. "Prompter", at best.

And yes, this is absolutely "lesser than", just like a middleman who subcontracts his work to Fiverr (and has no understanding of the actual work) is "lesser than" an actual developer.