And in China they were far more occupied with a cultural revolution than any form of advanced education. At best you could argue that they were teaching basic literacy to more people.
It did and didn't. Nix tools for building language-specific packages almost always wrap the language build tool/package manager. This can be easy or hard, depending on how onerous the build tool is for vendoring libraries.
What Nix and build tools need to agree on is a specification or protocol for "building a software dependency tree". Like, I should be able to say 'builder = cargo' in a Nix derivation and Cargo should be able to pick up everything it needs from the build environment. Alas, there is simply far too much tied up in nixpkg's stdenv for this to be viable, so we have magic stdenv builder behavior via hooks when a build tool is included in nativeBuildInputs.
I think one of the key problems too is that a system level dependency is managed by people dedicated to ensuring the chaotic nature of the package they are responsible for conforms to the way the OS they are maintaining for has proscribed.
There's no real way to do that at a language level - we cannot have "Go has determined the package you are trying to fix has not met the versioning requirements proscribed so you cannot submit the patch to fix it"
What language dependencies do is what OSes would think of as "unofficial versioning" that is, an OS will let you install and run an unofficial version of some lib (we've all been there, right, multiple versions of some core library because one doesn't work with whatever you are trying to install), but they will not manage it at all.
> Your customers don't care whether the failure was Google or Railway; they see your product.
Refreshing. So tired of businesses blaming their vendors. Oh it wasn't us spamming you text messages and emails, it was Shopify. Oh, our delivery guarantee said 2 days and it's been a week? That's not us, it's UPS.
I don't care. I didn't pay UPS or Shopify. I paid you.
Yep, the real strength of AI is less in replacing engineering skills, it's more in slashing all the time we spend not using those skills and doing low level research and data correlation tasks instead. Which isn't to say that those tasks aren't valuable in their own way, but in terms of raw output...
Just create a skill for it -> I call mine `babysit`. It spins up a subagent that polls it every x minutes and auto-fixes it until it's green. I already continue with the next task while it does that in the background
About 30% of our AI PR review checks are flawed at a fundamental level, based on poor comprehension of the whole. If I told the AI "fix everything and keep going until it's green" I would be terrified of the result.
I disbelieve this works in anything other than a toy codebase (or an incredibly fine-grained microservice).
The 70% is amazing! But a 30% failure rate requires intense supervision.
It is possible. I tell to use cli app, and for the agent to ad timer and check the status once in a while. Especially if there is something with a long wait. Also if it can run some validators/ same tools locally, would be much faster.
Might tend to deviate and waste time, needs guiding once in a while, and to check what is it spewing out, point it in the correct direction.
I treat the low level tasks as building blocks. You need a grasp and understanding of what is possible with them, but you do not need to remember the exact byte order and syntax. I think the idea is you should structure your workflow in a deterministic way, and just use Claude/ LLM as the interface. It is much easier and enjoyable to use high level language, where you give pointers to building blocks/ directions/ say hard no when you understand things deviate.
If I had to output the code myself, would take around 8 hours of constant writing to get around 1k LoC of code. For FUSE level tricky stuff, I might need to spend 3 weeks for 10 LoC. Very easy to burnout and build pain.
I love matrix-docker-ansible-deploy and use it for my homeservers.
I also bounced off this piece around halfway through when I realized it was mixed AI/human content. I can read AI output anytime I want. Show me your true self! :)
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