This is why I am a big fan of self-hosting, owning your data and using your own Agent. pi is a really good example. You can have your own tooling and can switch any SOTA model in a single interface. Very nice!

https://lucumr.pocoo.org/2026/1/31/pi/

My non-technical friend, never learned coding, doesn't know Linux, zero sysadmi experience does this and he can do anything and doesn't even know what Clause is doing. He learned some concepts recently like Docker, SSH, but that's basically it.

I find templates atrocious to use for component fragments like this, that's why I wrote a Python component library when I started using Django with HTMX. Order of magnitude more pleasant to use, works with _every_ Python web framework not just Django: https://compone.kissgyorgy.me/

It's just simple validation with some error logging. Should be done the same way as for humans or any other input which goes into your system.

LLM provides inputs to your system like any human would, so you have to validate it. Something like pydantic or Django forms are good for this.

I agree. Agentic use isn't always necessary. Most of the time it makes more sense to treat LLMs like a dumb, unauthenticated human user.

But hey! At least these four AI components made it in, so the important stuff is okay...

I simply forbid or force Claude Code to ask for permission to run a dangerous command. Here are my command validation rules:

    (
        r"\bbfs.*-exec",
        decision("deny", reason="NEVER run commands with bfs"),
    ),
    (
        r"\bbfs.*-delete",
        decision("deny", reason="NEVER delete files with bfs."),
    ),
    (
        r"\bsudo\b",
        decision("ask"),
    ),
    (
        r"\brm.*--no-preserve-root",
        decision("deny"),
    ),
    (
        r"\brm.*(-[rRf]+|--recursive|--force)",
        decision("ask"),
    ),

find and bfs -exec is forbidden, because when the model notices it can't delete, it works around with very creative solutions :)

This feels a lot like trying to sanitize database inputs instead of using prepared statements.

What's the equivalent of prepared statements when using AI agents?

Don't have the AI run the commands. You read them, consider them, and then run them yourself.

Why is that a good thing?

I don't think that the whole ecosystem should be dominated by a single VC backed startup.

I want my tools to be interchangeable and to play well with other choices.

Having multiple big players helps with that.

Maybe I'm wrong on this, but I rather have 1 tool everyone else is using. Cargo in Rust ecosystem works really well, everyone loves it.

Imagine if Cargo was not first-party, but a third-party tool belonging to a vc startup with zero revenue.

Then that startup makes rustup, rustfmt and rust-analyzer. Great, but I would be more comfortable with the ecosystem if at least the rust-analyzer and rustfmt parts had competitive alternatives.

I strongly disagree with the author not using /init. It takes a minute to run and Claude provides surprisingly good results.

If you find it works for you, then that’s great! This post is mostly from our learnings from getting it to solve hard problems in complex brownfield codebases where auto generation is almost never sufficient.

/init has evolved since the early day; it's more concise than it used to be.

I think (hope) it's meant to be a joke.

Scott Hanselman have a good blog post about this suggesting you should detach yourself from your code: https://www.hanselman.com/blog/you-are-not-your-code

Especially true when working as an employee where you don't own your code.