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I assume Docker Compose v2 from Docker.

Well, is this Podman's "service mode" also fully compatible with Docker Compose file functionality though?

That's an Ubuntu issue though, they ship lots of outdated software. Nginx, PHP, PostgreSQL, Podman, etc, the critical software that must be updated asap, even with stable versions they all require a PPA to be properly updated.

It's works great until you need that one option from Docker Compose that is missing in Podman Compose (which is written in Python for whatever reason, yeah...).

Podman compose isn't compatible with Docker compose, end of story.

ASRock has Zen 5 CPUs dying with stock settings from brief core voltage spikes on idle (max core frequencies). I believe either PBO has to be enabled to allow undervolting headroom or VSOC has to be permanently fixed to a value lower than 1.2V.

Are they out of their minds? How can a tiny startup without their own actual product (nowadays anyone can strap OpenAI/Anthropic API or fork open source models, such as Deepseek, on top of web scraping) buy the largest browser used by billions made by a company making trillions?

Gitlab is an easy way to scale things related to code. There's also this new thing Radicle.

I can't imagine searching with Google these days unless it's something very niche. Even free AI with web search are marginally better, even with the traffic spam they create, Google Search has made itself unbearable.

>URLs up to ~2000 characters

Exactly, this approach doesn't scale well without trickery involved. You have to have some sort of weird encoding in place to compact it down.

Somewhat solved by type annotations + a good static type checker, such as pyright (it's 2025, there must be type annotations everywhere), and dynamic cases (very rare, probably due to poor or unfortunate design decisions) can be solved with validators, e.g. the aforementioned Pydantic. This isn't a silver bullet, but it works really well.

An easier/moderate approach: make a proper base DTO model, which can be extended by validators, such as Pydantic, and the db model is the Domain is just whatever an ORM offers/dataclasses.

Apart from dataclasses (which generally should have slots and/or be frozen), this article gives way too much inapplicable advice, which is not scalable even in a small sized project.

Yeap, self-reinforcement learning is missing in LLMs.