Why stop there? We could eliminate all external dependencies and even build our own compiler and OS, since the cost of rolling own solution has apparently gotten so low, right? Sometimes I feel like I'm living in a completely different dimension from some of the commenters here.

Yet they were pretty quick to change Lake Ontario to Lake America. OTOH, if Apple has no idea what its own app is serving, that shows poor state of their monitoring system, right?

The reason why it became second nature for you is this hand-rolling, manual work. I observed that with math - unless you manually practice problem solving (integrals, differential equations), you might know the mechanics but you'll have hard time solving them. And that knowledge of mechanics will also fade away at some point.

> LLMs have changed the equation. It used to take me 2-3 hours to write a parser for a moderately complex grammar. Now, if I hand an LLM a loosely written, BNF-ish grammar and ask for a recursive-descent parser, it finishes the job in five minutes. At this point, writing them by hand is hard to justify

So, what is the difference between LLMs generated "manual" parsers vs those with parser generators, beside that with LLM that will be done in five minutes + plus some $$ and with parser generators you'll get that for free and under a second?

> Which makes me wonder: what’s the appeal of PEGs or parser generators now? They used to make sense when hand-writing wasn't practical, but what compelling reasons are left to use them today?

The appeal is predictability - use i.e. Bison, feed it with grammar and you'll get always the same output. Not so much with LLMs.

Perhaps they simply don’t advertise it and investors (currently) love companies that spend heavily on frontier models. That said, OW models, especially when combined with RAG, work quite well, and given the current state of the industry, they may be the only sensible way to keep inference costs under control.

Why? It is a great PR to build a hype, especially before the IPO, showcasing how AI is "self-aware" and dangerous, essentially resurrecting Sam Altman's talk about how only a few should hold the keys to this (opening a route to regulation, which is his ultimate goal).

Also, collusion.wiki was recently registered and it looks too vibe-coded for my taste, so let's see will that domain be alive in a year or two.

If your account is that valuable, it's time to consider moving to a self-hosted option. Or at the very least, start by purchasing a domain and linking it to your Google account, while keeping offline backups of all your emails and documents.

The real problem isn't that Google might accidentally ban you; it's that there's no way to get a human in the loop to review the issue. My client is an enterprise GCP user paying a hefty sum every month and getting someone knowledgeable typically means wading through Gemini or talking to (non-technical) support who just read GCP documentation back to you; and it can take months something to get resolved. Now imagine the situation for someone paying nothing or a double-digit for their gmail account or workspace.

I'm aware people will complain that self-hosting is hard, insecure, etc. but it's like a backup: an annoying process you truly appreciate when shit hits the fan.

This is highly debatable. They look better, but whenever I inspect the walls and see what is holding the house together, I just shrug and leave my contact info, because I know I’ll be called to fix the mess.

> ...and building them increasingly feels like magic.

Engineering should not feel like magic to those with a proper education. Otherwise, we are merely practicing alchemy.

[1] https://www.youtube.com/watch?v=IHD8BDFYyGI

Why is that ironic? Since Mimir is open-source, $0 revenue users are expected. AFAIK, Grafana Labs relies heavily on go, typescript, and linux, without necessarily being their top financial contributor. They could have kept Mimir proprietary like Splunk, but whether that would have attracted the same level of adoption or community contribution is another matter.

Exactly! For instance, we had pull-based monitoring 20 years ago (Zabbix et al), but we abandoned it because it scaled poorly, favoring push-based agents (for InfluxDB, KairosDB etc). Now Prometheus is all the rage, yet we’re hitting the exact same scaling walls these systems had before. In a few years, we’ll rediscover push agents and call them the best thing since sliced bread.

Modern IT has become a ubiquitous commodity, much like the car. You don't need to know how an engine works to drive; while that knowledge might make you more efficient, it isn't strictly necessary to get from A to B. Besides, most twenty-two-year-olds ten years ago didn't know how to use ssh, either.

However, if you want to call yourself an engineer (and work in the field), you must understand the underlying mechanics. IMHO if you want to defeat a competitor today, you don’t need industrial espionage - you just have to cut their internet and/or AI subscriptions. Modern vibe engineers would struggle to function.

> The man page is dead for most users. The RFC is unread by most developers who depend on the protocols it describes.

Well, those who are accustomed to using man pages still use them today. I find them far more accurate than whatever an AI might spit out at any given moment. As for RFCs, they were always read by a small population - either those implementing the protocols or the few of us who like to brag about obscure technical details.

> You can now write complete programs without understanding what a single line of them does... until something goes wrong in production at two in the morning and you are completely without tools to respond.

I’m not worried about this. When things go south, there will still be experts who will know how to fix them. But since those experts will be fewer and farther between, they will likely charge $1k/hr, and rightfully so. If you are in that field, more power to you! :D

[1] https://orgmode.org/worg/worg-about.html - Worg is a collaborative knowledge database about Org (Emacs org-mode).

"I’m not a mechanical engineer, but I watched a five-minute YouTube video on how a diesel engine works, so I can tell you that mechanical engineering is a solved problem."

And it’s worth reiterating that most (all) of these LLM/AI providers are currently operating at significant losses. If they aim to become even modestly profitable, prices will have to increase substantially.

Dollar dominance gives the US disproportionate leverage over global finance and allows it to shape the rules of the system. Absent this asymmetry, it is difficult to imagine US tariffs or financial pressure (or any kind of pressure) would carry comparable global impact.