Engineering practices or best practices are much more than writing code.

So not sure what we are debating here: I see first hand companies jumping full on using LLM for _everything_ for the last 6 months (of course Anthropic longer) and without guardrails and good engineering practices the number of incidents, downtime is increasing.

Look at status.claude.com - Anthropic could at any point come out and say all those are due to third party providers.

I am also not saying here Anthropic is worse than other scaleups. But they do something different: they come in front of us and tell us they have better engineering practices.

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hombre_fatal 4 hours ago | parent [-]

> Anthropic could at any point come out and say all those are due to third party providers.

Why can't it be simply the case that Anthropic is struggling by their own accord? Infra scaling isn't a solved problem, much less with new, complicated, ever-changing, stateful LLM requests.

Pretty much every API-service-centric company I've worked at was in some constant state of either triaging or thinking about infrastructure health, often due to the familiar cascading problems of a necessarily distributed system.

But now with the AI scapegoat, we rewrite history to pretend us humans solved infra scaling, so any issues today must be caused by AI and any related superstitions we want to tack on.

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gls2ro 3 hours ago | parent [-]

> Why can't it be simply the case that Anthropic is struggling by their own accord?

They can and it is normal. I have said it is normal for scaleups specifically at a similarity growth rate.

What we (or at least I) critique here is coming out in the world and announcing that coding is done while having a product that has a status page full with red stripes. Yes, could be infrastructure, could be third party integrations could be a lot. But a lot of what is there is software. And yes, some parts is hardware. Unless the root cause is culture. In that case as I mentioned in another comment there I give them that: LLMs cannot solve culture.

Again the difference here is that the other scale-ups with similar _scaling_ issues are not talking about how we should all just use LLMs for everything and that learning to code is not required anymore.

So I am not saying the real issue is not infra or integration with third parties. What I am pointing at is: "don't talk that you don't need engineering while you - yourself - have engineering problems that need engineering solutions and still have not solve them".

Also you are getting out of your way to brainstorm possible root causes that will let them get away with this cognitive dissonance (or is there a better them in communication). Let them do the explanation and defend their position as they are the ones attacking the computer science engineering.

	▲	hombre_fatal 3 hours ago \| parent [-]
		> Again the difference here is that the other scale-ups with similar _scaling_ issues are not talking about how we should all just use LLMs for everything and that learning to code is not required anymore. > Let them do the explanation and defend their position as they are the ones attacking the computer science engineering. This once again boils back down into: because they make claims about LLMs being good, I get to make any claim I want, and if if they didn't want me to make my claim, they shouldn't have made theirs. It seems reactionary rather than earnest. You've accused me and someone else of "brainstorming" reasons why they might have infra scaling issues, but I'm not. I'm pointing out that everyone has them especially pre-AI, and all of those reasons are on the table, not less likely. You have done the opposite: committed to a suspicion. That is the end result of the thought-terminating cliche.