And don't forget that they have BILLIONS of dollars and can't figure out how to get a decent support or public communications system setup.

Their outages are probably not due to their code though. It’s probably their infrastructure that can’t keep up. So seeing failures of infrastructure doesn’t really tell you anything about how good or bad Anthropic makes use of their models.

Well, people keep throwing money at them, including you and investors. So why would they care? It hasn't annoyed you or a large enough portion of users enough to move off their service - because there isn't a better alternative.

Not necessarily the parent's fault, but the energy of this thread is not my favourite...

They also don’t have…a login page with authentication . To access the console you get an email link. No passkeys, passwords, 2fa, just an email.

Infrastructure is a much harder problem. They can't even improve Claude Code, which eats 1GB+ of RAM. Meanwhile, my editor only consumes 80MB of RAM.

This comment is a good example of the double standard laymen have about AI usage:

If you use AI, then AI must be expected to solve all problems, even problems that affect everyone like infra scaling.

And if perfection isn’t delivered, then of course it wasn’t: you used AI and AI sucks.

Growing pains of being successful. These are solvable problems and will be. Can they maintain their momentum without pissing off too much of their customer base before these issues are resolved?

you're conflating a compute problem with a code quality problem.

Personally at my own job self-writing code is letting us tackle big, long-deferred refactoring projects (like the article mentions), but any sort of refactoring introduces new bugs.

Answers the question: how can Anthropic sell more Usage "Credits"

This is weird to me because i am using claude code 10+ hours/day 7 days a week, usually multiple sessions, and run into api errors maybe in 1 or 2 sessions per week. And about..2 major outages of 10-20min in the last month. Not terrible and nowhere near what you are reporting. Therefore I dont believe you, because you dont even couch this in terms of it being something that seems particular to you or your region. Obvious dishonestly is fairly bad of you.

Look, I've never been someone who mindlessly hypes AI companies, as a matter of fact I think they have serious leadership problems across the board, but you people are straw-manning them so badly it actually makes me sympathize with them.

They aren't saying they have fully automated luxury AGI, they specifically list the ways models fall short of that bar and caution against people taking the 8x figure as the actual uplift number. At the same time they recognize that 80% of new code is now AI-authored, when two years ago those models were little more than toys. And frankly that checks out: if two years ago you told me we'd have something like Opus 4.8/GPT 5.5 I would have rolled to disbelieve.

Better doesn't mean perfect.

The main reason I am building my own agentic environment is that I need full control and reproducibility of what I am building.

Post November and post openclaw agentic environments need to be built differently, and for selfhosting models the context size problem really requires a strong harness which intelligently helps reduce context size.

Planner/orchestrator architecture, agent to agent summarizer, specification based tools (fck all this markdown memory bullshit btw), tool call shrinking, and workflow management are all really important because of the context size problem.

Nobody has enough VRAM for the large K/V caches, and nobody can afford f16/f32 caches in terms of memory, which are also necessary for longer conversations. MoE 30b models have improved so much though, qwen 3/3.6 coder is the real champion doing almost the same things with less than 1/10th the memory requirements. Just think about that in terms of engineering and what your bet is going to be. Haiku pales in comparison.

Currently my focus with exocomp is trying to figure out how I can record, replay, restart, and debug workflow sessions of agents in a better manner so that I as a human can understand what's going on. Currently I think that UI will be something like a gantt chart where you have a graph with connections representing agent to agent communication. And yes, that's a lot of fiddling with SVG as it turns out, so I'm not quite there yet.

Anyways, in case you're interested. I'm manually building this env and trying to unit test the critical parts. [1]

[1] https://github.com/cookiengineer/exocomp

Indeed... why is Anthropic even employing people at all if this AI magic story is true?

We’ve got a company of several thousand employees serving hundreds of millions of people arguably the best AI model in the market. Meanwhile you’re asking for a handkerchief for your pool of tears because their product is struggling to do your daily job functions for you, with much of that due to being limited by the worlds supply of silicon, electricity, water, and other resources. Cry me a river.

[dead]

those are results of the humans only. not the AI. AI is perfect /s

Just as you expected, I'm throwing in my harness. Please support: https://github.com/rush86999/atom

Have you considered just... using OpenAI? They are more reliable, models are just as good, and their subscriptions provide more requests per dollar.

Opus 4.8's critical assessment of Anthropic's "When AI builds itself" [0][1]. Because, why not?

[0] https://pastebin.com/Vc5Yq9Ai [1] https://www.anthropic.com/institute/recursive-self-improveme...