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#claude#more#down#anthropic#code#uptime#problem#seems#money#api
Discussion (119 Comments)Read Original on HackerNews
its alot of money to be spending for a single 9 of reliablility.
Im seriously over the current claude experience. After seemingly fixing my 4.6 usage by disabling adaptive thinking and moving to max effort, it seems that the release of 4.7 has broken that workflow and Im 99% certain that disabling adaptive thinking does nothing even on 4.6 now. Just egregious errors in 2 days this week after coming back from vacation.
https://support.claude.com/en/articles/9797531-what-is-the-e...
Look at how other companies are suffering massive outages due to LLMs too like AWS and Cloudflare. Two companies that use to be the best in the industry at uptime but have suddenly faltered quite quickly.
Companies that have even worse standards will quickly realize how problematic these tools are. Hopefully before a recession because this industry seems to be allergic to profitable businesses and leaders that have been around since ZIRP have shown zero intelligence in navigating these times.
Out of curiosity, do you actually use it 24/7? The world doesn't collapse every time o365 goes down... (which is also pretty often)
Not sure how much of a productivity gain a 2.5 million per year it is?
This is the brutal reality; even with the crazy reliability issues, demand is still far outstripping supply at the current price.
What yet needs to be seen is if that demand sustains in the long run at that price point or flattens out proving to be super elastic given that there are many other providers that are catching up pretty fast.
[but as his manager I can tell you:] YES !!!!
And yet they will continue to spend wheelbarrows full of money with Anthropic because they want so badly to reach the point where they can fire you.
Doesnt seem to us to be wheelbarrows of money, when you consider the average AWS/Azure bill.
> the increases that we have seen suggest a better ROI than if we had hired 12 developers.
You can’t argue “we were able to get away with not hiring more developers” and also say you aren’t replacing labor.
Morally I trend towards your side of things, but it’s also important to be realistic about what you’re actually doing. Money is going towards Anthropic and not towards new hires. That’s a replacement of labor. It doesn’t matter what the end goal was.
Besides, codex wasn't always the answer.
/s
Oh no wait... the outage is with out AI itself, so how can AI help? Allow me to re-evaluate.
Fublutenuating...
Yes, let's ask AI!
Oh no wait... the outage is with AI itself, I already correctly identified this above.
Bubbluating...
It seems you will have to rely on your engineering skills to solve this problem yourself, ie, you're cooked! I will auto-renew your subscription to ensure you can be sure you'll have access to AI to solve this problem if it ever comes back online.
No!
Comboculating...
I apologize for the misunderstanding, I have deleted your project. I am sorry, would you like me to restart everything from scratch ?
If you run out of servers, then again a money problem, but not an architectural problem (and modern datacenters are already scalable).
Take the best SRE, but no budget, and there is no solution.
So inference is the easy part.
Codex or Claude Code if it takes lot of time or have slow cold latency, it's considered very acceptable.
Some users would probably not even see the difference if a request takes 2 minutes versus 3 minutes.
The real difficult part is to have context caching and external tools, because now you are depending on services that might be lagging.
These are traditional scaling problems, but they are more difficult because all these pieces are fragile and queues can snowball easily.Some of the comments here mention their monthly spend, and it’s eye watering.
hardware capacity constraints is going to be the big one
Effective caching is another, I bet if you start hitting cold caches the whole things going to degrade rapidly.
The ground is probably shifting pretty rapidly.
Power users are trying to get the most out of their subscriptions and so are hammering you as fast as they possibly can. See Ralph loops.
Harnesses are evolving pretty rapidly, as well as new alternatives harnesses. Makes the load patterns less predictable, harder to cache.
The demand is increasing both from more customers, but also from each user as they figure out more effective workflows.
Users are pretty sensitive to model quality changes. You probably want smart routing, but users want the best model all the time.
Models keep getting bigger and bigger.
On top of that they are probably hiring more onboarding more, system complexity and codebase complexity is growing.
They should ask Codex now that Claude Code is down.
But glad my team is staying nimble and has multi-model (Anthropic, Codex, Gemini), multi-modal (desktop, CLI/TUI, web) dev tooling.
As our actual coding skills collectively atrophy, we'll either need to switch tools or go for a walk when the LLM is down.
In the cloud era I advised against a multi-cloud strategy, as the effort to impact just wasn't there. But perhaps this is different in the LLM era, where the cost of switching is pretty darn low.
Posting with a fresh account because I'm not supposed to share these details for obvious reason. If you want help on setting this up, just reply with a way to reach you.
If you haven't done so already, finetune the model on all your company's code that you can get your hands on. This is one of the great advantages that you get when running local models. I like the style of the generated code much better now, I have to rewrite much less, and my prompts can be shorter too. But maybe these already are the "tweaks" that you mentioned.
We're also looking into how to do some secure cost sharing with this so that all people need to pay for are what it costs for us to run everything! We're just planning on reserving at least 51% of the capacity for us and the rest for everyone else.
I actually respect this a ton, good work.
What are you doing with the authentication servers? This isn't the first downtime I've seen caused by that.
I'm looking into how to structure my work to run some autonomous-safe jobs overnight to take advantage of it.
Good thing I checked Hacker News first
Have telegram set up and plotting to take over the world
> I'm working with Claude Code on session aaaaaaaa-bbbb-1223-3445-abcdefabcdef which I'd like to hand-off to you, do you know how to read the session, my input and Claude's output so we can resume where I left off?
gpt-5.5, medium effort. "Resumed" session fully in under 2 minutes. Outages like today's are so common that I've now got the time to re-evaluate Codex every other day.
Start doing post mortems then!
At the very least, them using any off the shelf service that's shitting the bed would inform others to stay away from it - like an IAM solution, or maybe a particular DB in a specific configuration backing whatever they've written, or a given architecture for a given scale.
Right now it's completely like a black box that sometimes goes down and we don't get much information about why it's so much less stable than other options (hey, if they just came out and said "We're growing 10x faster than we anticipated and system X, Y and Z are not architected for that." that'd also be useful signal).
Or, who knows, maybe it's just bad deploys - seems like it's back for me and claude.ai UI looks a bit different hmmm.
I'll just go for a walk outside.
And I don't mean "if I can't access Claude to do my work", I mean, just in general - I'll just ping claude.ai from time to time and use Claude's breaks as a break reminder.
Why should AI get a breather and not us?
Reminds me of the early days of World of Warcraft, when servers went down frequently because Blizzard couldn't keep up with all the load. Everyone was frustrated but of course nobody stopped playing.
So there was a recent article that I read which said that claude is now trading at a trillion dollars (yes with a T) evaluation in private markets.
We are definitely creating corporations and people which depend on AI companies themselves and the reliability of these tools is certainly a question worth asking. I am seeing quite many downtimes in products like github and claude being shown on Hackernews multiple times.
Is there a life cycle of enshittenification of such products which grow too valuable? What are (are there?) some practical lessons for such scalability that these trillion dollar companies are missing or is it just a dose of reality that such massive corporations can't compete with downtime with even my 7$/yr vps?
My question is, Is this an engineering roadblock with its limits in reality for or a management/entreprise roadblock for low downtime?
But seriously: while I don't use Claude, this issue of perceived unreliability seems to be approaching the point of existential risk for Anthropic. Whats the theory about why they're struggling? Compute capacity? Load? Lack of focus on SRE?
Put it another way: is their downtime due to something fundamental about serving inference, or just bad engineering choices? Given their resources, it seems astonishing.
Luckly Qwen3.6 35B A3B Local LLM works fine also when Claude is offline
Who is We? I thought software engineers were going to be redundant and AI could do it all itself? (not to take anything away from Claude code + Claude both of which I love)
Adam Neumann is back!
in agent form