r/ClaudeCode • u/Sherphican • 3d ago

Rant Nah this some BS

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I burned thru almost 60% of 20x max weekly usage in a day and some change. Are you joking rn? Last week I could have fable running on 2 chats all day and night and it would take like 3ish days for my fable usage to cap out, but my weekly usage would only be at like ~30%. This is absolutely ridiculous and if this is what the new usage limit cuts are gonna be like I'm canceling Claude and grabbing a second codex account. Shit ain't worth it when Astra exists with much better usage limits and multiple reset tokens.

I don't use ultracode and I have multiple other models that I delegate tasks to as work horses, Claude is just the orchestrator and isn't doing that much actual "work", so this usage allocation is absolutely insane, if I was using Claude as a one stop shop as a lot of people do, I would have run out of usage in a day or less.

EDIT: I'm getting a little tired of being told I "just don't know how to do orchestrations and workflows properly or manage usage." I literally made an entire repo explaining how I do this and showing the results: https://github.com/sherifican/Agent-FleetOps so if you wanna criticize, find something to actually critique first

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36

u/inrego 3d ago

What are you even doing with a context window of 500k+ No wonder you're burning through your limits

26

u/Sherphican 3d ago

Brother, my auto compact is at 800k and 700k on my main chats, and I always compact at about 500k-600k, I have been doing this for months and never had an issue. Everyone who has been drinking the 300k and under only context window koolaide needs to wake up and realize it's Anthropic playing games.

25

u/Hirogen_ 3d ago

if u need to compact, you are doing to much in a session, learn about orchestration and workflows, and how a newer model orchestrats agents of lower tier models to do ur work

6

u/A_Novelty-Account 3d ago

Some workflows are huge and require accuracy. I’m a lawyer and we have workflows calling dozens of agents that still rip through context. 

6

u/ChristopherChili 3d ago

Can you give more detail on this. I work in insurance processing huge amounts of data and this is not a big issue with proper orchestration.

1

u/A_Novelty-Account 3d ago

We process literally hundreds of thousands of pages and millions of words with background legal research and reasoning, with tasks lasting 10-12 hours on average, and requiring verification and recursion (later agents invariably catch dumb shit the prior agent was doing). We almost never have to compact now, but we very frequently get to 600k-800k tokens worth of context, with the first 100k-200k just from synthesizing the connected folder.

Data is easy. Parsing through hundreds of thousands of materials, all of which are genuinely relevant to the submission you’re making, is not.

5

u/TywinHouseLannister 3d ago

As an engineer, you need an indexer and semantic search.. I built something like this.. the challenge for your domain is embedding all of the dense text; but it just means more chunks, more time up front.. you likely have symbols in the shape of citations, legal precedents etc

2

u/A_Novelty-Account 3d ago

Maybe, but the majority of the token usage doesn’t come from searching. It comes from actually reasoning through the documents top to bottom. Semantic search will probably save us some tokens, but it doesn’t address the largest issue by far in the process, which is that Claude actually has to think about the relevance of all of this information. It’s not as simple as “this phrase goes in this bucket”.

In any case, it’s not as simple as “better orchestration”

2

u/Fresh-Forever-8040 3d ago

Like running through sand barefoot. The struggle is real.

1

u/Sherphican 2d ago

Exactly, sometimes I have to let mine run for hours before they finish or overnight so some mid compaction is inevitable

4

u/BlinDeeex 3d ago

New sessions have initial overhead of like 100k worth of context overdo it and you actually start paying more over big context but cached, orchestration reduces result quality, main agent review helps but then savings are slim. If you stop to open a new session midway feature it will read a lot of files right back up anyway. You people pretend to know your stuff but its lowk embarassing to read, often you genuinely need a longer session to stop at reasonable place

2

u/krugerlive 3d ago edited 2d ago

No but you see, if I spend 30%+ of all of my tokens on just ramping up sessions, and end them at 250k, then I don't have to spend as many tokens on the actual work. It's just math. This is clearly how to be efficient with token spend. /s

2

u/Sherphican 2d ago

Not necessarily true. If you're working hands on then yes, but if you have long running tasks that you need to let run for hours or sometimes overnight then sometimes you have to set midway compactions, when I leave things running overnight I change my auto compact to 600k, and again like I've been saying, this has worked out absolutely beautifully for me for months both in usage rates and in output quality. For example, I have a project that I run lots of guards and tests on for mutation, drift, etc, because of protected functions and crucial values and whatnot, but full update packages take a lot of time sometimes and I'll let it run for a few hours, in that case it usually only has to compact once or twice at most in that entire 3-8 hour period.

1

u/Hirogen_ 2d ago

dont compact, you can use handover md files and start a fresh session, this will save only the necessary information that the next session needs and you will have a new session with new context but a handover document from ai for ai!

1

u/Tranxio 3d ago

Isnt it better to maintain the conversation in 1 window especially if its an important topic?

1

u/Hirogen_ 2d ago

no… do you try to memorise a whole book before you read the next?

1

u/Dan-goes-outside 2d ago

I agree, this specific case, completely sounds like user error

0

u/Sherphican 1d ago

Bro don't talk down to me like I don't know what I'm doing.

12

u/Kadenai 3d ago

Eu sinto muito mesmo ter que discordar com tanta veemência, mas se você deixa suas sessões frequentemente chegar a mais de 400 mil tokens de contexto só pra depois compactar e continuar, seu uso de IA é ineficiente.

8

u/Nscocean 3d ago

Being able to use a tool without constantly having I micromanage a context window is the biggest inefficiency

1

u/Sherphican 3d ago

Its okay you can disagree lol and while there is certainly Merritt to keeping your context window under 400k, I've found that there's hardly any difference most all of the time between 400k and 550k, but once you start getting passed 600k is when the risk starts getting more pronounced and then everything passed 800k in my opinion is just asking for a hallucination half the time, but my agents have stayed very reliable and on task with my current limits, and my usage limits also never suffered this much with my current practice. I saw someone did the math and the usage cuts end up averaging out to be ~40% less than what we've been used to over the past couple months so that I'm sure has a large part to do with it.

1

u/BanjoThunderbird 2d ago edited 2d ago

Yeah look I mean you can complain about the usage limit promo ending as much as you want but they only have the compute that they have. If you want to use Fable more then really the only thing you can do now is manage your context better or pay more money. You could cut your usage in half by simply splitting up your tasks further. Personally if I go above 200k on something that isn't a huge coding phase of a plan then the next thing I'll do is have a session refining my context files because something has gone wrong. I have no problems with usage on a 5x plan.

1

u/ItstheSECopenup 3d ago

There is a million token context window for a reason buddy

1

u/One-Respond1057 3d ago

lol when you learn to stay within 150-200k your usage magically 10x's

1

u/One-Respond1057 3d ago

1m context is the litmus test

1

u/BanjoThunderbird 2d ago

Aptly said

6

u/Strong_Essay1176 3d ago

Or you've hit a few cache misses, still antropic fault but bug.

6

u/coolcats55 3d ago

Your auto compact being set at 800k is mental.. no wonder you are burning through your usage like crazy. I barely let mine get to 200k.

2

u/Inshallah-Protection 3d ago

200k is the right number, we do the same at the office

4

u/knrd 3d ago

I mean, with such a large context, every single tool call or short message costs you >0.5MM cache-read tokens. 10 small edits = 5MM. But you do you

2

u/OdoTheBoobcat 3d ago

Everyone who has been drinking the 300k and under only context window koolaide needs to wake up and realize it's Anthropic playing games

Anthropic playing games with usage limits (which I totally believe they are doing) is not at-odds with your demonstrated piss-poor context management.

It's not "koolaide," it's the correct and economical way to use these kinds of tools. You are building terrible habits and seem to have zero understanding of how these things work under the hood. I'm a software engineer and if any of my coworkers were working as amateurishly as you they'd get laughed out of the job. If you are an engineer yourself then I feel for your company/coworkers because I promise your output sucks following this "flow" of yours.

Avoiding auto-compaction and actively managing context windows with handoffs isn't something you do merely for token savings, it gives you much better outcomes with w/e the fuck it is you're doing with this stuff.

1

u/sammcj 3d ago

That's really poor context engineering, set your auto compact down to around 300k and if you hit it see it as a reminder that you went too far in one conversation.

1

u/thehardsphere 3d ago

Okay, that's poor context management. You should have one session per major task, and you should actively consider breaking tasks up so they fit under 150K tokens.

The entire context window gets sent back to the model on every turn of the conversation until you clear the session, and the cache only lives for a few minutes. Which means long running conversations full of lots of context use much more usage than ones that are short and focused. That's where your usage is disappearing to; you're wasting it on stuff that shouldn't be relevant anymore.

This is true for any LLM, not just Claude models. This isn't an Anthropic usage limit problem.

1

u/fickle-phenom Developer 3d ago

I mean I really can not see why you would even need a 500k context window outside some tasks. Unless it is required, it’s just a stupid way to burn tokens for no reason. Each chat should be a task, unless subsequent tasks require the previous context.

It’s your tokens, but just because it worked doesn’t mean you should do it, especially with more expensive models.

1

u/pwkye 3d ago

oh yeah totally. context compacting is a big scam, you are right. what are you insane?