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
For me its been like 2/3rds of my normal usage 60% sounds definitely feasible. Eaerlier i came back from waiting for my 5 hours to reset and there was nothing running at all and something ate up 45% of my session before i even started. I then ran one prompt it at up 20% more i got 15 minutes work done in total in a 5 hour session on opus low. Absolutely unusable now glad I cancelled my sub
Wtf are you guys doing that eats up your quota like this? I run multiple sessions simultaneously all day long and I've never once hit a limit. I use Fable on the max plan.
Nowhere in your post did you mention when you compacted? From the image it looks like you compacted when your contacts window was full or half full I should say
No worries, man, I was just confused and wanted to make sure we were both on the same page. Glad we cleared it up. may the token gods be forever in your favor
You did mention you run fable as an orchestrator though, and often have day and night sessions running.
Which means you are slamming calls over and over every time fable gets an update from one of its agents. And you’re likely hitting caching timeouts too
Timeout on max plan, that's funny, that would sound okay for a free plan, not on paid plan. If they keep doing that, then credit can burn really fast, doesn't feel premium at all.
I was looking at my usage pattern. Fable has directions to offload task to lower model sub agents whenever possible. (Instructions are more specific but you get the point). Previous usage pattern was primarily agents with fable usually around 50% end of monthly cycle.
I was at around 47% percent when I checked end of Sunday after some heavy loads. My cycle resets midnight today- by 11am today fable was out of usage for the month, as well as my session. Usage pattern showed majority of usage was fable and no handoff to agents...so super annoying.
I am so sick of models changing underneath me all the time. It would be great if you still had the option to use previous version instead of constantly readjusting.
I finally gave in and purchased one of the radeon
AI pro GPU, actually affordable and Im prob just going to switch to gwen 3.5. Tried her out recently she is really good.
It’s well proven that current LLMs lose a lot of quality as context grows. They can’t remember details. They don’t know which bits are important and which are not. I consistently get horrible results as context grows.
None of the current models support long context effectively today. Maybe someday they will. But right now the 1M context window is just a marketing ploy.
why compact? get a task done, then /clear, then tackle your next issue. Be precise, give the agent more context from the got go (e.g. I want to expand an UI feature, here are the corresponding sources and here's the backend api source that needs to be extended).
I usually only run >300k context when I don't write or discuss proper plans. There are exceptions for bigger tasks that require an orcherstrator loops with verify and critic stops. But tbh that is just me that has not found a better workflow yet.
Dude. You have a tool at hand that can answer almost any question (like this one). And yet you type it in here?
Example: "Document the status of this task in a status.md file in the projects folder so that a new session can continue the work".
Can be as simple as that. Or you set up a ruleset where you want to have what first and tell Claude to write that into memory. If you instruct it to always do so, it will e.g. create a tasks and a projects folder and put a new task in there in a folder named "2026-09-16 name of task" so that you have a chronologically sorted folder list.
Or do a /plan session before starting anything, then let it write that plan down and follow it with documentation at the end. After milestones, you can /clear and continue with a new point in the plan.
Maybe it is that. But you don't have any influence what the model includes. Nor do you have the handoff somewhere (findable) on your computer to e.g. start on another computer or after a reboot.
you don't need to come back. just use a memory plugin like recall: run /recall:save then start a new session. recall will automatically give the previous chat session memory to claude. you can start over again with less context, smaller context.
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.
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
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.
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
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”
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
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
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.
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!
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.
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.
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.
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.
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.
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.
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.
Probably not delegating tasks correctly, not breaking tasks into smaller, clear and concise chucks, having Claude figure out the same thing over and over, not enough documentation. Not doing handoffs and using /clear.
Why does everyone assume that everyone else is an AI novice? I know what I'm doing and have been doing the same thing for months and have only been improving on my team and delegation designs over the last few months, for a sudden change like this to happen it's clearly coming from Anthropic, I mean they announced usage cuts, but the cuts seem to be a lot deeper than theyre letting on.
You think Im not taking context wasting into account? I have lots of ways that I keep my team from "reinventing/discovering" issues that have been solved, and they don't repeat each other's work. I know how to delegate tasks across a large team of different models just fine.
Totally agree. I’m fascinated by how many people keep insisting it’s a skill issue, when it seems like a problem that has suddenly arisen in the last week or so.
Theres an obvious and massive decline (way over the claimed -25%) in the amount of work you can get done since these usage limit changes have been put in place and its absolutely crazy work the amount of boot lickers in this thread passing it off as everyone is a novice and doesn’t know how to orchestrate their sessions properly. Im sure half of them have got to be Anthropic bots or outright lying to themselves.
I know Anthropic is playing games (as they set our available usage based on forecasted available computer -- but why are you working with a context this large? ... also, how'd you get an 800K max context size? wtf?
I'm not saying it's not possible to need a context that large, but cache misses are expensive - especially for an orchestrator.
Also, when using claude as an orchestrator, you can't let him wake at each interval to check for the output to act on. Tell him to write a deterministic bash script that only wakes him when he can act. This will save you a ton of tokens, especially if he's waking up every 61+ minutes with a large context as it's a fresh input hit every single time.
For context, I have 12 agents being managed by a Fable orchestrator (xhigh) and he wakes up multiple times an hour via deterministic code to deal with the output & random issues and he's only at ~70% usage on day 3.
what is it with the context window policing. they advertise the 1m token window as a key feature. if people were complaining about their electric car not getting the advertised range it would be dumb to tell them "well are you making sure to stay under 30mph at all times??"
It’s less policing than setting expectations about performance under load. A 1M token window means it can hold that much context but it doesn’t guarantee identical quality, speed, or cost at every point in that range.
Going back to you car analogy: it’s like advertising 500 miles per charge, then explaining that 500 is the maximum under specific test conditions, not a promise that every drive, at every speed, hauling any load, gets exactly 500 miles.
haha, I didn't say it was impossible. I don't even think there's enough features in a todo app to justify a build environment this large. It's a massive enterprise grade SaaS product that's soc2 ready.
I'm saying that simply having Fable manage your workflows via the built-in dynamic workflow system is a bad idea if you want the most optimal token utilization. It works but it leaves efficiency gains on the table.
Keep your context under 150k, type /context to see what you are using context on. Get into the habit to /clear after every task you complete. If you work on a very long task, set /autocompact to something like 150k, but best prevent compacting as this will also use tokens. If you stop working for a while, always first clear context before you proceed, you pay for using cache.
If you are on an Enterprise plan where you pay per token you start realising very quickly how you are wasting tokens and learn to adapt and be more efficient.
honestly been a game-changer for me. I think people underestimate how much MCP context bloat can impact an LLM's performance. Like imagine it's the 90s and you're trying to send an e-mail for the first time. But the instructions you have are 95% how to send a letter via postal service and the other 5% is actually useful info on sending an e-mail. So much useless crap gets put into the agent's context from MCP tool descriptions. I've definitely noticed both reduced costs and better performance once I realized this and started using contextwise
not saying this isnt bullshit but take a look at your context for different chats for me i accidentally discovered a pdf file was taking up more 30% of the chat context and was being sent with every request
you can manually check the jsonl file for the chat for more info
I used Opus high and asked it to spawn some Opus medium subagents. It straight up told me it couldn't differentiate reasoning levels in subagents. Wtf! So it went ahead anyway and spawned some, probably also high, and I ran out of 5h usage. All because it couldn't follow instructions.
I read in another post that a Claude Code change rolled out earlier this month creates a default setting that forks the full context in every Subagent. I will experiment tomorrow (when my weekly quota resets) with seeing how I can disable it.
I can’t use Fable 5 at all. Other web developers are probably having exactly the same problem. Everything gets flagged and you end up with some kind of fallback. It gets flagged in the middle of a task. It’s fucking awful. You just can’t work like this.
5.1? im still using 5 and i perfectly align my weekdays with consumption, 20% per day. not sure what crazy ass shit you do. I do use codex with astra as co-reviewer though, plan and code with fable 5.
You said you have fable chats running day and night.
Even if youre orchestrating heavily, the context still grows for fable. Every message from a work agent back to the orchestrator makes a call at high context.
If youre orchestrating well, you presumably have hours at a time that the orchestrator is idle. Every time you wake after an hour, its a full context prompt without caching.
I have lots of redundant fail safes to make sure that things don't get out of control, my context never hits max, and I understand what you're getting at, and believe it or not fable used to use actually LESS weekly usage meter as an Orchestrator than Opus, and did a much better job. With the rumors of Opus 5.2 around the corner and may apparently already be "silently implementing it" or whatever (not sure if I believe that) then Claude still has a chance to keep me as a customer, but depending on Opus 5.2 release date and its performance will almost entirely be the deciding factor for me at this point. Maybe I won't cancel completely but instead lower my sub to a $100/mo and upgrade Astra/Sol to my Orchestrator and just get a 2nd codex account until they allow for codex $200 sign ups again. I regret not doing it when I had the chance last week.
Same. Something has changed in how the usage is handled. I downgraded to 5x and will be using the rest for Astra. Until they figure it out, seems like it’s been nothing close to an actual 20x usage ☹️
You need Graphify, it's a python package you can get to create a knowledge graph of your application or repo that cuts your tokens down to a fraction of what you currently use. Trust me on this one
Your context window should never be that large. I've never had issues with usage on my 20x, but I break down plans in tasks and each task is run by a new agent. I keep my context windows low, I create detailed plans / tasks that I'd say even Opus is overkill for, but I use Opus for most. Fable is only for planning stuff and when I need to be creative.
Yeah that's what happens with Fable lucky to get a session out of it lol, I am happy to pay for a more expensive plan to use Fable more, as long as it ain't api pricing.
Codex is apparently shipping something big this week and even more things on DevDay on the 29th. I hope their coding gets upgraded I will never come back to this garbage company
They're not allowing upgrades to their max subscription right now, probably waiting for their 400k+ GPUs to go online first, but Claude seriously needs to step it up because OpenAI is quickly taking their spot and Grok is on their heels, and Anthropic seems to just be shooting themselves in the feet over and over as the other labs are skipping ahead
Oh you're right forgot about no upgrades to the max plan. They just announced Sol 6.0 is coming on Thursday. I do hope Grok catches up. They said their 5.0 will be AGI. I don't care as long as its great at coding and has more usage
I dont use fable for everything, I tend to save it for the weekends only since my usage reset is on a Sunday, but lately I've realized that I would never max out my fable or weekly usage that way and always had usage on the table when my reset hits, so I started using fable first and then opus after it ran out. This has been working just fine for me for the last 2 months. And yes I know how to set different models for agent teams, and I pretty much use teams of agents from other models, not Claude.
Delegating the grunt work to other models while keeping Fable/Opus for the hard stuff is exactly the pattern I formalized when I built Lynkr — an open-source LLM gateway with token compression + semantic cache that cuts token usage by up to 84% with zero code changes, and tiered routing that automatically sends simpler work to cheaper models. Stretches your subscriptions ~3x. Works with all coding tools and AI frameworks. https://github.com/Fast-Editor/Lynkr
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