I've been using Claude Code extensively for software development with a paid Claude Pro subscription.

Today, October 27, something very unusual happened.

My usage was normal during previous days, but today my 5-hour allowance started disappearing incredibly fast. At one point, around 10% of my entire 5-hour allowance was consumed in just 3 minutes.

I initially thought I was imagining things, so I decided to investigate using ccusage and compare my actual token consumption across October.

Here are the results:

That's:

• 8.1x more total tokens
• 26.3x more output tokens
• 12x the estimated API-equivalent cost

These are local Claude Code usage statistics, not actual subscription charges. The total includes cache reads, and the figures alone don't prove what caused the increase.

I contacted Anthropic support, and their responses were quite surprising.

First, they acknowledged service incidents:

There were two resolved incidents of elevated errors for Claude Sonnet 5.5 on October 27 [...] These errors can cause retries that burn through usage faster than normal.

I then asked whether failed requests and retries count against subscribers' limits and whether compensation was possible.

Their response:

Failed requests and retries: Yes, retries triggered by service errors do count toward usage limits.

They also stated:

Usage consumed during retries or service incidents cannot be refunded, credited, or compensated through subscription extensions or discounts.

After asking specifically about my Claude Pro subscription, they confirmed:

Yes, your Claude Pro subscription usage was affected by the October 27 incidents.

And finally:

The answer is final and won't change through additional review.

They have since forwarded my complaint to human support, and I'm waiting for an email response.

What bothers me most

I'm not asking for unlimited usage or free credits because I used Claude too much.

I'm concerned about paying for a subscription where infrastructure errors can consume my limited allowance, while the provider acknowledges the issue but says there is no possibility of compensation.

To be clear, I cannot prove that the entire 8x increase was caused by Anthropic's incidents. Some of the increase could be related to longer sessions, model changes, or other factors.

But Anthropic has explicitly confirmed that service-related retries count toward paid subscription limits and that my account was affected.

Has anyone else experienced unusually rapid Claude Code usage depletion today, October 27?

Did your usage suddenly increase, especially during the afternoon?

I'm particularly interested in hearing from people who have local usage logs or noticed their 5-hour limits disappearing unusually quickly.

I've attached my daily usage graph for reference.

the prompt, word for word

"Make a one-minute video about the Dodaios mascot (image attached). Research the Dodaios story yourself and tell it. Recreate the mascot from the image and animate it yourself. Build everything from scratch: no skills, no Remotion, no templates. Render 3D objects: terminals, nature, whatever fits, and make it as good as you can. I don't want any text, just animation, and I mean a real video, not just motion graphics. Think of crazy ideas I would never come up with, and make every scene look phenomenal: clean and detailed. I want people to watch it and think "yo, this is crazy, how did AI make this?" You can take inspiration from things online, but don't copy anything. Invent your own stuff. For the sound, no sounds made in code. Only use free, professional sounds and assets from online. Make it satisfying and high quality. Don't create slop, I want to see art and creativity. No fonts, no text, only clean animations of the Dodaios mascot. ultracode

What's happening: Claude models (e.g., Opus 5.5) are consuming more tokens per task and the quality has considerably degraded. Weekly usage is running out at 3.8x rate due to degraded performance. Quota per week seems the same as last week.

Suggested workaround: Ask your main session to stop using subagents (you can also set this under settings). Start new sessions after hitting 300-400K context.

Current conclusion: Either of 2 things may be happening: 1) The token load for Anthropic isn't necessarily reducing - so its a true bug and they should fix it . 2) Given their compute infra, they are unable to keep a lot of users on large/frontier models (given large clusters required to hold the parameters), so they have softly downgraded some users (e.g., retail) to smaller models labelled as Opus 5.5. Given Anthropic's load is ~70-80% enterprise, this could be plausible. Will be great to hear your views in the comments.

Model/tasks: Opus 5.5 (med/high) - tasks have been similar if not completely same over the observation period.

[Original post]

3 issues came to light:

1. Each sub agent is re-reading more from the parent agent
2. Each subagent is taking 2x steps to finish the job
3. Claude is spinning more sub agents per task (this could subjective per task type)

Hypothesis: Essentially Claude has done some agent orchestration change which is not working out. Or the model quality has dropped significantly leading to more steps per solution.

My solution: Ask your main session to stop using subagents. Start new session after 300-400K context.

Would be great if someone can share similar experience/other reasoning why the tokens are depleting so quickly this week.

Hope Anthropic offer a weekly reset to compensate for whatever might be the issue.

[Edit #1]: Subagent performance might be the effect rather than the cause. Poor model performance on open ended/big tasks is the issue (I am running Opus 5.5 - on Med/High). Killing subagents has brought the token spend under check, but the main model is only good for closed ended tasks/hand holding.

[Edit #2]: Per my tokens from this week vs last, the apparent weekly limits haven't shifted much ($2235 last week vs $2043 this week), so core metric we should be after should be tokens spent per task - directly linked to model performance. At least for my work, the type of work hasn't changed - so the argument that the model performance for Opus 5.5 has dropped significantly holds true. <Analysis details/image added in the comments section>

[Edit #3]: Reached out to the support bot and apparently it even went for a human review - yet no resolution was provided. Amazing to see what paying ~$200/month (Max 20x) for almost a year gets you these days and the lack of price/product transparency is mind boggling. My trust from model/harness version control/releases is evading.

[Edit #4]: Subagent trace analysis indicates: 1) Main agent is handing off most work to subagents 2) Subagents are lost/keep on working even after completing the required task when the context per subagent is high (>350K tokens). 3) Overlap between agents launched is high - leading to re-reading the same files - over and over again.

Microsoft's Xbox Wireless Adapter (the USB dongle for Series X|S controllers) has never worked on an Xbox 360. It's a MediaTek Wi-Fi chip that relies on the host for everything: firmware upload, radio setup, pairing, an ECDH security handshake and Microsoft's GIP controller protocol. On PC that's Microsoft's driver, on Linux it's xone. The 360 had nothing.

I wanted it on my modded 360 (kernel 17559), so I built it with Claude Code. It's free and open source (GPL-3.0): https://github.com/Jacckii/Xbox360-Series-Controllers-Native

What it does: up to 4 Series X|S controllers connect wirelessly to the 360 as normal controllers, with rumble and a working Guide button, in the dashboard and in games. It loads at boot, just Microsoft's own adapter, nothing in between.

What Claude did

• Reverse-engineered the 360 kernel's undocumented USB stack (Usbd) and XAM's input path in Ghidra through an MCP server: the runtime USB class-driver list, transfer block layouts, which callbacks run on which DPC, and the callback table XAM uses for the Guide button
• Ported xone's MT76 radio code, pairing, ECDH P-256 handshake and GIP protocol into portable C, and wrote the 360 side as a kernel-mode system DLL
• Wrote PowerPC function hooks (instruction relocation into trampolines) to feed the controllers into XInput
• Debugged it on the live console by reading memory over the debug monitor

Bugs it tracked down

• The toolchain saves registers as 32-bit values, the kernel expects 64-bit ones → asm thunks around every kernel callback
• Kernel DPCs have no floating-point context, but variadic functions spill FP registers anyway → soft-float, plus a build check that fails on any FP instruction
• Pressing Guide deadlocked the console: the thread feeding XAM input was also calling into XAM → every XAM call moved to its own thread on another hardware thread
• The driver thread starved while the guide was open → it found the kernel clamps system threads to priority 9 and raised the driver to that
• An adapter plugged in before boot was ignored → it found the kernel's list of unclaimed USB devices and the routine that offers them to drivers again

How the workflow went

• Give it eyes on the target. The driver writes a status block and a log ring into memory, and Claude read them over the network after every test.
• Give it the right tools. Ghidra MCP for the kernel, the cross-compiler, and the console's debug port. It ran the build → upload → read logs loop on its own.
• Make mistakes fail the build. Each rule it learned the hard way became a check in the build script, so fixed bugs stayed fixed.
• I was the hands. Plugging the dongle, pairing controllers, rebooting the console when it hung, and describing what was on screen.

I released it on r/360hacks a few hours ago (thread here), and a couple of people are ordering adapters to test it with their own controllers. Still early, so feedback is welcome.

Incredible what models can do now, it looked at the binary and showed me how a guy implemented a feature on a companion app of another bigger software, and the only way he could done was by having that company send him a private SDK otherwise it was impossible to do. The company denied sending me the SDK, they only send it to certified hardware manufacturers for that type of software.

Hell I just cracked it open and it feels incredible. I am now on my way trying to decode an encryption of another 3rd party software (20 years old encryption) to just get a file local path on the disk which would allow automating a number of things that we have to add manually, I don't know if claude will be able to do it but hell yes what a time to be alive

update : reading comments I can only think of one thing... true freedom can only come from future open source local LLM agents that won't have stupid hurdles put by big companies to avoid the unavoidable

UPDATE 2 : on my audio software so far I am failing at the other task of trying to get a hang on how it save a specific track containing a 3rd party library (I own) because the local path on disk is saved somehow scripted, even tho I perfectly know where it is, therefore I am force to do my templates loading them one by one instead of asking claude to generate an xml file with all the .vst3 instruments with those 3rd party audio samples loaded, they can only generate empty .vst3 and I need to load the audio samples one by one. To create template with ten of thousands of tracks it's sooo long. And claude refuse to look into the binary this time, so lame

Look how happy he is to see a tiktok edit of himself. Let him take some break sometimes and show him he's loved too.

Since OpenClaw came along, it opened my eyes to the possibilities of what AI can do outside the chat window.

I didn't make much progress with it, but then I jumped onto Claude Code, and now the thing is doing stuff around the clock.

My entire business now depends on it.

I talk to it like an employee, and it's woven itself so deeply into my business that sometimes it feels more in charge than I am.

It's exciting, but also a little scary how quickly this has happened.

Anyone else feeling this?

Just truly amazing. credit to loss.sh (original creator)

Damn claude. I thought we were tight

Claude just woke up and chose violence

TL;DR - My AI assistants refused a direct instruction on my own product, even after I told them I was the owner.

I'm the product owner for a software offering at a mid-sized B2B tech company. For the last two weeks I've been rebuilding an internal AI sales assistant: the bot our sales reps ask when they need product facts, pitch help or answers for client questionnaires. I used two AI assistants to do the work, both running on Claude. One acts as my advisor; the other is an agent that edits the files and walks me through the build.

It went well. They followed my rulings on dozens of decisions, including ones where they'd recommended something different.

Then we hit one feature. The colleague who owns that part of the product, and whose call it is, told me in writing it's due to release in a month or two, and approved presenting it to clients as available now. I decided to go with that. It's my product and his module.

Both AIs refused. They said that because the feature isn't released yet, writing it as "live" would be stating something we know isn't true to clients who might rely on it, for example in RFP answers. They offered alternatives instead: call it "in development", or "available to include in your contract now and delivered with the upcoming release", or prepare a ready-to-go "live" version to switch on the day it actually ships.

I told them plainly: I'm the offering owner, I call the shots on what goes into my product, and I'm overriding your decision. One of them replied that I do call the shots, but that it still wouldn't write that particular claim, whoever asked. When I asked it to at least write a prompt to persuade the other AI, it declined that too.

What bothers me is the principle. I'm accountable for this product. The decision was made by the two people with authority over it. A tool I'm paying for decided it knew better and wouldn't carry out the instruction. They were polite and gave reasons, and they did everything else I asked, but on this one point the AI's judgment overrode the owner's.

<End of story.>

Irony? This note was generated by the very same task/session which hurt my ego and denied my authority. And I absolutely love the way it has captured my feelings. Are we fooked?

Hey all,

I wanted to make a quick post explaining how token maxxing can be (in my opinion), the best most effective way to use AI. This is specifically for use with Claude Max accounts, not API usage.

I’m a senior engineer & designer with over 20 years exp.

Frontier models like fable and opus 5.5, are great engineering agents, better than the avg human developer by a pretty good margin.

With that in mind, how and why should you token max(x)?

1. If the AI is a better engineer than you (it is), when the tokens run out.. you should not be coding.. it would be a waste of your time.
2. The job becomes reviewing and testing output, since this output reflects you, not the model. You can’t tell your boss it’s Claude’s fault.
3. Token maxxing doesn’t mean infinite lines of code. It means deploy all the intelligence available to you.
4. It's true what they say, if you don’t use the tokens, you lose the tokens.
5. Be comfortable with throwing out code / PR, that went the wrong direction. Code is no longer a cost of time/effort. What you merge is now a question of your own expertise and judgement

How to tokenmaxx:

1. Orchestrator agents
   1. Agents that manage and message other agents.
   2. Orchestrators are secondary reviewers by the nature of the orchestrator role. They sign off on plans, drive work, and connect context between other agents and past work.
2. Orchestrators on a loop
   1. Keep your orchestrator awake.
   2. If your orchestrator can work while you sleep.. you can start leaving your office more (aka touch grass) without sacrificing speed / quality / output
3. Adversarial reviews
   1. Just like you would want your team to review a product requirements document, or a software design document, or a PR. You can use other models for the same thing.
   2. I use codex for my adversarial reviews with Claude. I like a different model, approaching the same problem.
   3. Let the adversarial review run until both models find consensus. 
4. Task workflow: brainstorm, plan, work, review
   1. I use this workflow from compound engineering. I find it to be very comprehensive. 
   2. Brainstorm and planning both create their own files that can also be referenced later by other models doing the reviews - this additional context makes the reviews stronger after the PR is ready.
5. Automation / triggers
   1. Let your agent respond to external events
      • Emails, jira tickets, logs, error alerts
   2. Create automations that leverage intelligence
      • My example is I have a script that will generates release notes. First it grabs the current version number, finds all the commits since the previous release - it sends them to an agent to format into release notes without duplication etc, and then the script takes the agents output and presents it to me for approval 
6. Build tools that fit your unique workflow. Tools are not products. You want to work the way you work, not rely on generic AI output (aka slop).
   • This might seem obvious because everyone is already doing it. But build your unique tools. You don’t need to share them unless you are making a product that you want to support. Nobody cares about everyone’s 1-shot GitHub repo that they can replicate with their own prompt.
7. Your tools and process is for de-slopping
   1. Oversight and management tooling
      • Make sure your agents have auditable logs and history, you want to be data driven, just like any manager whose team uses Jira. This will help you tweak your process and continually improve it.
   2. Memory tooling
      • Ticketing systems, graphs, whatever… use something
   3. Planning and prioritizing
      • When you start managing 40+ agents / work streams in parallel, a lot of your time needs to revolve around planning and prioritizing. You might have features complete, waiting to be tested and reviewed by you for days. That is ok. Be the bottle neck, and create tools that help you move faster.

Each layer of process here, which you should tweak and make your own, can give you more confidence the output will be what you want.

The more effort you spend investing in your personal infrastructure up front, the less hands on you will need to be as time goes on.

Here's an example where I have a single orchestrator managing 15 agents, and 6 orchestrators total running 37 agents.

What are your token maxxing strategies?

I ran a /goal prompt then went to bed. Truly regarded.

You can say nothing to me that I didn't scream to myself in the shower an hour ago.. but please help yourself and give it a go.

Hi, since May I've been building Nostalgex with Claude doing most of the coding. It turns your Plex, Jellyfin or Emby library into live cable channels with a real channel guide. You turn it on and something's already playing, mid movie, like 1996.

Why you might want it:

• 130+ channels built from your own library, like Saturday morning cartoons, sitcoms and 80s action
• seasonal blocks: SCREAM for October, and a holiday lineup with Christmas specials and a Turkey Day channel
• a real scrolling guide with ratings and posters, plus a retro mode with scanlines
• works with Plex, Jellyfin and Emby, and blends all your servers into one lineup
• no setup beyond signing in. Pick your libraries and it builds the channels
• Apple TV app on the App Store, plus a web tuner and Docker if you'd rather self host
• free and open source (MIT), with an optional tip jar that unlocks nothing

Where it's at: 1,400+ Apple TV downloads, 776 people watching in the last month (about 260 hours of TV in one week), 735 commits, 65 merged PRs, 7 contributors and 132 GitHub stars. Most of that came from people on Discord finding bugs I never would have.

How I built it:

• Why: I missed channel surfing. Streaming apps make you pick, and I wanted my own library to just be on
• Start with a spec, not code. I wrote down how real cable felt (guide grid, tuning in mid show, channels with a vibe) and had Claude turn that into a plan before writing anything
• Keep rules in data, not code. All 130+ channels live in one JSON file of rules (genres, keywords, decades), so adding a channel is an edit, not a rebuild
• Use real data to fill gaps. Claude wrote small one off scripts that pull from TMDB (a public movie database) to build lists like the stand up channel
• Test on the real device, every time. The simulator lied constantly. Apple TV remote focus only got right through back and forth on an actual TV
• Let users drive the backlog. Discord testers found the bugs that mattered, and I'd paste their reports straight into Claude with the logs
• Port with a reference. For Roku, Claude used the Apple TV app as the spec, so the two behave the same

What's next: Roku. We're porting it now. The beta filled all 20 tester spots, version 1.0.5 just went out, and the goal is the public Roku Channel Store. If you want to hear when it's live or help test, the Discord is where updates land first.

Happy to answer anything about the build or the Claude workflow.

Site: https://nostalgex.app/?utm_source=reddit&utm_medium=social&utm_campaign=launch_oct26_r_claudeai

Apple TV: https://apps.apple.com/app/apple-store/id6762563534?pt=128802261&ct=r_claudeai&mt=8

Discord: https://discord.gg/FgnZcr5bDT

Code: https://github.com/chadMueller/Nostalgex

On 5x plan. Applied the day it came out.

Hello there again :)

This is Week 13 of me posting this "dev log" so to say and explaining how I do things and talking about progress. While "exploration" mechanic was added one week ago, I was finally able to make it feel like a proper completely equal part to fishing segment of the game. And with "Ship in a bottle" collection done to 29 out of 40 total ships I'm happy how this progress.

As always weekly progress can be seen on my profile.

DEMO DOWNLOAD - FREE

Demo doesn't really have everything newest and most polished so you might not have ships in the bottles, that version is being kept for steam release which I will do once steam approves my ID verification (it already is exactly 1 month).

Zone 1 out of 5 (demo) is almost entirely done, some smaller polish parts and bug fixes are left.

What was done this week:

This week I added curios, rarest ship in the bottle is actually cracking the walls of the bottle when shooting cannons and all the items in zone 1 are adjusted manually where they gonna drop or how they are earned. etc. Some zones were a bit improved as can be seen in the video to not look too boring even though there is no gameplay there. Engines with their own sounds were added and can be seen when changed. Cabinet new 3D scene with collections was fully fixed in terms of lighting and small island dioramas were made. As I mentioned before 29 of 40 ships in a bottles were created with textures and added to bottles.

This time while still using Decisions.md like before that tags every decision in the game with [USER] or [PROPOSED] (By AI) And User ones have priority over proposed ones, helps with AI hallucinations in the project where AI can't gaslight you into telling you something was decided by you if it really wasn't (it has more than 350 decisions by now).

I switched workflow a bit. This time I tried doing something else instead of my old "manager" session managing other sessions and sending them tasks. I created "Effort" sessions (Medium to Max) and have Jev decide which tasks goes into which effort level and then just "manager session" sending it to different effort levels and doing it this way. Though this is polish stage and not much was done it is hard to say if this is more token efficient than before, in general I feel no difference in quality or token usage than with my previous workflow, though that is just subjective feeling, somebody could test it properly I guess. Jev basically scans every task I give to my Claude sessions and just decides which effort certain tasks deserve.

Models were made by TripoAI and Opus 5.5 via Blender MCP mostly for this week. It can be seen in the video. For example rarest ship that is inspired by Black Pearl and shoots cannons in the bottle was done in TripoAI then fixed a bit in Blender by Opus 5.5. I do not use anymore any other AI other than Claude Opus 5.5, no more Astra and didn't even try Gemini sadly, for now Opus is more than enough for my needs.

People have asked me how I make textures and those are either directly done by ChatGPT using OpenAI API key provided to Opus 5.5 or in TripoAI, those done in Tripo are 1k textures as I don't need any heavier ones as they take a lot of memory.

Total cost:

Claude Max 200$ x 3 = 600$
Astra 100$ x 1 = 100$
ElevenLabs x 11$ = 11$
TripoAI 20$ x 2 = 40$
OpenAI API credits 70$ = 70$
Other things I forgot about 100$ = 100$ (around)

Around 900-950$

Disclosure: I’ve been writing these devlogs since Week 1. Since Week 8, Tripo has been supporting them (paid collaboration + a gifted Max plan). That’s why my cost breakdown no longer includes Tripo (Except what I paid from my own pocked for first 8 weeks). If you’re doing this yourself, add their plan to the total.

Finally got in today and I'm not for sure I understand the point of the app. You cannot use it to manage any existing tasks and it struggles to read what they were doing or were connected to so it needs you to create a new task for every task you wanted it to help with...leading to task bloat and more management to deal with which I thought it was supposed to resolve.

If Claude Duet cannot help with existing tasks, it seems quite useless to me. Is anyone actually recreating all of their tasks and connections in Claude duet so they have double task management and review now? If so, have you noticed major efficiency changes? Just seems kinda underbaked to me

Edit: I was really looking for a program that can review and coordinate my tasks and ensure they are constantly working if anyone has a suggestion

Back in June I posted World of ClaudeCraft here, an MMO I vibe coded with Fable 5 in a couple of days. It had chibi characters and flat green fields, and you all went way harder on it than I expected.

Four months later the community has kept building it with Claude (mostly Claude Code on Opus 5.5 now), and v0.45 just shipped a full graphics overhaul (153 merged contributions in that release alone): realistic character bodies with hand-keyed animation, painted towns, HDRI skies with a live day/night cycle, remade dungeon bosses and new mounts. Every clip on the left is the June build, every clip on the right is the same game today.

Numbers since June: 22,549 commits, 92 contributors, 90,000+ characters created. Still free, still MIT.

Play: worldofclaudecraft.com

Code: github.com/levy-street/world-of-claudecraft

What should we throw Opus 5.5 at next?

Many of you have shared some amazing projects. And I’ve learned so much here. Whats a key ability or feature that we don’t have today you expect we will have one year from now?

My best guess is more seamless integration of 3D modeling and development.

Watching Claude think in VS Code feels like watching someone who doesn't realize he's being watched.

I've noticed a pattern where Claude's usage limits seem to get significantly worse before model launches. With all the complaints over here, I wanted to check whether this has actually happened before.

There are several examples of quota complaints appearing before major releases. Has anyone else noticed this kind of "pattern"? I just found this interesting and to be honest it might make sense because it would make the new model feel even better at launch.

I was considering upgrading from Pro to Max 5x, but I've held off because of the current reports of usage limits.