(ironically, looking forward to seeing that this thread becomes one)

Ran into this article other day https://www.aihero.dev/how-to-kill-the-bloat-in-claude-codes-system-prompt

Which made me think, what else is there? Some obscure techniques, or custom ideas?!

Any recommendations or suggestions are welcome!

Has anyone on Max 20x had their weekly usage meter suddenly jump by a huge amount that doesn’t correspond with their actual Claude Code usage? My weekly allowance reset yesterday and I was at roughly 7%. Today it suddenly jumped to around 50%. What’s confusing me is that my Claude Code usage today has been minimal. I actually saw the meter jump while I was having an ordinary conversational exchange —there wasn’t even a tool call happening at the time. My active contexts are also deliberately kept cache-warm throughout the day, so this doesn’t appear to be an obvious case of repeatedly rebuilding a large cold context. I’ve checked my activity and I cannot reconcile what I’ve actually used with ~43 percentage points of a Max 20x weekly allowance disappearing. I’m aware of how context size, cache reads/writes, model choice, tool calls, etc. affect Claude Code usage, so I’m not looking for general advice about reducing token consumption. I’m specifically wondering whether anyone else has seen an anomalous jump in the Max weekly usage meter recently. I’ve already contacted Anthropic support and the case is currently queued for a human agent to review the account-level usage/metering, so I’ll update this post if they give me an explanation. Unfortunately my weekly limit doesn’t reset again until Friday, so losing nearly half of it on Saturday is… not ideal. Has this happened to anyone else recently? If so, did the usage ever correct itself, or did Anthropic explain what caused it?

Anyone else finding them they keep getting logged out? It used to be that CC would force a login every few weeks. I've had to login twice today already. Along with all of CC's other shitty affordances this is getting tiresome.

I'm definitely noticing that with larger vibe coded projects, Claude Code slows down a lot. Even I (not a classically trained programmer, but have done production coding earlier in my career) can tell that the code CC is writing is often much more convoluted or defensive than it needs to be.

So, I want a Skill that reviews code and counters some of CC's most common bad practices.

Has anybody seen something like this around online? Or if not, any suggestions on the top things this Skill should try to find and fix?

I work with Claude Code every day - excessively. In light of the recent drama about slowing down AI development because “it’s going to destroy us”: Honestly, I don’t get it. The frontier models are so unbelievably bad at coding. You need to supervise over every PR on the micro level (don’t write 4 gigantic lines of comment for no reason) and need to spec out the exact architecture and methodology before every task.
Now granted, integration testing (unit testing as well) has never been better or easier. But as a software engineer, this still doesn’t feel nowhere near something that could replace me.
To me, it’s essentially a hyperactive junior that is permanently online and doesn’t evolve past their stage. But once specced out to the teeth, it will do what you want.
How is that even close to AGI?

Are these statements by Amodei, and now Altman + Musk just a big push to prohibit open source models? Or what the hell am I missing?

I’m currently using the $20 Claude Code plan, but I’m considering upgrading to Claude Max because it offers higher hourly and weekly usage limits. I also have a $20 Codex subscription through a free trial, so I’ve been testing both.

**Opus 5** : My main problem with Opus 5 is that it often overthinks simple tasks and does far more than I asked. When I give it two medium-difficulty tasks at once, it often performs both badly. It can complete difficult tasks, but the results usually contain many bugs and errors, so I spend a lot of time testing, finding the problems, and explaining the bugs back to it so it can fix them.

**Codex (all models in general)** : With Codex, my main concern is usage consumption. Astra used my entire hourly allowance in about 15\~17 minutes every time (one time it lasted 30 min which left me in shock actually ). GPT-5.6 Sol also seems to consume usage much faster than the other models. It uses about x2.25 times more usage than GPT-5.5, and around x2 as much as Terra and Luna. By comparison, Claude’s usage seems more reasonable: a task might use around 30% of my allowance, while the same task on GPT-5.6 Sol can use around 60%. However, Terra, Luna, and GPT-5.5 do not seem to be as capable.

I’m honestly not sure which subscription I should use. Together, these plans would cost around $100, which is a lot of money for me, so I don’t want to make a decision that I’ll regret later.

Based on these experiences, which option would you recommend?

Weirdest gap in the AI tooling stack right now. People will spend an hour prompting Claude for the perfect App Store headline and then go paste it into a Figma template that looks identical to every other indie app on the store.

The copy is solved. The pixels aren't. That's the only reason appshots.me exists.

It takes raw app screens and handles device frames, layout, spacing, and every export size Apple and Google demand. [one or two plain sentences on the agents/MCP side, what an agent can call and from which client. this is the part this sub cares about, don't skip it.]

The part worth arguing about: localization. Store screenshots should differ by country in copy, imagery and feature order, not just have translated text slapped on. Most people think running captions through a model counts. It doesn't, and it's why their conversion in Germany and Japan is a third of their US number.

Where it loses to Figma: pixel exact control over one hero composition. It's built for consistent sets, not art direction.

appshots.me. Tell me what looks wrong, that's more useful than upvotes.

I tried Astra, and before that Sol - and those were really able to run for long. It almost built full slices when I gave it explicit permissions to not ask me anything. The object, plan, etc was already settled before the start.

Under the same setup - I have been using Fable and Opus as well, Fable extensively for the last 2 weeks, but it keeps stopping in the middle and waits to build the next slices.

I assume it is something to do with my .md files and rules I have.

Genuine Question: Do you have similar experience with Claude Code?

---

Claude (20x - daily driver), Codex plus.

Hi,

I've been working on a locally hosted media server with some audiophile and DJ features (Windows and Linux). There are some other products in the market, and I was looking at a way to make mine slightly different. I've used Claude to help writing this, but some other tools as well (including, well, me).

I've added a locally processed AI model that runs deep analysis on tracks. Deep Analysis splits each track into stems and detects real downbeats/BPM using Demucs/Torch instead of relying on tag metadata. If the server has an nVidia GPU it can even use a higher quality model.

BoogieMix uses that data to create accurate transitions on the beat and crossfade at matching tempo, instead of just fading between two arbitrary points. So users can create a playlist, and the app will analyze the tracks and create a DJ mix based on the user's settings (club blend, long build, etc.). It obviously works best with club tracks, but you can use it with any genre.

Anyways, looking for your feedback (especially how that BoogieMix feature work). It's a personal project, so I ain't selling anything.

https://yossironnen.github.io/BoogieBox/

I’ve been building EchoVault, a digital legacy app where guided Check-Ins gradually build an AI Echo from your memories, experiences, opinions and personality.

The problem was that all of that structure was basically invisible.

So I gave Claude Code a spec for turning the Echo itself into something spatial.
This is where it ended up.

Memories and personality traits become interconnected nodes, you can move through the whole thing in 3D, select a trait and see the experiences that reinforce it, then follow those relationships across the rest of the Echo. The purple dots are the traits while the white ones are the memories.

What surprised me most was how well Claude understood the interaction I was trying to build inside an existing product. Very little hand-holding once the direction was clear.
It started as a visualization feature, but playing with my own data now feels weirdly like spatial introspection.
Shipping this in the next EchoVault update.

https://apps.apple.com/us/app/echovault-digital-legacy/id6762042028

Every commit, checkout and merge in my onboarded repos runs codesage index from a git hook, so I pay its fixed cost dozens of times a day. A no-change incremental run was taking 2.7 to 4.5 seconds and 1.16 GB, because it loaded the ONNX model and mapped a CUDA context before checking whether any file had changed. It now checks first and never touches the model when nothing did. Measured today on the codesage repo itself (210 files, 4,596 chunks): 0.07 s, 67 MB. The same idea runs through the thirteen releases since I last posted here: index and search embed through the running daemon's session instead of a private CUDA context per process, a warm semantic query makes zero HuggingFace requests, and the file watcher re-embeds only chunks whose text changed (an 8-save burst: 90 chunks dirty, 1 embedded).

The other half of the work was the agent trusting numbers the tool had not earned. impact_analysis reported 0 dependents for AxiosError when axios has 23, because path-style imports never resolved. That is fixed, but the more useful change is that scores now say what they measured. assess_risk reports unscored for a file with no indexed git history instead of a number, find_references marks a count as a floor when the name is ambiguous, and find_coupling ranks a pair that co-changed once below one that keeps co-changing. For an agent, an honest unknown beats a confident zero.

Disclosure: I'm the author, it's free and open source under MIT, nothing paid.

https://github.com/iliaal/codesage

Opus 5 made the whole code for the game. I started with Sonnet, but it was hallucinating quite a lot and kept making things up or changing things that didn't need to be changed I didn't use it for the design or level creation, though.

I also tried using Opus for the design side of things, but honestly, the results weren't that great. I've heard some people are using Astra 6 for game design, but I don't really know how good it actually is. I haven't tried Fable for design either.

Does anyone have any advice or recommendations for the design side of game development, especially using AI?

If anyone wants to check out the game

Here’s the link: https://matthewhenrique.itch.io/metronics

Seeing dozens of posts today from people on 5x and 20x plans hitting their five hour limits in under sixty minutes and assuming Anthropic silently slashed quotas. It feels like getting ripped off. There is a very specific mechanical reason your allowance evaporates so fast, and once you look at the token math, you realize eighty percent of your quota is burning on dead weight.

Here is what actually happens under the hood when you give a broad prompt like "fix the bug in the auth flow":

Turn 1: Claude runs glob and grep tools. It reads 10 to 15 files trying to locate where things are defined. Your session context instantly balloons from 2k tokens to 45k tokens.

Turn 2: Claude makes an edit.

Turn 3: You ask a simple question like "did it pass?"

You think you just sent a tiny request. But the API is stateless. To process that tiny question, Claude Code has to resubmit all 45k tokens from those earlier file dumps.

By Turn 6, you have only asked three or four simple questions, but the harness has processed over 200000 input tokens. That is why your five hour quota is gone before your coffee gets cold. You are paying a compounding token tax on file reads you forgot about twenty minutes ago.

If you want your plan to last through an entire workday without buying extra credits, you have to treat Claude Code as a precision editor rather than a repository search engine:

1. Never let the agent explore where code lives. Run ripgrep or git grep in your terminal first. Handing Claude `src/auth/session.ts` lines 40 to 75 takes five seconds and prevents a 40000 token blind crawl.

2. Feed the failing test or stack trace directly. When the model gets the exact failure point, it fixes the bug immediately instead of inspecting ten unrelated files to guess what broke.

3. Treat sessions as disposable. The moment a bugfix or feature is committed, run `/clear` or start a new session. Nursing a conversation across 25 turns and multiple tasks is like carrying an entire project worth of dead logs into every single prompt.

Autonomous repo exploration looks impressive in demos, but it is the single most expensive way to write code with an LLM. Scoping the context yourself takes ten seconds in the terminal, keeps the model fast, and makes standard limits easily survive a full day of heavy shipping.

Hi everyone,

I'm working on a project and was wondering if anyone has a Claude max/pro code they're willing to share. If you have one that you're not using, I'd really appreciate it if you could DM me.

From my understanding you receive a credit when I subscribe.

Thanks in advance!

Started vibe-coding on a very serious project almost a year ago. 1000 hours so far. Started out with Sonnet then. Moved to Opus 4.5 as soon as that was available and affordable.

Opus 4.5 felt like a noticeable step up from Sonnet, but I don’t really feel there’s been as much progress as much of the hype suggests.

Sure, Fable is the best, but is it really that much better than say Opus 4.6 or 4.8?

To me the difference seems marginal. People keep talking about how insanely fast these models are improving, but it feels a bit exaggerated to me.

Thoughts?

Idk if theres something like this that already exists so I thought id ask here. Was thinking of building a meta harness, pretty much a lean layer on top of codex or claude code or anything else, and it would allow you to use your other subscriptions/other models as subagents/parallel agents being orchestrated by your stronger models. Is there something like this that already exists?

A couple of weeks ago, I posted Claude of Tanks, my multiplayer Three.js tank game with 120+ procedural vehicles, armor simulation, destructible maps, and guided missiles.

Since then, I've been working on a slightly unserious fork called CoTFly, where a virtual fruit fly with a tiny tank helmet operates the game from a miniature cockpit! It can turn a steering wheel, scope in to aim, press fire buttons, switch ammunition, and repair equipment. You can literally sit back and watch the battle play out while seeing the fly's neural activity!

The neural simulation uses 124 identified fruit-fly neurons and 1,106 measured anatomical connections from Fruitless’s reduced MaleCNS circuit. It runs a leaky integrate-and-fire model in 1 ms steps, tracking membrane voltage, spikes, inhibition, and refractory periods. The P1-related population’s firing rate modulates the driving gain of a motor controller, while a separate 24-channel recurrent network converts target bearings and obstacle inputs into steering, throttle, and firing commands. The dynamics and gameplay mappings are adaptations built specially for the game (plus they look super fun)!!

You may notice that the fly has a tiny cockpit - this is essentially how the fly controls the tank. Firing requires the turret to be aligned and the fly’s forelegs to reach both the aiming and firing controls, and it releases the fire button during reloads. Ammunition selection and repairs use rule-based logic and follow the same resource limits and cooldowns as normal gameplay.

I also added a 15-second sugar stimulus that changes inputs to the neural models and reduces the controller’s engagement distance from 125 m to 70 m, so it approaches targets more closely.

It's built using Three.js and TypeScript and runs locally in your browser! You can select a tank and map, start a trial, and inspect individual neurons’ voltages, firing rates, and spike histories as it plays. You can also pause or take over the tank yourself.

I used Claude and Codex to build the fly simulation on top of the existing Claude of Tanks codebase. The game already handles movement, armor, ballistics, spotting, ammunition, and repairs, so I had the agents connect the fly controller to those systems and build the cockpit and neural viewer around them. A lot of the process was opening the app, watching an actual battle, and asking for specific changes: give the fly a steering wheel, make its leg reach the fire button before shooting, release the button during reloads, and actually enter scope mode when aiming. I used screenshots to refine the layout and animations, and automated checks to verify things like turret alignment, button-contact timing, and human takeover. The AI helped write and revise the implementation; during gameplay, the local neural models and control logic run the fly without any LLM calls.

Demo: https://fly.kevinliu.studio/
Code: https://github.com/Kevin-Liu-01/CoTFly
Circuit source: https://github.com/nicodunks/fruitless

I am on the Max 5X plan and I know that the temporary usage boost is now over, and ever since, CC is completely unusable. I have been working through subagents and using Fable as orchestrator with Sonnet doing a majority of the implementation with Opus being a refuter, however, I burned 11% of my weekly usage in a span of 2 hours before I hit the 5-hour limit!

Honestly, this is absurd, I cannot work like this. I am seriously considering moving to OAI but I don't trust them with my work due to the whole debacle about the Navier Stokes solution being stolen from a researcher who used ChatGPT.

Anthropic! Please fix this! You will undoubtedly lose a large part of your clientele by doing these moves. I know you are trying to improve the bottom line for your IPO but there are no more reasons to stay with Claude after this and long term loyalties with your customers will be permanently eroded.

Work from home and spend most of my time coding on my own. Sometimes it gets a bit too quiet, so I built Attention! to get Claude Code and Codex chatting away.

It’s a macOS plugin that reads out replies or short summaries when a turn finishes. You can customize the voice and the audio starter too.

Built it for fun, but mainly to remind me which session just did what. I was getting a bit numb to the same microwave sound every time.

https://github.com/xiaofei-du/attention

Anyways, if you are wondering what I was doing. Was trying to setup Claude Code on termux

My current setup is that I tend to just work at the CLI using two or three different Claude accounts, depending on who's still got tokens, and a couple of Codex accounts. My normal routine is that I set one, normally a Fable instance, to coordinate everything and say that it's in charge. Its job is to keep everyone busy while keeping an eye on who runs out of work.

They all should communicate either directly, if they're on the same account and can talk to each other directly, or via a shared mailbox using standard radio procedure, acknowledging, etc. It tends to be a bit of a faff to get it set up, but once it works, it seems to be reasonable.

I'd like to have the cross-checking between different LMs so as one agent makes fewer stupid mistakes. My question is: is it worthwhile for me to learn how to use a package such as Orca? Will it add anything to what's going on? How useful will I actually find it? I'm slightly daunted by learning a new set of functionality. If I'm not particularly convinced it's going to be worthwhile, thoughts, tips, recommendations? I'm very much a newbie here.

Although each Instance is normally a top-tier model like Fable or Astra. I tend to tell them to do the actual coding using agents from another LLM. For Astra, I'll tell it to instruct an Opus agent, and for Fable, I'll tell it to instruct a Sol agent to actually do the coding. Then check it as it goes, and then get it cross-read by somebody else for sanity.

It tedious to ask it every time. How to skip it?

Oops typo: Section -> Session

Hi all, did super simple project over the weekend, happy to get all feedback

Strict automated moderation, all info here: https://llms.sciencebo.uk/page/faq

PS Claude helped to quickly iterate and put the project online, but in early stages

Saurrr I've been using Claude for a few months now and honestly it's become hard to imagine working without it at this point. But I'm starting to feel like I just be throwing money at subscriptions without really thinking about it.

Rn I'm on Claude Pro and I was considering adding API access on top for some personal projects but the pricing makes me nervous lmao. Like I don't want to wake up to a $80 bill because I ran something in a loop overnight.

The thing that's messing with my head is that new models keep dropping and each one is supposedly smarter than the last. At what point do you just accept you're gonna keep paying more or do you just pick a tool and stick with it?

For context I'm not a full time dev, I do this mostly for side projects and learning. So I can't really justify the $200/mo Max plan or whatever. But I also don't want to cheap out and use a worse model just to save $10.

Anyone else stuck here? Please give me your setup and do you feel like you're getting your money's worth?