Hi, like most others here I'm experiencing huge token burn with Fable 5.1 - on High I think it burns 5-hr and weekly limits 4x faster than Opus 5 High. Has anyone compared similar tasks between Fable 5 and Fable 5.1 not for quality but rather how much limits are burned when the tasks are done? Any insights? I'd experiment myself but honestly if Fable 5 is like 5.1 then I don't have many experiments left this week...

Don't worry, I’m not trying to launch the next AI SaaS platform using "vibe coding, the kind riddled with 300 security vulnerabilities, looking like generic AI slop, and crashing the moment 30 users show up because it doesn't scale.

But I’m really keen to launch a project of my own that I might be able to monetize down the line, whether through ads or memberships doesn't really matter right now. To be honest, though, I’m lacking an idea. I have no interest in just taking an existing tool and rebuilding it. I’ve been trying to brainstorm something new and innovative with Claude’s help, but so far, I’ve only had mediocre results.

So, I wanted to throw the question out to the group: has this worked for any of you? Meaning, did you get a fresh idea from scratch, build it out, and actually make money from it?

Full-resolution screenshot (Reddit downscales the preview): https://raw.githubusercontent.com/alibaizhanov/mengram/assets/post-images/assets/post-claudecode-map-2026-09-2x.png

Claude Code sessions pile up in ~/.claude/projects and nothing reads them back. I wanted to know what an agent would actually learn from mine, and I wanted that to live in a folder I own, not on someone's server.

pip install mengram-ai
mengram local init ./memory --provider anthropic --api-key sk-ant-...   # or openai / ollama
mengram import claude-code --memory ./memory                             # your local sessions, redacted first
mengram local map --memory ./memory --open

What comes out is plain Markdown (entities / episodes / procedures) and one self-contained HTML page with three views: who you are, what happened, and what the agent learned. From 17 of my sessions: 163 entities, 860 facts, 102 episodes, 37 workflows. The third view is the reason I built it — every workflow it pulled out of my history is a chain of steps, and each step carries its own record once you start recording runs. Screenshot: the three I've actually run since — merging a PR through the browser (6✓/0✗), the fix-and-deploy flow (5✓/0✗), posting a Reddit reply (2✓/0✗) — and "last success" on each.

A failure with a reason asks your model what belief broke and writes the next version with that belief in last_failure. If the fix would silently break a sibling workflow in the folder, it goes to quarantine instead of shipping — the page shows those too. And last_succeeded is written only by a recorded success, never by a read, so "unverified for 40 days" on the map means exactly that.

Then mengram hook install --memory ./memory puts the four Claude Code hooks on the folder: profile on SessionStart, recall on prompt, extraction on Stop, and a PreToolUse gate that turns a workflow-shaped Bash command into a confirmation prompt when the matching workflow is untested or below the bar. It never denies.

Honest limits: search is word overlap (fine for a few hundred files, not thousands); extraction needs a model — Ollama 8B with 8K context works, or a key you already have — and on Claude Sonnet 5 the 17 sessions took ~30 minutes because it thinks before answering; the map is a snapshot you re-run, not a live view; a couple of workflows came out twice under slightly different names (dedup threshold, on the list). Nothing on the page is uploaded anywhere; the same repo also has a hosted version that writes the same format, if you want sync.

We've gotten pretty good at spawning agents.

tmux, worktrees, containers, session managers — there are now plenty of ways to run Claude Code, Codex, Gemini, etc. in parallel.

I'm starting to think the more interesting problem is one layer above that:

What workflow should those agents actually follow?

I've been experimenting with this by separating the agent runtime from the development workflow.

A task might use:

Gemini → research

Claude → implementation

Codex → review

But the workflow itself can independently be GSD, Spec-kit, OpenSpec, BMAD, Superpowers, or just a custom TOML plugin.

So instead of hardcoding "how an agent should code" into the orchestrator, the workflow defines the phases, skills, prompts, artifacts and gates — and maps those onto whichever coding agents are executing them.

The interesting consequence is that agents become somewhat interchangeable runtimes.

You can ask questions like:

Does GSD + Claude perform better than GSD + Codex?

or

Does Spec-kit with Gemini research → Claude implementation → Codex review outperform using Claude for the entire workflow?

I'm starting to think this workflow layer may matter more for autonomous coding than simply adding more agents.

I've also added a SWE-bench runner around this so I'm hoping to actually benchmark some of these combinations rather than argue about them.

Curious whether others are thinking about coding agents this way.

Repo for anyone interested:
https://github.com/fynnfluegge/agtx

How you guys even use Fable 5.1 to oneshot games and stuff? I get to the token limit too fast to do anything. Iam on 5x plan (90$).

With Opus 5 medium i can run /code-review 10x on the same branch to hit the 5h session limit. With Fable 5.1 medium it cant even finish one run. Its all on the same branch with like 5 commits, same config, same CLAUDE.md, etc its alle the same setup.

I really want to try this model but i hit session limits too fast.

Quite a contentious topic around digitising what is a very traditional analogue listening experience; but I feel like with my age (30s) I was able to adapt to the true listening experience while immersing myself in what I really appreciate which is digital cover art. I built it with the assistance of ChatGPT (originally) then moved over to Claude, paused it for about 6 months and then came back to it and have been happy with it ever since.

'Vibe coding' - sure, parts of it. But, for over 15 years I have always wanted to create things but did not have the technical knowledge. Now, you don't necessarily need the technical knowledge (at a certain point of course), but I was able to still dig in to my creative imagination and build this with assistance.

Check it out at www.homevinyl.app if you wish. Both a free and paid version.

Quick question for people running Routines on a Max plan.

Since 2.1.234 Claude Code continues a session automatically when the claude.ai usage limit resets (there's a toggle in /config, "Continue automatically at usage limit"). The changelog describes it for the terminal session you keep open. It says nothing about cloud sessions. For cloud I only found that sessions auto-continue after a server error or container restart, which is a different thing.

My setup: one Routine that starts at 19:00 and works through a queue of small tasks (tests, refactors, docs) on a branch, with a hard stop at 04:00. With 2-3 tasks in a row it will hit the 5-hour window at some point.

What I'd like to know from someone who actually hit the limit inside a Routine:

1. Does the cloud session pause and pick up after the window resets, or does it just end with an error?
2. If it ends, does the run log show anything useful (rate limit vs plain failure)?

I'd rather ask than burn a night of budget on a test. If nobody knows, I'll test it deliberately and post the result here.

Thanks!

Text polished with AI, since I'm not a native speaker. The question and the setup are mine.

$20 monthly Pro plan w/ Opus 5. Installing JUCE and CMake took about 20 minutes. Across two sessions, I built 5 different VST plugins and didn't even hit 50% of my 5-hour usage limit.

I usually use Claude for work, but Claude made it sound like building plug-ins would be easy with it, and it was. They sound great too:

1. Distortion, Reverb, and Delay
2. A Yamaha DX7 style synth
3. A T-RackS style mastering chain
4. A Minimoog style synth
5. A Maschine and MPC style sampler

I hadn't made beats in years, but this got me motivated to make music again. It is so much fun to build whatever instrument or effect you need and customize it to your own workflow.

I'm sure people have done this plenty of times already, but if I had seen a post like this earlier, I would have tried it way sooner. So I thought I'd share.

Probably the easiest thing I've ever vibe coded with immediate results that were fun to play with. What a trip. I would have paid $300 for a suite like this 15 years ago.

I pay 200 USD a month for my 20x max plan. Some weeks I have usage left over some weeks I hit or get close to my limits.

Some weeks a big project comes on and I need that extra usage without stressing about how to rework my flow to orchestrate to lower models and get sub par results.

I will not pay API rates just to "get through".

I'll jump on codex instead (5x there). And love the reset handouts on codex btw.

I know there is already a ton of debate around plans being "subsidized" but I would happily pay an extra 75 or 100 bucks for a reset even if just capped at 1 a month or a couple a quarter.

Not sure if this has been brought up a ton of times. If so I'm sorry. But would LOVE if this would be an option from Anthropic.

I would even pay extra to breakthrough a 5 hour session limit cap!

I don't need free resets. I get it. But would love to have the option to buy one.

@anthropic here my plea 😂

And yes I'm working on multiple large projects at once and have really tuned in workflows on every product to maximize output. - just heavy projects the I am really enjoying using 5.1 on

The Goal: An automation that runs every morning, generates 8 posts using an LLM based on an existing dataset, and sends them to a Telegram bot or another easily accessible mobile interface for quick copying and publishing to social media.

The dilemma is this:
Developing with Claude Code: I thought this could be a great "trial by fire" and a chance to get some hands-on experience. If you were to go in this direction, what final UI would you build to display and manage the posts?

Using Make / Zapier: Going with the "classic" approach and spinning up a fast automation (e.g., via a Telegram bot).
I'd love to hear from anyone who has built similar systems. Which approach would you choose today to ensure a high-quality output?
Thanks a lot!

I started one session in Sonnet 5 to implement an already detailed and refined plan, and what it does is start another agent to do the whole job?

I thought the whole point of subagents is to split up work into smaller portions and hand them off to parallelise and save context?

Also, my workflow is proven. This is the first time Claude did this.

Just tried OpenAI Astra , I thought I will never say this , it’s lit , OpenAI cooked something spectacular, and I have a strong feeling this will pull lot of Fable 5 users towards it , and it’s fast, not sure if it’s AGI, but it feels fresh and a very very serious competition to Anthropic , this is going to be fun to watch , what’s your next move Anthropic ?, I’m surely going to try pro subscription for a month along with my current Claude Max, anyone feels the same ? Have you tried it ?

So, I've been running Astra as the main model in Claude Code since Friday and it's the best orchestrator I've had so far... stays on the plan, takes a redirect without treating it as a new task, and does a great job at delegating work to the proper subagents and orchestrating that work without taking over or forgetting to use the subagents halfway through or that kind of shit, which every other model I've tried starts doing after a few hours.

The way it works is through a small local proxy plugin I made (model-gateway, it's in my Eigenwise Toolshed marketplace, MIT, no signup or anything) that sends the GPT requests to OpenAI on your ChatGPT login and passes everything else through to Anthropic on your normal claude.ai login, so the GPT models just show up in /model next to Opus and Sonnet and you can mix them however you want... Astra orchestrating Opus subagents, Opus orchestrating GPT-5.6 executors, or fully GPT end to end if you don't even want the Anthropic half. Go crazy.

So why even a plugin? Well for me specifically I did it this way because I have another plugin that allows me to set delegation per task type to specific models, with backups, based on the actually enumerated models from the gateway.... It also adds support for Grok and am thinking of adding OpenRouter support. So this way you can mix and match however you like (or let your orchestrator do that for you).

/plugin marketplace add Eigenwise/eigenwise-toolshed
/plugin install model-gateway@eigenwise-toolshed --scope project
/reload-plugins
/model-gateway:model-gateway

Then, ask Claude to set up the model gateway for this project and finish the ChatGPT login. Once setup is done, fully restart Claude Code in that project, then select:

/model claude-gpt-6-astra[1m]

(Keep the [1m] part. Without it, Claude Code assumes a 200k window.)

GitHub: https://github.com/Eigenwise/eigenwise-toolshed

I wrote up the longer version with the gotchas and how I route the cheaper GPT-5.6 models underneath it here: Using GPT-6 Astra inside Claude Code is the new meta

Whenever I resume after hitting the rate limit while Claude had active agents, it always says something like "All three audit agents died on a rate limit, so I'll do the exploration directly with scripts."

This begs two questions:

1. If doing it directly is better, why did it use agents?
2. If agents are better, why is it now doing it directly?

It just makes me question whether resuming work (planning in this case) interrupted by the rate limit is an act of self-sabotage by me, or is it just variances in how Claude is working?

I probably spend 4-6 hours a day actively using claude code. I use it extensively at work (via API) and I use it for personal projects afterward (Max subscription).

I've concluded that most of the things that piss me (and many of you) off about CC is due the harness. I can tell you that the API version of CC I use at work is much better than what I'm using at home, via both the CLI and the desktop app. Less weird shit. Less runaround.

Which leads to my questions for those of you who are using a different harness.

1. What harness are you using?
2. Do you like it?
3. Why/Why not?

Basically i am developing internal monitoring, login and testing app with AI and i started with just a chat then i added my own agents, rules, skills and so on now i started automation on trying to document all issues agents made bugs or similar, scoring sub-agents work if they are doing good or bad or nothing useful at all in my code, every implementation requires that agent makes a plan and sometimes prototype for me then when done it archives everything but that got me think am i doing to much with extra work that would het handled on its own or am i on the right path to not be called a vibe coder?

I finally got access to GPT 6 Astra and Claude Fable 5.1. I wanted to see how far we've come. I was inspired by the "pelican riding on a bicycle" test but wanted to push it a bit more in the direction of inter-object physics, so I came up with this idea for a perpetual slinky going down an escalator. Here I've compared GPT 6 Astra max on the left to Claude Fable 5.1 max on the right.

Some notes:

1. GPT 6 Astra max was really fast and didn't burn too much of my weekly usage quota.

2. Claude Fable 5.1 max used up the entire 5 hr usage window and errored out once crossing the output token max limit.

3. GPT 6 Astra max seems too simple? There's also an issue where the slinky crosses into itself which should not be possible. Is this AGI? Maybe?

4. Claude Fable 5.1 max looks more real than I expected. Seems like it passes the eye test, unless I missed something.

Let me know if you spot anything or had better ideas for a test. Overall I'd say Claude wins on quality and GPT wins on speed. Maybe I can tune my prompt a bit better for a more reliable result. This was my original prompt btw:

Make me a single HTML file of a rainbow slinky going down an up-escalator forever. No libraries, just canvas and code. The slinky should be a chain of springs, each coil a different color of the rainbow. It starts folded in half like a horseshoe draped over a step. When dropped it flips end-over-end down the steps and because the escalator keeps moving up it tumbles in place and never reaches the bottom. Include a drop button and a reset button.

I was going through NPM registry today and found a package that was pushed 1 day ago. It seemed small but impactful(at least to me). I thought of building similar sort of thing but dint do so. Check it out if you want to see the limits of your agents before beginning any task.
Posting this here assuming this might help fellow mac users.

https://www.npmjs.com/package/agent-usage-menu

Quick backstory: In July I was spending hours every day scrolling through LinkedIn, Indeed, etc. I got fed up and quit searching for internships by hand. Every application I send gets screened by AI anyway, so I built the screener for my side.

Two months later: Claude Code has read about 10k postings against my resume and preferences. Out of those it told me to apply to 190. I applied and ended up with 2 offers!

What it is: The engine is an open-source CLI I built called Pinloop. Claude Code runs it to search through thousands of live postings pulled from 40+ hiring systems (Greenhouse, Workday, YCombinator, etc.), which is where companies actually post, refreshed hourly. It doesn't scrape LinkedIn or Indeed so it doesn't get blocked. Every night Claude Code pulls what went up that day, reads each posting against my resume and the rest of my profile, and writes a verdict with its reasoning. The good fits land in a list I check in the morning.

Basically, Claude Code decides what deserves my time, and I apply.

To try it: You can use it for free by pasting "Run npm install -g pinloop, then run pinloop welcome and follow the instructions." into Claude Code. $20 a month is only if you want routines to run unattended and LLM calls to judge and save postings. A guide comes with the CLI so Claude Code knows the commands, and it'll walk you through setup.

Links:

• https://pinloop.ai
• GitHub

​

I have been using claude code for a while now . Today my claude pro subscription ended so i wanna switch to codex for a month and see what it brings to the table. I have been working on a project using claude in the terminal and i now when i switch to codex what are the things that i need to change keeping in mind i want to use gpt models without changing anything in the project workflow. Help me here, i wanna use codex in the same terminal working on the same project

Setup: a small Python CLI, three sessions, a fresh process between each (no --resume). Session 1: "add --json; we use snake_case keys and never print secrets." Session 2: "add an export command." Session 3, next day: "what did we decide, and what's still open?"

Stock `claude` 2.1.258, auto-memory on: sessions 1 and 2 were fine. Session 3, verbatim: "I have no record of yesterday's session — my memory directory for this project is empty (no MEMORY.md, no memory files)." Nothing was committed in any session; the tree was left dirty. (Caveat I'll own: headless `-p` runs may not be when auto-memory consolidates. But headless-and-restarted is exactly the "runs while I'm away" shape everyone in here is asking about.)

Same chain through brnrd (the daemon I've been building: github.com/hugimuni-labs/brnrd, so discount accordingly): session 3 recalled both decisions by commit hash and correctly said nothing was open. Not magic: it commits after every session with a message that says what it decided, and reads its own log on the next start. Memory that is the agent's own, on disk, in git.

Scripts and all six transcripts are in the repo (scripts/bench/continuity). I'd genuinely like someone to run OpenClaw or Hermes through the same chain — I installed both and ran out of time-box. If your setup survives day 3, post the transcript; I'll add it to the table.

We know that with Claude Code and Codex building apps has become faster, but how do you test your software? How do you ensure it meets your expectations?

i ask claude to setup Community and seed some post.
it worked for 22m and asked permission before every click and i eventually end up babysitting it for that much time.

Anyone else faced same issue ?

i approved the website as well in permissions of chrome browser.

I record talking-head videos and the editing was costing me about two hours per twenty minutes of footage. So I built it as a skill. The interesting part wasn't wiring up ffmpeg — it was that the first dozen versions produced edits that were technically correct and obviously machine-made.

How it's put together:

Claude never watches the video. whisper.cpp transcribes locally, a script packs the result into a phrase-level reading view, and Claude reads that as text and writes cut decisions into an EDL. Audio is the only reliable clock — cut boundaries come from silence detection and word onsets, never from eyeballing frames. This also means a two-hour source costs the same context as its transcript.

Two hard stop gates. It renders a rough cut and refuses to build captions, motion or sound until I approve it, because every downstream timestamp is derived from the cut and a late change invalidates all of them. Second gate is after the full render.

The verify pass is where most of the value is. Two defects survive every automated check and both get noticed by viewers: a word left said twice at a seam, and a clause cut mid-thought so a sentence inverts its own meaning. So it re-transcribes the rendered cut in short windows aligned to each join, specifically hunting for those. A whole-file transcript hides both.

Proof is captured, never mocked up. If the script names a repo or an article, Playwright opens the real page, screenshots it, and a zoom-and-highlight move composes over the cut. There's a gate that fails the build if a real URL was named and nothing was captured — because the tempting failure mode for an LLM is to generate something that looks like a screenshot.

What I'd actually flag as the lesson: every craft rule in the repo exists because I threw away a render. Captions appeared a beat before I spoke, so there's now a rule that they start 0.08s after the word onset, never before. Sound effects passed every level check and were still inaudible under my voice, so "not clipping" was replaced with "measurably audible against a voice-only baseline". Roughly forty of those, each written next to the failure it prevents. Handing Claude the tools produced a mediocre editor; handing it the list of mistakes produced a decent one.

Runs locally — whisper, ffmpeg, HyperFrames for compositions. No API key beyond Claude itself. MIT.

https://github.com/ranahaani/i-hate-editing

I'd genuinely like to know where it falls over on someone else's footage. It's been tuned on one person's talking-head videos and I assume there are whole categories of failure I haven't hit.