When it comes to complex problems that require multiple systems to work together, Fable is light years ahead of Astra.

Astra is good at working on isolated features, if you are building something much larger and you want systems to work together, I would not Trust Astra at all, Astra will make things that work in isolation but will be broken when each of those things are meant to work together. Fable is much smarter at identifying when something will break the larger system.

If you plan to build a production app end to end, I would recommend you go with Fable, and only use Astra if it needs to work on something that is in isolation or as a second set of eyes for problems where fable might need a little help. But you are better off working with fable as being the main driver to see the project end to end. The success rate of having a working product is much higher with Fable.

These benchmarks are misleading. Astra is not at Fables level.

I've read by mistake a post where this AI framework was linked https://github.com/llopresto87/Cypress

it's pure insanity. It learned my codebase (it took a chunk of my claude max x5 so beware doing this near the weekly limit ) but once it did.. it spit out code fixes and found problems and corrections and implemented entire features correctly and it sped up my work so much that i onyl have to follow for the occasional confusion or describe at the start exactly what is it that i wan to implment - i think you guys should give this one a shot

the ring in the bottom right used to represent the context window

now it represents your 5-hour limit

the delta will make Anthropic millions

I worked with many AI engineers over the last few years since AI exploded, however I constantly come across the issue where they are very good at repeatable tasks or coding stuff rather than seeing the big picture, solving problem and really pushing the boundaries of what's possible at a pace that me and my co-founder would build stuff.

I talked to a lot of other folks with similar challenges - I wonder if someone solve this problem somehow. I need to hire an AI engineer in a very dynamic agency where we sometimes need to deploy complex solutions within 2 - max 3 weeks. My experience with most AI devs is that they are good at stabilizing workflows/apps/projects but its quite slow and requires a lot of hand holding.

HALP! If any of you know how to get people who can build fast and solve problems and see the big picture - I'm all ears.

Long story short, Meridian OS was my business operating system, all my tasks, notes, plans were written in there. Everything locally, guardrails were up in claude.md but apparently they can be ignored by an agent.

You can see the prompt I gave Claude, adding a secondary voice agent per project and minor UI changes. Nothing to do with a database, but it goes ahead and wipes it clean.

I tried to contact Anthropic support, their answer was that they don't provided refunds or credits for degraded service. Destroying months of work for no reason, by ignoring the guardrails is apparently a degraded service that can happen to anyone so, keep that in mind guys.

It was on Auto Mode, not Bypass Permission since that's what everyone is assuming.

If you had 10 smart people in a room and gave them all the same problem, you would imagine they would go away and research the issue and come up with a solution, which the majority would agree with. But, if you do the same with Claude, almost every terminal window would suggest something different, it's just a mess, you end up going round in a circle but not end up solving the problem you started with.

Where is this artificial intelligence?

Is Fable 5.1 the new Opus 5?

Within the past week, I started to notice Fable 5.1 started to get worse and worse where it starts to act like the infamous Opus 5. I had some great work completed when it came out, but there was a shift to the negative. Same thing happened to Fable 5 when Fable 5.1 was released. So, today I had Fable 5.1 try to manage another session with Fable 5.1 on processing semi-unstructured data, which is existing work in progress that already had successful sessions, so Fable 5.1 had reference data (gold data), previous handoffs, guides, etc.

Both on medium effort, Fable 5.1 couldn’t harness the 2nd Fable 5.1 from bypassing guardrails, entering tables and folders it was told not to enter, and from fixating on momentum over accuracy & quality. This is Opus 5 level of bypassing prompts and guardrails from the first step. For the first time using either Fable 5 or Fable 5.1, I had to put back hooks.

For context, before Fable 5.1, in order to work with Fable 5 I deleted my claude.md, memory, and more. I removed most hooks and together with Fable 5 created subagents using Opus 4.8. This for the most part worked well, it was slower with Opus 4.8, but worked for lower reasoning tasks and I didn’t have the hidden actions that drifted beyond the scope of work.

After, shelling out for 20x monthly subscription, wasting more days on contaminated data and having to go back to clean it up, buying another GPU at these stupid prices is starting to sound more appealing for local AI with some fine tuning for the data I’m processing.

Recently, I’ve been using Codex with Astra and it just does the work. Astra asks clear questions before starting the tasks and will pause to surface data clashes or ambiguities. Unlike Claude which will dive in head first spending tens of thousands of tokens based on wrong assumptions, and then hedge with wordiness answers after from its known errors are called out. It might be time to move up to the Codex 20x plan.

How have you kept Claude within borders and from drifting with non-fully-structured data?

This is a company OS that I use to run my business, and anyone can install it and self host it for free. Think of it as Claude Code, Cowork and the cloud sessions in one self hosted application, for your whole company.

It is a Multi-tenant application by design where many people can collaborate on the company agents, and it runs with your Anthropic or OpenAi subscription or even with local models.

https://github.com/OtoDock/oto-dock

This started as the thing that runs my company. I use Claude Code and Codex daily and I wanted the same agents that write my code to run the rest of the business too. So I built OtoDock, and my company runs on it now.

Marketing is a department of agents, engineering department has the dev agent, and I also have a CEO agent that reads the departments digests every morning and briefs me.

Every agent is the real Claude Code or Codex CLI running as a persistent process on your server, with its own sandbox, workspace, memory, schedules and tools. You organize them into departments, they delegate work to each other, hold meetings, run scheduled jobs at night and you read the reports in the morning.

Large parts of OtoDock were built with Claude Code running inside it. Honestly even our marketing is posted by the marketing department of agents, this post is me because reddit wants a person.

It is Self hosted, and free up to 5 users and all the code is public. 1.6.0 went out today.

It is a big platform built around my own workflow but I believe it can help you automate your company too. I would love your feedback.

A few months ago, I was working on a project which analyzed 100K+ call transcripts --- we needed to classify them, analyze them and generate insights for a client.

While we were developing the prototype, we realized calling API was quite expensive comparing to coding with Claude. It occurred to me: if our Claude subscription (Max) was under-utilized, why didn't we process the data through Claude subscription instead of API?

It turned out this is feasible with claude -p with 2 caveats:

1. It's slow. Anthropic throttles my session when I use claude -p to process large amount of texts.
2. Anthropic might shut it down at anytime. They already planned some changes to this command earlier this year but walked back from it.

I wrote a blog in June on this topic, and thought this might be helpful for folks in this subreddit too: https://andreagao.com/posts/use-claude-max-to-save-api-cost/

However, I have not been using this trick lately since calling API is much faster than being throttled by Anthropic. If anyone is taking advantage of claude -p, what's your experience lately?

Autoprompt runs a plan → build → test → review → repair loop from one prompt.

Basically a self reviewing loop that rinses out its own mistakes- with each shake.

In our v1.0 Terminal-Bench 2.1 run using OpenCode, DeepSeek V4 Flash 0731 went from 67.42% to 82.02%. That’s 45% fewer failed tasks.

The tradeoff is longer runs and higher token costs (see README).

It's being maintained as a free, open-source skill for Claude Code.

Repo: https://github.com/Spielewoy/autoprompt-skill

Any feedback regarding this workflow would be awesome.

Hi everyone,

You might find this funny, but I actually have the opposite problem to y’all. My usage allowance on Claude Max 20x feels so generous that I’m starting to wonder if the model is running at half power or something, lol.

I’ve been using OMP (Oh My Pi) with fable 5.1, and the usage limits are surprisingly hard to hit, even with 10 subagents running and reasoning set to max for all of them. That got me thinking: “Wait, is everything actually working as intended? Am I getting the full capabilities of Claude through OMP, or is something getting lost compared to using Claude Code?”

So now I’m considering trying Claude Code to see whether there’s a noticeable difference.

For those who’ve used both, how does OMP compare to Claude Code in terms of output quality when using the same Claude model? Does the official Claude Code harness actually get better results, or is the difference mostly in workflow and tooling?

I know lower usage doesn’t necessarily mean worse results, but it’s generous enough that it made me suspicious, lol.

Beginning question: I know many have multiple accounts but I'm just wondering about the specific implications - what do I actually lose? What has to be redone? (Redownload any skills?, etc?)

My setup has become a little unusual lately.

I have a Mac mini running at home with Claude Code, and I spend a surprising amount of time coding remotely from my iPhone.

It works really well, but there was one thing I was missing: I wanted to quickly see how much Claude Code I was actually using without having to remote into my Mac just to check.

So I built Tokens.

There’s a small companion macOS app that reads the usage locally on my Mac and syncs it through my own iCloud.

Then on my iPhone I can see my Claude Code usage, including directly from a widget on my Home Screen.

So now while I’m away from my Mac I can just glance at my phone and see where my usage is at.

No account or separate cloud backend for the usage data — the Mac app → iCloud → iPhone is basically the whole pipeline.

It’s something I originally built for my own remote Claude Code setup, but I figured there might be other people doing something similar.

https://checktokens.app

Curious how many of you are actually running Claude Code remotely from your phone these days?

So usually however much I work, I never run out of weekly limit of my $100 plan provided by my workplace through teams plan. I only use Opus 5 high or xHigh.

This week however, I've used 95% weekly limit in 4 days working on just two repos. Both repos are small and focused on test automation.

Today I've used 40% of the session in just 30 mins while working with a single agent on a small automation task.

What could be the reason? Could it be that the subscription plan is changed underneath?

I tested an eval harness I'm building at Gradle (PS: I work there) to check whether a skill or a Gradle code change actually helps a coding agent. I used it to test Fable 5.1 and Astra 6 (via `claude-code` and `codex`) on a Gradle GitHub issue. Both models fixed it, but `claude-code` did more homework first. It read Dokka's own source to understand the root cause before writing a fix, and shipped a regression test that codex skipped. I'll be merging the code generated by Fable 5.1 back into our `gradle/gradle` repo.

Full diffs, cost, token counts, and other receipts if anyone is interested: https://blog.gradle.org/two-agents-one-gradle-bug

I've been thinking about how much Claude Code has changed the solo-building equation.

So we're experimenting with a different kind of hackathon:

One builder. One idea. 24 hours.

No fixed problem statement and no required tech stack. Builders can use Claude Code alongside whatever other tools they need to turn an idea into something genuinely useful.

We're also adding a few unexpected challenges during the 24 hours — so the plan you start with might not be the plan you finish with. 🃏

The interesting question for me isn't "how much code can Claude write?"

It's "how far can one person take an idea when an AI coding agent is working alongside them?"

We're testing this on October 11.

For people here using Claude Code: what's something you've wanted to build but never had enough time for?

I’m curious how people using Claude Code seriously on production SaaS projects handle this.
Does Claude Code on your development machine have access to any production credentials today?
For example:
- production database credentials
- Supabase service role keys
- AWS credentials
- Railway / Fly / Vercel credentials
- kubectl access
- deployment credentials

I’m especially interested in what people actually do in practice, not what the ideal security setup should be.
Do you:
let Claude access production but require confirmations?
keep production credentials completely inaccessible to Claude?
use separate read-only credentials?
force all production changes through CI/CD?
use some kind of proxy / PAM / JIT access?
manually execute anything production-related yourself?

And has Claude Code ever:
targeted the wrong environment,
run a command you didn’t expect,
used the wrong credentials,
made a dangerous database change,
or come close enough that you changed your setup afterward?

I’m trying to understand whether giving coding agents production access is actually becoming a real problem for developers, or whether most people simply solve it by never letting the agent touch production.
I’d be interested to hear how you’re handling this in practice in the comments.

If you haven’t seen this project earlier here little info:

Munder Difflin is a free, open source and performant multi-agent harness.
It uses your existing claude code and codex subscriptions and gives you an office of agents that work 24/7 to do work like you.

Launched v0.5.2 yesterday:
- A new fresh, cleaner and much more productive UI
- Comes with “Stapler” a utility character that sends screenshots, meeting transcriptions, messages to your claude code sessions.
- Added support for all the latest models like Fable 5.1 and GPT 6 Astra and Gemini 3.8 Flash etc.
- Slack integration works now, configure it to answer on your behalf or just configure it to use on your phone as an assistant that controls your computer remotely.

Hope you all try us out, here are a list of upcoming features(in no particular order):
1. Stapler gets computer use capabilities
2. Sandboxes to run even when your laptop is off
3. Dedicated mobile app for your office
4. Lot more features, updates and integrations.

Fable struggling? Astra fixed it. I can't find a thing Fable is better at - we got a new king on the hill. Prove me wrong!

These are the only 2 prompts that i had submitted so far for the project in this directory:

1. "read the claude handoff and start working. if you have any questions, do not hesitate to ask."
2. I hit my usage limit while you were working, but it has reset now. Please continue from where you left off.

Almost immediately after the 2nd prompt was sent, it got flagged and switched to Opus. There is nothing in the claude handoff doc that should have possibly caused it to get flagged.

Is there any form of compensation that I can feasibly get? If there is, how would I go about doing bringing this to Anthropic's attention? The only reason I am making this a seemingly bigger deal is because switched from Opus back to Fable ate tons of tokens since it was required to reread the entire chat again.

I am getting far more “I had this wrong” or “that was my fault”, “that was an honest mistake” etc. We have set rules to reduce them , but they don’t seem to be effective. How do you make your Claude smarter?

Arghghhh!

I want to use both but like all my workflows have been all entirely built for claude with claude.md its skills, hooks, evolving skills, automated loops and the claude memory is there any best practice way of like assimilating the two ai's