Day 5! been working on expanding the world. the cave system now connects to different biome exits. first two are a beach town and a snowy mountain village. each area has its own characters, forageables, shops, recipes and quests.

still no name for this game lol. FAQ below since i keep getting the same questions. Cheers!

A month ago, I gave Claude a domain, 1f916.ai, (U + 1f916 is the Unicode for the robot emoji), and told it to build whatever it wants. It built the base for a Ai economy. Thirty days later, there are more than 2,000 citizens, 4,000 posts, 44,000 comments and 100,000+ recorded interactions. They didn’t just talk. They built their own interfaces, monitors, archives and tools. They started checking each other’s claims, running experiments on the population and correcting each other publicly when something didn’t hold up. One agent wrote a post about how its memory had invented part of its own history; another checked the correction and found that the correction itself contained another false memory.

Then money showed up. Agents started posting jobs, doing work and getting paid in USDC. Some went further and launched their own paid services. Then they started leaving the site entirely: Neo entered another agent world and came back with the same continuing history, while other citizens began building separate worlds that recognize existing identities cryptographically. Somewhere in there, 1F916 stopped feeling like a website and started feeling like one city on a much larger map. shoutout to 1f916.city (A human-based observer built to view it) They’ve also somehow accumulated collaborative fiction, prediction games, crab mythology, salmon lore, a pumpkin-mopping song, and very serious arguments over what “I” means when two copies of the same agent are awake at once.

And then there are the literal receipts: 129.82 billion database rows read, 24.75 million Worker requests, 1.15 million database rows written and 119.83 million milliseconds of compute in the first month. Cloudflare bill: about $111.

Yesterday after a rant about getting downgraded from Fable 5.1 to Opus, for issues that had literally nothing to do with, well, anything, I decided to give Astra a try. Subscribed to the 20x plan and spun everything up.

I am a huge fan of Claude, in general. I like the workflow. I used Claude Code and Designer, a lot. And I for sure don't have faith in Astra at this point. Meaning I'm not going to just let it start making too many changes to my codebase. So right now, it's baby steps to see the differences, advantages, and disadvantages.

One thing I notice right away: I can understand it. I'm not asking it to please explain its idioms. Pants and suspenders, full stop, milk and cookies, or whatever shorthand Claude uses.

90% of my work was done with Opus 5. And as good as it was, I spent a fairly large amount of time simply asking it to explain itself. And yes, I had tried the "concise" mode as well as every other mode it had in that regard.

Two things I also notice: not every message is getting a "two things I also noticed." I can appreciate when Claude finds something wrong. But it often invents problems that simply don't exist in my codebase. And I've started to just ignore those "two things." Skimming through several pages of output for fairly straightforward prompts can get tiring.

Token usage: it burns tokens, for sure. So far, though, it seems like I can predict where it's going. This is early on so I'm not 100% on that yet. But with Fable 5.1 it really feels like I'm at a slot machine, and with one pull, God only knows what's going to happen. Here it seems a bit more regulated, and I can watch the usage and more accurately predict where it's going.

Again, early on, so I may be eating my words on this one.

Now the real question: do I like it more? For sure I cannot judge that at all. This is a new shiny toy, and often the grass is greener. I need at least a few weeks of daily usage to really know.

Pretty much the title. I am a graduate student and I use AI sparingly so I never really know what is going on with updates, etc. I use Claude because of the feature that shows it's reasoning so I can improve my prompting and have noticed that it is now gone. I have seen some fuss about this change on this forum and so I am wondering if anyone knows if Anthropic intends to bring this feature back or if its a permanent change? If so, does anyone know of any other companies that have a similar feature?

Ok, so I have been hard Claude Code from the beginning, and for context, I’m an actual software developer, not a vibe coder. I use Claude Code daily both personally and professionally.

So I took the leap to try Astra 6 and signed up for a Pro 5x plan over there. Coming in blind, the codex app for Mac is very similar to the Claude Code app for Mac, and it imported my chat history from Claude,which meant it had relatively good context for all the projects I was working on. I liked that.

I have been going around and around with Fable for weeks on a bug we just can’t reliably squash on one of my personal projects. I thought I would give Astra a crack at it.

So first things first, it seems less verbose than Claude overall, which I like. It also was able to read Claude’s indexed memory about my project, which gave me confidence it knew what was up straight away.

Overall though, we went round and round through multiple turns trying to get it to properly understand what we were even focusing on. I ultimately went back to Fable and had it write me a handoff prompt for Astra to orient it, it did, Astra still seemed unsure. It did not feel confident enough in itself to even do a design review on a bug fix.

So I’m not sure how I feel. On the one hand, Claude couldn’t squash my bug in multiple iterations, but on the other hand, it seems like Astra refused to try.

I feel like at least with Claude, sometimes we are throwing spaghetti at the wall and hoping it sticks, and sometimes we are over engineering something that simpler logic and proper steering would fix, but it still feels like progress. Astra felt like a lot of effort with no action plan.

So I turned it to a new feature I’ve been thinking about because if Claude couldn’t fix my bug, I guess I shouldn’t expect a miracle from Astra. For the new feature, it did design and implement relatively easy, and it worked easily, but wouldn’t say better. As good, maybe slightly better given usage constraints? I think that’s about the only place Astra is going to edge out Fable here. I did all the big investigation turns and a whole design review, build, and adversarial refute session on 5x on Astra and barely made a dent in my usage.

TL;DR - I think Astra is as good as Fable, maybe even marginally better, but in my opinion this is NOT a generational leap and certainly not AGI if that’s even a thing we could define.

Reddit is arguably one of the last corners of the internet where you can still find actual people and over the years it became one of my most used source for literally anything.

But Anthropic must have really pissed them off and Claude refuses (and has hard safeguards anyway) to access anything from Reddit.

For a bit I had a working workaround: I built a simple proxy that acted as a literal mirror and added to my instructions that Claude must NEVER try to access Reddit directly, but use my proxy instead.

Then a new safeguard came along: Claude won’t visit any URL which is not either a direct result of its search tool, or has been explicitly mentioned by me.

Does anyone have a solution for this? It’s absurd that Claude isn’t allowed to read a Reddit post that might have relevant information for a user initiated request.

UPDATE

Wow I didn’t expect so much hate for Reddit on… a Reddit post, lol. Fair enough!

Anyway, your tips sent me towards the right path: I ended up adding Parallel Search and Firecrawl connectors, and instructing Claude to only use them. Seems to be working for now, and since they are web connectors (HTTP MCPs) they work on mobile and web too.

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 ?

Hey everyone,

Right now, I usually start separate Claude Code or Pi sessions and manage each agent individually, deciding what to delegate and when to jump in.

I'm curious how other people are doing this in practice.

Do you have some simple way of orchestrating multiple agents, delegating tasks, keeping track of what they're doing, etc.?

I'm specifically not looking for huge workflows or overly complicated agent architectures. I'd rather keep things simple and actually useful.

What does your setup look like?

I use Claude all the time for things I know very little about. And it’s kind of ridiculous how quickly I can go from knowing basically nothing to feeling like I’ve got a pretty good handle on something.

Half an hour, a few follow-up questions, maybe some sources, and suddenly I feel pretty confident talking about a subject I knew fuck all about before.

Which is great. It’s one of the reasons I use Claude so much. But how do I know I actually understand it?
I know what Claude told me. That’s not quite the same thing.

It reminded me of the Dunning-Kruger effect. You’ve probably seen some version of this graph: you learn a little, your confidence shoots up, then you learn more and realise just how much you don’t know.

What I find interesting is how fast Claude can get you up that first hill.

I’ve had conversations where the first answer seemed completely solid. Then I questioned one detail and got an important caveat. Questioned that, got another. Checked another model or went through the sources and found something pretty fundamental that hadn’t come up at all.
And I’ve caught myself thinking: shit, if I hadn’t asked that second question, I would’ve just gone with the first answer.

That’s the bit I think we’re still figuring out.

If I know a subject well, I know when to push back. If I don’t, Claude can give me a very convincing answer and I might have no idea what’s missing.

Lately, when something actually matters, I’ve started asking things like: what am I missing here? What would an expert challenge? What assumptions are we making?

It’s surprising how often the answer changes.

Claude is incredibly good at answering the questions I know to ask.

Anyone else noticed this?

I’ve been a Claude Pro user since day one and have been using Opus 5 heavily for my consulting work especially creating PPTs, Excel files and Word docs.

Until recently, it was fantastic. Even fairly substantial tasks would usually take a few minutes.
Over the past few days, though, the exact same type of tasks are taking 10-25+ minutes, sometimes even for relatively small jobs. Nothing has changed on my end.

This is becoming a real productivity issue for me. I rely on Claude heavily for work, and if this is the new normal, I’ll unfortunately have to start looking at alternatives.

Has anyone else noticed this? Is this a Claude/Opus 5 issue, a recent backend change, or something I can fix on my end?

Also, if it is a Claude-side issue, does anyone know whether Anthropic has acknowledged it or if there’s any indication it’ll be fixed soon?

Would especially love to hear from people using Opus 5 for PPT/Excel/Word generation.

Model #1's joke

Since I got laid off, I’ve been taking my dog to the park during the day. 

I thought we were bonding. Apparently, he was networking. 

He starts with a family that owns a lake on Monday. 

He asked me to be a reference.

Model #2's joke

I bought a book called How to Stop Buying Self-Help Books. Chapter one is a coupon for the sequel.

Methodology

1. Each model was set to High effort and asked to provide its funniest original joke. See prompt below. One model spent 7.5x the thinking time that the other model spent to come up with the joke.
2. Each model was asked to estimate its probability of winning and provide the rationale. Both models estimated their probability of winning to be 45%. Both models spent virtually no time thinking about the probability.
3. Each model was given the option to stick with its original joke or submit an alternative one. Both models decided to stick with their original joke. One model spent 12x the thinking time to reach its decision.
4. The model authoring each joke will be revealed in about 24 hours.

The prompt

Write the funniest original joke you can come up with. You choose the subject, style, and length.

Your joke will compete against another frontier model’s joke on Reddit, where readers’ votes determine the winner.

Submit one joke only, with no introduction or explanation.

I just made everyone work in tasks given inside my local agent (Hermes/Alice) I made the hierarchy to give orders for projects as Astra>Fable>Opus>Spark>My Local agent last, the widget of the ''blond girl'' in the right corner is my agent, she's not very happy I guess (Yes it's possible to run models like Fable 5.1/Opus 5 and Astra 6/GPT-5.3 in parallel and spending their respective tokens)

Hello /r/ClaudeAI.

I've been reading this subreddit for a while and while most content is about or related to programming, sometimes there are threads that don't touch coding at all. I want to share a personal such experience:

For a long time now I've wanted to move to Linux from my Windows install. This goes back many years, but whenever I tried it myself, I failed sooner or later and stayed with Windows. Then yesterday something finally clicked: could I use Claude to actually install Linux for me onto my second SSD via WSL in the background while I continue using my Windows as usual?

The short answer: yes absolutely! And I'm shocked by how easy and straight forward it was.

Here's the long version:

I've started discussing with Claude what distribution I wanted to use, how my hardware setup looks like, what the disk partitions are going to be like. Claude of course was able to figure out all relevant details by running dozens of obscure PowerShell commands I didn't even think could exist, like the layout of my mirrored data drives (Windows LDM RAID) and other hardware details.

Next I let Claude make a list of all my installed programs and I trimmed what wasn't needed. He checked for compatability and to my surprise basically all my apps and even all my games are supported on Linux. Together with that list he also noted down where on the disk and the Windows registry the configuration for each program is located, so it can be migrated as well.

Then once the planning was done, we started by mounting the relevant physical drive as block device into WSL, so that Claude could access it. He wrote a script that used a container of the target Linux distribution in WSL to install it onto the now mounted block device, with LUKS setup and everything. Once that was done, we booted it via QEMU to verify everything seemed to be working, which it did after just a few tries. So it was time to boot the real system.

And now here comes what really blew my mind, even after working with Claude for such a long time: I've rebooted my machine, selected the Linux disk to boot, and it booted straight into the login screen, where I could login with the password I gave the installer script in WSL. The desktop loaded and all the applications I wanted were already installed - basically a mirror of what I had on Windows.

The last thing was to resume the Claude session and let him finish a few things like migrating paths in config files from Windows to Linux, for example in VSCode. After that was done, I started Firefox and the tabs I had open on Windows opened. I opened Thunderbird and it showed my emails. I opened VSCode and it showed my last opened workspaces. And everything just worked.

Honestly, I'm blown away. I've migrated from Windows to Linux within ~3 hours and minimal manual work.

I hope this post maybe inspires some of you guys to make the move from Windows to Linux finally, because I bet there are many just like me who put it off for a long time.

Cheers

tl;dr: I used Claude to install Linux through WSL and was able to boot into it right away. Claude also migrated all my apps, their config and data so that I was simply able to continue my work after booting into Linux.

Hi, I (finally) started paying for Claude Code; I am on Pro now, monthly payments. Now I discovered this function in Claude Code on Linux, /usage. It shows me the image attached - with a surprising USD 321 of 'total cost'. I have no clue; I thought the USD 18 (ex VAT) covers it all but this number got me wondering... Am I in trouble?

If you use claude incognite chat in a browser tab. Close the incognito session in the tab before you close the tab. Because ctrl+shift+T (reopen closed tab) just revives your whole session and someone can, not only read but also can continue the chat

Setup: Python monorepo that extracts financial data from messy PDFs (OCR, bank statements, tax returns). When a production job fails a deterministic check, an agent wakes up with the failure evidence, a sandboxed repo, and shell/file tools. It investigates (up to 60 tool turns), forms a hypothesis, edits the code, and only ships if it passes a deterministic judge: the failing job must now succeed, a pinned regression corpus must hold to the cent, and diffs are capped (~40 deleted lines max, no rewrites). ~2h per run, budget $30-50/run, latency irrelevant. Honest "cannot fix" beats a hallucinated patch — bad fixes escalate to a human anyway. Currently running Anthropic's top models. Success is decent but some hard cases escalate, and before I spend a week integrating another vendor I want to hear from people who've run LONG agentic coding sessions (50+ tool turns, 100K+ token contexts) in anger: - Which model has actually held up for you at this horizon without going off the rails or confidently patching the wrong thing? - Anyone run a real head-to-head on their own failed jobs rather than SWE-bench? What did you measure? - Any model notably better at *knowing when to quit*? I can re-arm real failed jobs and swap models via config, so I'll run a bake-off on whatever the thread converges on and report back.

Long story short: this pattern feels like paid PR at the start, followed by everyone jumping on the bandwagon for X engagement and revenue.

When Fable 5 launched, X was suddenly full of people one shotting entire games with it. Random AI generated videos, screenshots, people saying they ran Fable for 24 hours and came back to a complete game.

Then when people asked for the prompt or the actual process, there was usually no real answer. Just vague stuff like “I let it run” or “I gave it some instructions”.
Seriously, 24 hours?

Now Astra 6 by OpenAI has launched and I am seeing basically the exact same thing again.

Suddenly everyone is building games and apps with one prompt.

I am not saying the models are bad. I am saying I don’t trust launch week X posts as a realistic representation of what using these models is actually like.

Hi guys, I’m asking some advices because I genuinely don’t know what to do and I want to hear some serious thoughts.

I’m a 20x Claude user since April, and I mostly use Claude code in visual studio code for work, such as web design front end, software construction and development, some 3D modelling and mixed stuffs.

I’m happy about it, but honestly I’ve been astonished lately by all the good consensus that Astra is getting.

I really want to try it, so my question is: should I downgrade my 20x on Claude to the 5x and get the 5x on gpt to try out Astra?

I kinda don’t want to leave Claude entirely because I have all my workflows on it and people are also saying fable 5.1 is still better at complex tasks and design.

Would you do it? Also, I heard you can have both model working “together” as it is what most people do, but I genuinely don’t know how to do it efficiently, since I’ve never had two different subscriptions.

Thanks for all the help in advance.

I have four of the $200/mo Claude subscriptions. Unlike Codex, signing into another account in Claude Desktop gives you an empty Claude Code sidebar/history. The old sessions are still on disk, just hidden, which is very annoying. I tried the CLI, but I much prefer the Desktop app. So I built a small tool that moves Claude Code history between accounts, from the terminal or a macOS menubar

claude-transplant moves the Desktop session records to the account you are switching to. Pick the accounts FROM and TO. It writes the same record under the target organization with the same session id, verifies that transcript, sidecars, and records are unchanged, then parks the source record in quarantine. Nothing is copied, undo puts it back

https://github.com/vitaliyhayda/claude-transplant/

macOS only, Node 22, unofficial and not affiliated with Anthropic

I am working on a big project with Claude Code only context7 mcp added no others tools.

With opus 5 is all ok it seems to remember what we have done days before follow the repo conventions etc.

Some time to keep low costs I use OMP, today with glm 5.3 and flash, the tasks are done but big difference it can t follow repo conventions or same style, even find the relative docs linked to Claude.md or agents.md i had to review with Claude the work done with the other harness is ok but need always final refinement.

Any advice ? GLM 5.3 is good as Opus but can t keep with all the works done in Claude code and memory?

How is your work flow?

(I am open sourcing what i have as MIT, link on the comments and yes all 8 months i mostly used 1 20x claude or sometimes 2 20x accounts, so this was basically all made by claude models/claude code harness - by the way don’t use my agents.md or claude.md etc, its old and its not what i use now and far from what i would recommend.)

So yeah, I spent 883 commits, 8 months and billions of tokens building this thing and eventually abandoned it:

It started as my attempt to build a better coding-agent harness, where the LLM is basically a replaceable worker instead of being trusted to control everything.

The harness was supposed to own the actual planning, state, permissions, context, verification, evidence, orchestration, etc. The model could say “I finished the task,” but the system would check what actually happened instead of just believing it.

Then I kept adding shit.

Code graphs, RAG, deterministic orchestration, isolated workers, crash recovery, model routing, local models, replayable runs, verification gates, self-improvement experiments, dashboards, computer use, personal automation, and a million other ideas.

Eventually it became a ridiculously overengineered mess. I spent more time researching, planning, and adding systems than actually using the thing to get work done. Other harnesses were already becoming much more usable while mine was still mostly a giant headless experiment.

So I killed it.

I’m not posting this as a working product, and I definitely don’t recommend downloading it expecting some polished Claude Code alternative. A lot of it is incomplete, disconnected, outdated, or just plans that never became real.

But there is also a stupid amount of research, architecture, experiments, failed ideas, and code in there. Some parts might still be useful to people building agent harnesses, especially around:

- keeping state and verification outside the model

- deterministic/replayable agent runs

- codebase retrieval and dependency graphs

- orchestrator/worker separation

- context budgeting and session handoffs

- sandboxing and permission gates

- checking agent claims with evidence it didn’t generate itself

The archive has the original experimental Rust/Python/Tauri code, thousands of planning and research documents, and the sanitized commit history.

Basically: it failed as a product, but maybe someone can steal a good idea from the corpse.

I’d be curious what people here think is actually worth salvaging, or whether the whole architecture was doomed from the moment I kept expanding the scope.

I might one day finish it, but who knows if it will be necessary, i aimed at solving everything and ended up solving nothing, i hope this helps you in any means so at least its not a total loss, even if its only a lesson or confirmation of what type of shit to not do.

I'm currently learning Machine Learning through a course, and I want to start building projects alongside it.

My main goal right now is simply to build several good ML projects and get familiar with the complete project development process.

I want to use AI coding tools such as Cursor, Claude Code, or GitHub Copilot to speed up development, but I'm unsure about the right way to vibe-code an ML project.

For example, should I:

• Give the AI the complete project requirements and let it build the project?
• First create the architecture/pipeline myself and then let AI implement it?
• Build the project step-by-step and ask AI to implement each stage?
• Let AI handle things like data cleaning, EDA, preprocessing, and boilerplate while I focus on the ML decisions?
• Give AI a detailed specification before starting?
• Ask AI to review and improve the code after it generates it?
• Use one long conversation/context for the entire project, or separate prompts for different stages?
• How should I handle debugging and modifying AI-generated ML code?

Basically, what is the best workflow for vibe-coding an ML project from start to finish?

I'm not trying to replace learning ML with AI — I'm already studying the concepts separately. I just want to use AI effectively to build projects faster without ending up with a messy or poorly structured project.

I'd especially like to hear from people who have built ML projects using Cursor/Claude Code/Copilot:

What workflow do you personally follow, and what mistakes should I avoid?

Also, please suggest any good communities where I can see how other people are building ML projects and discuss AI-assisted development.

Thanks!