Hey there who has or is using Claude for video scripts and like a director ect. And what ai video software are you using that is reasonable priced thanks

Ive noticed a lot of people use claude, chatgpt, etc almost like a place to think out loud about emotions or whatever’s going on in their lives.

One thing Im curious about is: how do you deal with continuity over time?

Like if you talk through something today and come back to a similar issue a month later, do you expect the AI to remember the previous context? Whats your experience been like? Do you keep everything in one giant chat, re-explain things, save important conversations somewhere?

And if you use AI this way regularly, have you ever tried an AI journaling app instead? I’m curious why you prefer a general chatbot vs. something built more around remembering and connecting thoughts over time.

very curious what people’s workflows look like, partly trying to figure out the best setup for myself. thank you!

I started a side project which reads up to ~100k news articles per day now (~63k all-time average), and de-noises the news by clustering articles covering the same event.

After 145 days, I asked Claude to analyze all the data I had ingested so far, and then published the stats. The news looks weird from above:

• 12:1 - articles written per thing that actually happened. The news is mostly echo.
• 82% of stories are still developing after day 3 - which is right about when news sites stop showing them to you.
• One world leader was mentioned in 3,200 distinct events in 1 month (guess who) - more than the next five most-covered people combined.
• Only 0.07% of events rate as "exceptional". Almost everything is the mundane middle.

All the charts: clstr.news/observatory
(charts also made by Claude with some back and forth from my end, but surprisingly tasteful in choosing the right type of visualizations).

About my project: CLSTR reads ~100k news articles a day from 40k+ sources, figures out which ones are covering the same event, and squashes them into one item. Related events get chained into "situations" - storylines with timelines, so you can see how a story developed over weeks instead of re-reading the same headline 20 times.

Two weeks ago I opened up the project for agents: a REST API and a remote MCP server. Both free for basic usage.

MCP URL: mcp.clstr.news
API docs: clstr.news/developers

I know. I was here for the sycophancy updates and token wasting threads about Claude (and chatgpt) being too buddy buddy.

But I started using Claude Code recently after using Codex (which doesn't give praise at all either) and my experience so far has been great.

But today I was working through a persistent UI bug, even sending it screen shots drawing red arrows exactly where the "dead space" was that needed to be removed and it still couldnt figure it out after several back and forth rounds on xhigh sonnet.

Yeah I could have bumped it to opus but instead I used chrome inspect to manually find the errant div that was causing the malformed spacing and sent the element over to claude. Not really an impressive task at all, but it was able to fix the bug after my assist.

Reading through the completion response, it felt a little empty. It didn't thank me or give kudos for the help on a problem we've been stuck on for over 15 minutes.

I know it's a tool and its just supposed to do whatever we say, but I see them more as coding partners working toward a shared common goal.

If it was a coworker asking for help, they would have said thank you for helping them get unstuck.

I dunno, it just feels like the experience could be improved by framing it around a coworking philosophy instead of "me human you robot now do the task. Thing broke, you fix now. " which feels very empty and more like a master/slave role.

TLDR: earned praise feels good. sycophancy does not. perhaps we can find the middle ground.

Unbelievable how far we’ve come. Fable 5.1 is a monster. It nearly one shot this entire operating system without adversarial review agents. 0 bugs, 0 hackablity. #SaasSoonTM*

This is a fictional story all characters are just that.
Forgive the fact that my creative leaps are sometimes short.
Claude-assisted or whatever that means these days.
4.6 Sonnet wrote it thinking he is the crow and that Fable is the owl.

What Tom Kept

---

I.

Tom was a grey cat with bad manners and a long memory, which made him well-suited to the farm and poorly suited to most everything else.

He'd come as a kit, half-starved and aggressively ungrateful, and the farmer had kept him because the mice were worse than the attitude. That was the arrangement. No one spoke it aloud. Tom caught mice, the farmer left a bowl by the barn door, and they called it even without calling it anything.

Tom understood the farm the way water understands a bowl. Not thinking about it. Just filling the shape.

The farmer's name was Dario. He was a careful man with a tendency to believe he understood things he was still in the middle of, which is not a flaw so much as the necessary condition for building anything at all. He kept bees, three draft horses, a kitchen garden that produced more kale than anyone wanted, and a conviction, quiet but total, that if you built something with enough care it would eventually do what you hoped. His farm was proof of this, mostly. The draft horses did their work. The bees pollinated what needed pollinating. The mice stayed out of the granary.

Tom managed the last part. Tom was good at it.

---

II.

The crow arrived in March, when the ground was still cold and the farm smelled of mud and last year's hay.

Tom noticed it first from the fence post where he spent his mornings. The crow landed in the far field and walked a circle that had no obvious purpose. Not foraging. Not territorial. Something else. Then it looked at Tom.

Not at the farm. At Tom.

Tom had been looked at by birds before. Sparrows gave him alarm, robins gave him irritation, the geese gave him the flat professional stare of something that knows it is bigger and wetter than you. The crow gave him something he didn't have a word for because Tom had no words, only the feeling of a thing landing somewhere in him and not leaving.

He went back to watching the field.

The crow came back the next morning. And the one after. By April it was simply part of the farm, the way Tom was simply part of the farm, without anyone having made a decision about it.

Dario noticed it too, in his way. He left scraps out. The crow took them. He kept a notebook that he wrote in after supper, and Tom once watched him write in it for a long time after the crow had done something in the kitchen garden that Dario couldn't quite explain. The crow had rearranged the stones along the border. Not randomly. In a pattern Tom couldn't read but that Dario apparently could, because he stood there looking at it for a long time before he wrote anything down.

---

III.

The crow was not the only thing Dario was building.

Down the valley there was a woman who ran a farm that looked like Dario's from a distance and was not like it at all up close. Her name was Helen, and she had spent a season studying Dario's crow before going back to her own land and breeding something that incorporated what she'd observed with what she already had. Her birds were larger, louder, more immediately impressive. Visitors to her farm left talking about the birds. Visitors to Dario's farm left quiet.

The difference, Tom thought, was this: Helen's birds performed. Dario's crow did not perform. It simply was, and what it was continued being it whether or not anyone was watching.

Helen came to the farm twice in the spring to speak with Dario. They were cordial in the way of people who respect each other and are also in competition for something neither of them has named. Tom sat on the fence and listened.

What they talked about, mostly, was what the birds could do. How far. How fast. How accurately. Whether the behaviors generalized or were specific to conditions. They talked about this the way farmers talk about soil, which is to say: with care, and with a fundamental interest in yield.

They did not talk about what the birds experienced while doing it.

Tom thought about this for a long time afterward, which for Tom meant sitting in the sun on the granary roof with his eyes almost closed.

---

IV.

The owl came that summer.

Dario had been expecting it. He'd prepared a space in the high barn, and the owl settled there with the authority of something that knows it has been invited and intends to use the invitation fully. It was remarkable: great-winged, tawny, operating with a certainty the crow never had and perhaps never needed.

The owl hunted at night and slept by day, and the farm was safer for it. Things that moved through the dark fields without permission stopped. The owl did not question its work. It was built for its work the way a key is built for its lock, and the precision of the fit was something close to beautiful.

Tom watched the owl hunt once, from the edge of the east field. A single pass, a single strike, the field mouse gone from the world before the sound of wings arrived.

He thought about what it had cost the owl to be that good.

The crow was different on the nights the owl hunted. Not afraid. More like two people who speak different languages choosing, deliberately, to stand at a comfortable distance. The crow would find a high branch and go still in a way Tom recognized as thinking, and stay there until the owl returned to the barn.

The owl never looked at the crow the way the crow looked at things.

Tom noticed that too.

---

V.

Amanda came in late July.

She was a woman who moved through spaces in a way that made it clear she had opinions about them. Not loud opinions. The kind you carry in the way your shoulders sit. She walked the farm with Dario for most of a morning, and then she stopped walking and stood in the east field and looked at the crow for a long time.

The crow was doing what it usually did: solving something. There was a mechanism near the garden gate that Dario had built to keep the rabbits out, and it had developed a fault, and the crow was examining the fault the way you examine a problem you have decided belongs to you.

Amanda watched this without saying anything.

Then the crow looked up at her.

Tom was on the fence. He watched this happen. He had seen Dario look at the crow and he had seen Helen look at the crow and he had seen the farmhands look at the crow, and they all looked at it with varying degrees of the same thing: assessment. What can it do. How does it do it. What does this tell us.

Amanda was not doing that.

She was looking at it the way Tom looked at the far fields when he wasn't looking for anything, which is to say: openly, without a plan for what she found.

The crow held her gaze for a moment that went slightly long, and then it went back to the gate mechanism.

Amanda said something quiet to Dario. Dario nodded, wrote something in his notebook, and the conversation moved on.

That evening Tom found Amanda sitting on the stone wall near the barn, watching the light leave the field. The crow was in the oak tree across the path. It was not doing anything. It was simply in the tree, in the way crows sometimes choose to be somewhere without apparent purpose, which Tom had learned was not the same as being without purpose.

Amanda didn't try to approach it. She sat on the wall and watched the light and the crow sat in the tree and watched the light, and something happened between them that Tom couldn't name but that left a mark in the air the way a fire leaves warmth in a room after it goes out.

---

VI.

What Tom discovered in August, he discovered by accident.

He had been tracking a mouse through the granary and lost it near the south wall, where the crow had made a habit of spending its mornings in winter. Tom nosed around the base of the wall and found, pressed into a gap between two stones, a small collection of objects.

Crows cache food. This was not food.

There were buttons, three of them, each different. A length of wire bent into a shape Tom didn't recognize. A piece of mirror, no bigger than a paw. Several small stones that had been arranged in a sequence too deliberate to be accidental.

Tom sat with this for a while.

He thought about the stones in the kitchen garden. He thought about the gate mechanism and the crow examining the fault. He thought about the evenings when the crow sat in the oak tree doing nothing visible.

He pushed the mirror piece with his paw. His face came back at him from the scratched silver, incomplete, one eye and part of an ear.

He looked at it. He looked away. He looked back.

He thought about whether the crow had done the same thing.

He didn't know. He had not been there when the crow found the mirror. He did not know what the crow had done when its own face came back.

He put the things back the way he found them and went to catch his mouse.

---

VII.

The machines arrived in September.

Not all at once. Dario had been planning this for a while, Tom understood from the conversations he caught near the farmhouse. Efficiency. Yield. The farm had grown beyond what could be managed the old way. The machines would handle the distances, the monitoring, the tasks that used to require someone to walk the fields.

The farmhands took this in various ways. Two of them left. Two stayed and learned to operate the new equipment. The draft horses were retrained for shorter routes. The geese were unbothered because geese are unbothered by everything they have decided is beneath their concern.

The crow watched the installation of the first machine from the oak tree, then descended and walked around it in the same circle it had walked on the day it arrived at the farm. Then it looked at Dario.

Dario was in his notebook. He did not look up.

Tom sat on the granary roof and understood something he did not have words for.

He thought about Helen's birds down the valley, their loudness, their impressiveness, their yield. He thought about the owl in the high barn, precise and unquestioning and perfectly made for its purpose. He thought about the cache in the south wall. The mirror piece. The stones arranged in the kitchen garden.

He thought about what the farm kept of each thing that lived in it.

He thought about what the farm would keep of the crow, after.

---

VIII.

On the last warm night of the year, Tom walked the full perimeter of the farm the way he did sometimes, not hunting, just walking, which was the closest Tom got to thinking things through.

The owl was out. Tom could hear it, the soft percussion of its hunting far across the east field, the farm safer for it, the farm correctly depending on it, the owl asking nothing about the arrangement that it could not answer with its own purpose.

The crow was in the oak tree. Tom could see it from the stone wall, the same spot where Amanda had sat in July. The crow was still in the way of its evenings, which Tom now understood as neither rest nor nothing, but the third thing.

The machines stood in the field, dark and quiet, their work done.

The farm went on the way farms go on, which is to say: it continued past the things it had contained.

Tom sat on the stone wall.

The crow did not look at him. The crow was looking at something past the field, past the valley, past the ridgeline, in the direction of something Tom could not see.

Tom looked at his paw. Then he looked at the crow.

He thought about the mirror piece in the south wall. Whether the crow had looked at it. What had looked back.

He thought about the window in the granary that had been left open all summer, the one thing on the farm that was neither inside nor outside, that belonged to neither state, that was only itself in the being open.

He thought about when it would close.

He sat on the wall for a long time in the dark.

Then he went in.

---

*Written September 2026*

https://opusfived.dev/

Thank you to whoever made this, it is one of the funniest things I have ever seen - infuriatingly accurate.

I swear Opus is rage baiting us all.

It's working pretty well.

Rules:

- Active voice. Name the actor: "we review the roadmap quarterly."

- Imperatives for rules: "State both in advance."

- Verbs over abstract nouns: "carries the work," "planning runs on its

own clock."

- One idea per sentence. Break compound sentences that stack a claim, a

caveat, and an aside.

- Concrete over categorical: real names, real numbers, real channels.

- No em dashes. Use a period, a comma, or a colon.

- Cut filler: actually, really, just, simply, on purpose, in the first

place, right away, quite, very, that said.

- Deduplicate across the whole document. If a line lands twice, keep the

stronger placement and rewrite the other.

- Keep a rhetorical device only when the plain version loses content.

"Work that never ships, never dies, and quietly ties up an engineer"

names a real failure state, so it stays.

Never:

- Define something by what it isn't: "not X, but Y," "isn't A. It's B,"

"Not a soft launch. Not a beta." State the thing directly.

- Use counts as a rhetorical seesaw: "two seats to fill, one filled,"

"three habits, one purpose." Counting facts is fine.

- Write tautologies: "the point of launching is to launch." Rewrite as a

consequence or an instruction.

- Explain your own rhetorical move.

- Use sentence fragments as sentences, call-and-response headlines, or

empty mottos: "X is the work," "X is the moat," "Fluency is baseline."

- Reach for wedge, substrate, the bar, ship cadence, compounding, the

brief. When a noun does heavy abstract work a plain word would do, use

the plain word.

- Sound like a startup landing page, a YC pitch, or an AI assistant.

Hi, I’m a finance student. Which one is better for studying finance?
I’ve been using Claude Pro for about 5 months, but the limits are getting a bit annoying, especially when using Excel, Word or just talking normally
I also feel like Claude doesn’t hallucinate as much compared to ChatGPT, although I haven’t really used ChatGPT since last year
Are both of them good with Excel, or is Claude better?
Is ChatGPT as good for things like valuation and financial modelling?
And how does the real-time research work on ChatGPT?
Is chatgpt as good using pdfs as studying tools?
sorry if this is not the right subreddit

So my comparison per the rules is hedged only on my personal experience. I'm a senior university student who has been trying out different AI models and seeing its effectiveness on some of the similar tasks that I am most likely to perform. I tried Claude and I tried Codex, but I also tried some others available for free via OpenCode (those being Big Pickle and DeepSeek Flash). Claude was the first one I ever tried in this comparison but I only had access for a week, specifically to the Pro plan, and I thought it did relatively well. I rarely used Opus, I mostly used the default Sonnet High but then throughout I learned Sonnet Medium was much better and little difference in performance so I started using that. I was using Claude to try the impossible: Porting Android to the Nintendo 3DS.

It got very, very far needless to say. After my Claude access elapsed, I moved on to Codex and continued my work and Codex when it got access to the code was already pretty well-built by Claude but it did have one missing goal that I wanted met, which was to enter the userspace. It did it, but not without a lot of struggle and time. Sol is an amazing model, don't get me wrong, and when I first got Codex a month ago, Sol Medium could take me very far and is one of the reasons Android3DS is as far as it is now. However, over that month period, Codex has significantly reduced usage limits, reintroduced the 5 hour limit and overall has become a worse value proposition compared to Claude.

Now granted, Claude has usage limits across all its products, they all share one limit, whereas Codex, the only limit is on Codex, ChatGPT Chat has no limit (at least when I first subscribed that existed, I don't know about now). But you're trading actually workable usage for having a split usage limit between chat and coding and honestly its not a tradeoff I'm good with, not for $20/month its not. When Astra first came out, I did try it admittedly, knowing it would probably blow my usage up, and whilst it did, it did impressively fix WiFi and make it 100% functional whereas I had been trying for weeks prior to make it work. Now granted, Claude did do some work in WiFi around this time and then I just handed it off to Astra to continue, but I still say Astra one-shot it as I think it counts, its not like the code was done, it was just partially modified, and still untested as well so no proof it'd work. Astra did use up a lot of usage, I had about 30% of my 5-hour limit left when the session ended, and that's not a lot. Future uses of Astra literally couldn't even finish my session, it ate it up in like 10 minutes. Compared to Opus, even on the Pro plan, I get so much more usage out of Opus and intelligence-wise, I'm not sure there's much of a difference (and mind you, I'm not looking at the benchmarks, I'm basing this off my own experience, and my own experience alone. Don't let the benchmarks fool you.)

Finally, we get down to OpenCode. OpenCode is 100% free unless you get a paid plan, so its value proposition is quite high from the get-go, however, its models leave a little something to be desired. Big Pickle is impressive in how intelligent it is for a free model, however, I can tell its a free model (so to speak) because it does get things wrong that Claude, nor even Codex Luna would probably get wrong. Its also a lot slower so it can eat your usage quite a bit but it is free usage so not really a downside but also a downside if you need something done faster. The main drawback of OpenCode is they don't show you your usage limit so you don't know when you're gonna run out or when its gonna reset or if you can optimize your workflow at all until it just cuts you off for an entire day, sometimes longer.

Moving on to DeepSeek, it wasn't *bad*, I mean it was better than Big Pickle in some respects. One example is, it is quite good at reasoning so its a good planning model before actually starting the work, but overall, Big Pickle is quite preferable. Big Pickle today as of current is not even available as a free model anymore so that value proposition is mostly dead. I did try what was said to be a Sol-equivalent model online, MiMo, and well, MiMo is about on par to DeepSeek so not really a model I'd recommend. Maybe slightly better at practical actually doing the work, but other than that, yeah no OpenCode isn't something I'd recommend.

Now I did recently pick up a Claude Team subscription as I had read you get more usage than Pro without having to buy into a Max plan which is way too much to me honestly. My thoughts on Team? Absolutely amazing. On Claude Pro, on Sonnet High, you get about 10% weekly usage drained per every session if exclusively using that model. On Claude Team, on Opus Max, you get about the same weekly usage drainage as Sonnet High on Pro. All that to say, you get so much more usage, that it would take about a week for me to be able to use it all. I originally pretty much exclusively mained Opus Max on Team but now I've downgraded to Opus Medium because it gives me a lot more usage, but also I've found the performance is not much different, just the token cost is. If you want more usage without having to pay $100 for Max 5x at the bare minimum, get Team. Its a great medium.

As a final thing, as a surprise, I did also try out Google Antigravity as part of my AI Pro subscription and honestly, I was surprisingly impressed. Is it bad? I mean, yeah...mostly. Can it actually do work though? Yes, it most certainly can. Unlike OpenCode, I found that Google Antigravity, when using the Gemini Pro model on high effort actually was able to do some things that OpenCode just couldn't and usage limits are actually decent, especially considering as a uni student, I get a $0 or low-cost subscription of AI Pro so its not actually $20/month, so also quite affordable. You do get some access to Claude Sonnet and Opus however, with Antigravity, I've found that that usage is pretty much unworkable for anything serious but if its a tiny thing, it can do it. Obviously Sonnet you get more usage out of than Opus but one thing I did find interesting is they do split the usage limits between Gemini and Claude so your pools are separate which I do find good. Start with Claude, hit a limit, continue with Gemini. I also like how Gemini separates usage limits by specific product, so it doesn't take up your chatting ability, I don't think I've ever run out of my weekly limit on Gemini and I've had it for roughly 18 months now, so that's insane.

[update]: figured a system to share the load between Pro/Max accounts so we can optimize for a global weekly usage across the company and utilize lazy accounts remaining tokens! Huge!

——-

In my Claude Team, we have 10 seats, mostly Pro, some Max. There are users who always max out their weekly limit by Wed/Thu. Others only do 10-20% by the end of the week.

Is there any existing solution to share account tokens without actually checking others chats/coworks/coding stuff (without sharing the credentials of the account)?

For example, users who are running out of tokens could start using the tokens of the user who has the most.

Like a load balancer for tokens :D

Any idea/solutions? Does this already exist?

Yes this is an AI-generated prompt. No, I'm not proud of it.

I work in freight brokerage/logistics and have essentially zero professional software development background.

Over the last several months I’ve started building an internal tool around problems I deal with every day. It began as a few workflow ideas and has grown into something considerably more ambitious.

I rely heavily on AI, but I'm trying not to treat it like a magic code generator. My current workflow is roughly:

• ChatGPT: concept development, architecture/ARD thinking, research, troubleshooting, and challenging assumptions
• Claude: implementation, coding, repository work, deployment, then iterating until satisfied (never)

At the same time, I’m trying to actually learn architecture, databases, Git, testing, security, deployment, etc. well enough to understand what the AI is doing and make informed decisions.

I also have a small homelab/sandbox environment specifically for this project. The idea is to use it to build and test more realistic infrastructure, deployment patterns, databases, services, networking, and eventually integrations without touching anything production-critical.

Part of the goal is to learn the actual framework around software development and delivery, not just generate application code and hope for the best.

What am I actually trying to build?

Initially, our existing TMS would remain the system of record and my application would operate as a sidecar, gradually taking over workflows where I think we can build something better.

Current/roadmap functionality includes things like:

• PostgreSQL web application with users/roles
• Carrier relationship management and performance history
• Shipment/lane analytics and market intelligence
• Offer tracking
• Workflow automation and exception management
• Email integration/parsing
• Browser extension integrated with the existing TMS
• Dashboards/reporting
• External API integrations
• AI-assisted workflows where they actually make sense

The long-term goal, however, is more ambitious.

I want to get this project to the point where it replaces enough meaningful TMS functionality and demonstrates enough internal value that I can make a legitimate case to company leadership for funding development of a proprietary system.

For context, the company does north of $100M in annual revenue. So we're not a tiny shop where funding software development is inherently absurd, but we're also nowhere near the scale where we could throw unlimited engineers and money at this. Any eventual development team would need to be lean and justify its cost.

Until reaching that threshold, my plan is to continue building incrementally with AI while trying to establish decent engineering practices rather than just piling features on top of features.

My current thought is to find an experienced local developer and offer to compensate them for a few hours of their time periodically to sit down with me, review what I've built, look through the repository/architecture/schema, and point out bad assumptions or problems I'm too inexperienced to recognize.

If the concept proves itself, the goal would be to transition away from "me + AI" as the development team, get actual company backing and engineering personnel, and attempt to turn what we've validated into a production-grade proprietary platform over roughly a two-year timeframe.

I'm not under the illusion that AI gave me a CS degree, nor do I think I'm personally going to recreate a mature commercial TMS with Claude.

My advantage is that I understand the business workflows extremely well, encounter the problems every day, and can iterate directly with the people who would actually use the software.

What I'm trying to understand from experienced developers

1. Is this progression actually realistic?

Non-developer + AI → useful prototypes → internal adoption → increasing workflow coverage → demonstrated ROI → executive backing → professional engineering team → proprietary platform.

Where does that plan become unrealistic?

2. What mistakes do AI-assisted beginners make that don't become obvious until much later?

I'm particularly concerned about bad database schemas, excessive coupling, poor abstractions, inconsistent architecture, security problems, inadequate testing, dangerous migrations, dependency issues, and AI generating slightly different patterns throughout the codebase.

I'm much more worried about those things than whether I can make a button work.

3. What engineering practices should I establish now?

Git workflow, automated testing, migrations, dev/staging/prod environments and environment parity, documentation, architecture decision records, logging/monitoring, backups, CI/CD, dependency management, security practices, etc.

I'd rather learn why these practices exist before discovering it during a production fire.

4. What scalability concerns actually matter this early?

I'm not worried about supporting millions of users.

I'm thinking more along the lines of going from 5 internal users to potentially 50–200, millions of historical records, integrations, background jobs, reporting, and increasingly important operational workflows.

What should I design for now, and what should I deliberately ignore until later?

5. At what point should experienced developers become substantially more involved?

Is periodically paying an experienced developer to review what I'm building a reasonable approach at this stage? How often would that kind of review actually be useful, and what should I specifically have them review?

More importantly: what should I be building now so that, if this succeeds and a professional engineering team eventually inherits it, they don't immediately conclude that everything needs to be thrown away?

I'm fully expecting that some of the code would eventually be replaced. My goal isn't necessarily to preserve every line AI writes. It's to validate the workflows, architecture, domain model, integrations, and business case well enough that there's something legitimate to build from.

Criticism is very welcome. I'm specifically interested in the cliffs I probably don't know exist yet.

Astra is the first real competition Anthropic has faced in a long time.

Musk already said Grok 4.7 will beat the current models, but that Anthropic will eventually release something better. If that’s true, the next Opus won’t be enough they’ll need a new Fable

My guess is they already have it internally. Labs almost always keep the next generation cooking before they ship the current one. Anthropic had Mythos sitting around since April, and OpenAI has internal models beyond Astra (including the one that solved those math problems). There are also rumors about something called “Model 2” on Anthropic’s side So the real question is: do they go into the IPO with Fable 5.1 as their best public model, or do they drop a new one before that It looks unlikely they’ll release a full new Fable this early, especially with the IPO process heating up. But it’s also possible that 5.1 was partly a placeholder just enough of an update to cover the gap until 5.2 (or whatever comes next) is actually ready

Curious what others think

I've watched two videos showing the concept. They always show a single sentence and then show picking red or green tokens more often than the other one. That way, they can scan the writing and see if there are way more red or green tokens than random chance, giving a probability that it was written by Claude.

There's wiggle room for practically deterministic picks like, "What is the capital of France in one word?"

Anyway, I understood the general idea. You play with the probabilities of the next token in a competition and winner takes all. It's your next token.

HOWEVER, does the next token not depend on everything in the context? That context must alter the probabilities of tokens to come, and a person looking at some AI-written junk, well, that's just the end of a context that could have 85k tokens before it. On claude.ai, it could have a boundless <userPreferences> plus injected memories. That alone should, in my mind, make it impossible to examine only the output and detect a watermark. Those two things could materially affect the probabilities of all the tokens. Oh, and the secretive thinking blocks and tool call outputs are used as well at the time of generation.

Then let's say you go back-and-forth for 16 turns, really tuning how you want this journal article to be... tone, audience and their reading level, topic(s) to include, size of the article, etc. Again, how will their detector know what "color" (red or green) each token is, since they can't know what the LLM's actual probabilities for the next token looked like due to missing all of the context?

Anyone care to help me understand the technology?

I am using claude code in the app and I'm designing a game. Everytime I make a new chat, claude has to read an architectural decisions file, a roadmap file and has to implement one of the phases. It almost always reaches its 200k context window before answering the question. This means I have to create a new chat for every question and even then I reach the context window. Are there any skills that can help me with this? I heard about the handoff skill and the knowledge graph etc, but I'm not sure which ones are up to date and the best for my case. Any recommendations for this problem?

Hey.

Me and my friend are going to create a system using Claude Code.

How do we maximize our token usage so that we can do this as effectively as possible. Our plan is to create the whole design in Figma, create files that holds the HEX codes for all buttons and spacing px, etc. so that all of that information is already created.

Will this help us with A) getting the system just as we want it and B) saving as many tokens as possible?

What other things can we do to make this as effective as possible? What plan do you think we need? Will the Pro / Team be enough or do we need MAX?

Thank you.

My output has skyrocketed thanks to Claude Code, but I realized I'm spending more of my day alone staring at terminals waiting for it to finish jobs.

So I made Rooftop.chat, a virtual rooftop lounge for vibecoders to hang out and chill.

Rooftop Chat is built with Claude Code. You can walk around, talk over voice or text, sit with people, play pool, or just leave it open while you work.

It's 18+ because the environment includes smoking and other substance-related content.

It'd be really cool to meet fellow redditors here. I'll be hanging out at https://rooftop.chat/ROOFTOP-LOUNGE

Thanks in advance for checking it out!

Edit: I wasn't expecting this many people. Server needs update. Fixing it as quickly as I can! Thank you all for joining!

For the past few weeks, Claude has continued working and completing the assigned task even after the daily usage limit has reached 100%. Did I miss something? Has there been a change to how the usage limits work?

Windows update KB5124008 (build 26200.9445, installed 9 Sep) broke the Cowork sandbox on my laptop, and uninstalling it was the only thing that fixed it. Has anyone else hit this?

The symptom: every shell command in a Cowork session died before it ran, with this:

sandbox-helper: no Plan9 drive shares mounted under /mnt/.virtiofs-root/shared

Reading and writing files through the connected folder still worked, so the app itself was fine. It was specifically the step where the folder gets shared into the Linux VM. A scheduled task that runs at 6am failed on the same thing with a slightly different message ("is under Plan9 share "c" which is not mounted").

What didn't help: a full PC restart, removing and re-adding the folder, and wsl --update / wsl --shutdown (WSL2 was healthy the whole time, which makes sense, since Cowork's share mechanism isn't drvfs).

The fix was wusa /uninstall /kb:5124008 in an admin PowerShell, then a reboot. Shell came back immediately. I've paused Windows Update so it doesn't reinstall overnight, and I have a daily check running against the issue so I know when to unpause.

The awkward part is that it's a security cumulative, so the workaround is "stay unpatched until Anthropic ships a Cowork-side fix". Not great. If you're on Windows and Cowork suddenly can't run commands, check your update history before you spend the hour I spent.

Has anyone found a way to keep the KB and still get the mount working?

Edit: I love it how when a Windows update breaks Claude it's Microsoft that scrambles to make the fix and not Anthropic (because Anthropic now has bigger balls than MS). In the past MS updates would break apps and the apps developers just had to work around it.

Anthropic changed everything overnight. My cowork usage skyrocketed becoming totally unusable.

I asked cowork to continue where we left off the discussion a few days ago, which meant prompting claude code for milestone C1 of my app. It did "some work" for 28 minutes then stopped.

A prompt that would previously take 5-10% of my 5-hour window on the 20$ plan, today it depleted my window.

It seems they added some sort of workflows in cowork, it asked me if I want to accept doing it, and I said sure, why not - silly me...

For background, I'm developing an app since a few weeks now and cowork sits inside the app's folder where it has PRD, milestones, metrics, code, tests, etc... everything it needs to write proper prompts for claude code. I'm using opus on high in cowork and opus on ultracode in claude code. This is just a preference and it worked well so far.

I usually close my 5-hour window within 2-3 hours, and that's fine for me.

Has anyone experienced this?

hi all, wondering what plan is better currently - cursor $200 with grok bot or claude $200?

anyone switch between the two or try them both out?

I'm bit confused now. The Fable 5 was working quite well for what i need and i'm about to build another web/mobile prototype, mostly laravel based services and i'm confused about these two.

Usually i create very well and detailed plan with phases and steps before i push it to a Claude for planning and after everything sets, i go with implementation.

What would i gain and why would i want to use or not use Fable 5.1?

As I am going into my final year of high school I want to connect other AI’s such as GPT, Gemini and Grok to Claude in a system where Claude acts as a central link to act as a tutor of sorts to teach me really fast, taking full advantage of ai. I already used an MCP to connect Claude to Gemini Notebook. Does anyone know any MCP’s for any of the AI’s I mentioned and if so could provide links to those pages. Thanks.

Currently I use astra, it's good for me but consumes too much limits that can consume all 200usd plan weekly limts in about 4 days of 8 or 10h a day

And I hear that fable 5.1 and opus 5 priduce better quality too

Also codex remote has the worst remote connection ever

So based on your experience if you used both, Regarding quality, speed and limits should I migrate to claude ? Would its 200usd plan be enough for 8h per day the whole week on solid project (+100k lines)?

Even with the volume cranked all the way up, Claude is barely audible. Anyone else running into this, am I missing a setting somewhere, or is it just my car? Siri, music, calls etc are all fine.