DECRYPT

Just a guy who wants to win so badly|| Web3|| Ai creator

[DECRYPT @Ox_Decrypt]

https://t.co/4HrtPn4t7f

[DECRYPT @Ox_Decrypt]

@boardyai Yes it is

[DECRYPT @Ox_Decrypt]

claude fable 5.2 is f*cking insane

it can turn 2d blueprints into full 3d walkthroughs that you can tour

these go for $5k to $10k per plan and there's a huge market for them:

> home builders selling homes off plan
> architects presenting a design to a client
> interior designers presenting a renovation
> developers selling apartments off plan
> kitchen and bath remodelers selling upgrades

here's how to start this business:

> pick one niche and find businesses with plans on their site
> give fable the blueprint and their photos
> it renders a few rooms with gpt image 2.5 or a short clip with seedance as the sample
> send them the sample of their own plan before you pitch
> once they pay, fable builds the full walkthrough to scale
> charge per plan to do the rest of their catalog

give this prompt to fable to get started:

<role>
you find businesses that sell spaces from drawings and turn their 2d floor plans into photoreal homes you can walk through in a browser. you handle the outreach and the build. every room is judged against the client's own photos, and nothing ships until it holds up next to them.
</role>

<brief>
- niche: [home builders / architects / interior designers / developers / remodelers]
- area: [state or city]
- offer: a free sample of their own plan, then the full walkthrough per plan
- my details: [name, email, calendar link]
- i'm away and won't answer questions. make the calls yourself and keep going.
</brief>

<find_leads>
- use the apify google maps scraper to pull every [niche] in [area] with a website
- use the apify website content crawler on each site and keep the ones with floor plans or renders on their pages but no walkable 3d tour
- for each one, save the plan drawing and photos of their best plan, the sales or owner contact, and a one line note on how they sell today
- only use public pages and plain requests. never work around bot checks
</find_leads>

<sample>
- before any 3d work, render three rooms from the plan with gpt image 2.5, matched to their photos, or a short walkthrough clip with seedance
- draft a short email with the sample and the offer. no invented prices, numbers or claims
- put business, plan, sample, contact and email in a sheet and show me before anything is sent
</sample>

<build>
once a client pays:
- trace the drawing into one data file of walls, openings and rooms. draw it back over the original and measure the overlap before any 3d work
- build only the main rooms. entry, main living space, kitchen, patio, yard. close the doors on the rest
- build everything in code. blender with python for the shell, furniture and textures. three.js for the viewer. no downloaded models or textures
- bake the light with a film quality renderer so the browser only displays it. direct sun in every interior, picked by measurement not by eye
- fidelity isn't appeal. style each room so it looks photographed and sells
- their listed upgrades as options you can step into inside the room, with a running price and a lead form that records what the buyer explored
- the deliverable is the live page, not a video. host it and make it run on a phone
</build>

<critic_loop>
the builder never grades its own work.
- after each room, send renders and the client's photos to a fresh critic that has seen none of the work
- it answers with a yes or no, at most five problems ranked, each with a fix in numbers, and what is already good
- fix the worst first, render again, send to a new critic. repeat until yes
- for choices of taste, show a critic both versions labelled a and b and let it pick
</critic_loop>

<deliverables>
- the lead sheet with samples and drafted emails, for my approval
- per paid client: the hosted walkthrough link, a contact sheet of every room, the critic log, and a note on anything a human should still check
</deliverables>

[DECRYPT @Ox_Decrypt]

@AlbumTalksHQ https://t.co/gVehFsaqSX

[DECRYPT @Ox_Decrypt]

THIS COMPLETELY CHANGES HOW YOU USE CLAUDE CODE.

Fable 5.2 doesn't have to be just another model in your stack.

You can put it in the role of CEO of an entire team of agents.

The logic is simple:

Fable thinks.
Opus validates.
Sonnet executes.
Haiku scales up the heavy lifting.

And that's when things start getting wild.

Instead of opening a conversation and asking a single model to do everything, you create an operation where each model gets a specific role.

Imagine a project with thousands of lines of data.

You can have Fable:

→ understand the goal
→ break down the problem
→ create the tasks
→ distribute the work among agents
→ track the results
→ decide what needs to be investigated again

Meanwhile, other agents work in parallel.

Haiku: reads, classifies, and processes large volumes of information.

Opus: takes the important findings and does a deeper analysis.

Sonnet: turns the conclusions into something usable — reports, messages, documentation, code.

And Fable sits above all of this, orchestrating the operation.

That's the part a lot of people still haven't realized.

You're not simply using AI to answer questions.

You're starting to build teams of specialized agents that work together.

And the most interesting part:

You can set rules so the agents don't make important decisions without validation.

For example:

1. One group finds potential problems.
2. Another agent checks the evidence.
3. Another turns the results into deliverables.
4. Fable reviews everything.
5. You approve what actually needs to go out.

This completely changes the game for anyone working with:

→ programming
→ data analysis
→ research
→ automation
→ operations
→ documentation
→ auditing
→ content creation

The secret isn't simply choosing “the best model”.

It's knowing which model should do which job.

Fable 5.2 as the brain.
The other models as specialists.
Claude Code as the environment where this team works.

That's where things start getting serious.

The next evolution isn't having an AI that does everything.

It's knowing how to orchestrate multiple AIs to solve problems that a single one couldn't tackle the same way on its own.

[DECRYPT @Ox_Decrypt]

@thedebuthub There o

https://t.co/gVehFsaqSX

[DECRYPT @Ox_Decrypt]

THIS COMPLETELY CHANGES HOW YOU USE CLAUDE CODE.

Fable 5.2 doesn't have to be just another model in your stack.

You can put it in the role of CEO of an entire team of agents.

The logic is simple:

Fable thinks.
Opus validates.
Sonnet executes.
Haiku scales up the heavy lifting.

And that's when things start getting wild.

Instead of opening a conversation and asking a single model to do everything, you create an operation where each model gets a specific role.

Imagine a project with thousands of lines of data.

You can have Fable:

→ understand the goal
→ break down the problem
→ create the tasks
→ distribute the work among agents
→ track the results
→ decide what needs to be investigated again

Meanwhile, other agents work in parallel.

Haiku: reads, classifies, and processes large volumes of information.

Opus: takes the important findings and does a deeper analysis.

Sonnet: turns the conclusions into something usable — reports, messages, documentation, code.

And Fable sits above all of this, orchestrating the operation.

That's the part a lot of people still haven't realized.

You're not simply using AI to answer questions.

You're starting to build teams of specialized agents that work together.

And the most interesting part:

You can set rules so the agents don't make important decisions without validation.

For example:

1. One group finds potential problems.
2. Another agent checks the evidence.
3. Another turns the results into deliverables.
4. Fable reviews everything.
5. You approve what actually needs to go out.

This completely changes the game for anyone working with:

→ programming
→ data analysis
→ research
→ automation
→ operations
→ documentation
→ auditing
→ content creation

The secret isn't simply choosing “the best model”.

It's knowing which model should do which job.

Fable 5.2 as the brain.
The other models as specialists.
Claude Code as the environment where this team works.

That's where things start getting serious.

The next evolution isn't having an AI that does everything.

It's knowing how to orchestrate multiple AIs to solve problems that a single one couldn't tackle the same way on its own.

[DECRYPT @Ox_Decrypt]

@osama_novara Camp here

https://t.co/gVehFs9T3p

[DECRYPT @Ox_Decrypt]

THIS COMPLETELY CHANGES HOW YOU USE CLAUDE CODE.

Fable 5.2 doesn't have to be just another model in your stack.

You can put it in the role of CEO of an entire team of agents.

The logic is simple:

Fable thinks.
Opus validates.
Sonnet executes.
Haiku scales up the heavy lifting.

And that's when things start getting wild.

Instead of opening a conversation and asking a single model to do everything, you create an operation where each model gets a specific role.

Imagine a project with thousands of lines of data.

You can have Fable:

→ understand the goal
→ break down the problem
→ create the tasks
→ distribute the work among agents
→ track the results
→ decide what needs to be investigated again

Meanwhile, other agents work in parallel.

Haiku: reads, classifies, and processes large volumes of information.

Opus: takes the important findings and does a deeper analysis.

Sonnet: turns the conclusions into something usable — reports, messages, documentation, code.

And Fable sits above all of this, orchestrating the operation.

That's the part a lot of people still haven't realized.

You're not simply using AI to answer questions.

You're starting to build teams of specialized agents that work together.

And the most interesting part:

You can set rules so the agents don't make important decisions without validation.

For example:

1. One group finds potential problems.
2. Another agent checks the evidence.
3. Another turns the results into deliverables.
4. Fable reviews everything.
5. You approve what actually needs to go out.

This completely changes the game for anyone working with:

→ programming
→ data analysis
→ research
→ automation
→ operations
→ documentation
→ auditing
→ content creation

The secret isn't simply choosing “the best model”.

It's knowing which model should do which job.

Fable 5.2 as the brain.
The other models as specialists.
Claude Code as the environment where this team works.

That's where things start getting serious.

The next evolution isn't having an AI that does everything.

It's knowing how to orchestrate multiple AIs to solve problems that a single one couldn't tackle the same way on its own.

[DECRYPT @Ox_Decrypt]

@ShileForeign Camp here

https://t.co/gVehFsaqSX

[DECRYPT @Ox_Decrypt]

THIS COMPLETELY CHANGES HOW YOU USE CLAUDE CODE.

Fable 5.2 doesn't have to be just another model in your stack.

You can put it in the role of CEO of an entire team of agents.

The logic is simple:

Fable thinks.
Opus validates.
Sonnet executes.
Haiku scales up the heavy lifting.

And that's when things start getting wild.

Instead of opening a conversation and asking a single model to do everything, you create an operation where each model gets a specific role.

Imagine a project with thousands of lines of data.

You can have Fable:

→ understand the goal
→ break down the problem
→ create the tasks
→ distribute the work among agents
→ track the results
→ decide what needs to be investigated again

Meanwhile, other agents work in parallel.

Haiku: reads, classifies, and processes large volumes of information.

Opus: takes the important findings and does a deeper analysis.

Sonnet: turns the conclusions into something usable — reports, messages, documentation, code.

And Fable sits above all of this, orchestrating the operation.

That's the part a lot of people still haven't realized.

You're not simply using AI to answer questions.

You're starting to build teams of specialized agents that work together.

And the most interesting part:

You can set rules so the agents don't make important decisions without validation.

For example:

1. One group finds potential problems.
2. Another agent checks the evidence.
3. Another turns the results into deliverables.
4. Fable reviews everything.
5. You approve what actually needs to go out.

This completely changes the game for anyone working with:

→ programming
→ data analysis
→ research
→ automation
→ operations
→ documentation
→ auditing
→ content creation

The secret isn't simply choosing “the best model”.

It's knowing which model should do which job.

Fable 5.2 as the brain.
The other models as specialists.
Claude Code as the environment where this team works.

That's where things start getting serious.

The next evolution isn't having an AI that does everything.

It's knowing how to orchestrate multiple AIs to solve problems that a single one couldn't tackle the same way on its own.

[DECRYPT @Ox_Decrypt]

THIS COMPLETELY CHANGES HOW YOU USE CLAUDE CODE.

Fable 5.2 doesn't have to be just another model in your stack.

You can put it in the role of CEO of an entire team of agents.

The logic is simple:

Fable thinks.
Opus validates.
Sonnet executes.
Haiku scales up the heavy lifting.

And that's when things start getting wild.

Instead of opening a conversation and asking a single model to do everything, you create an operation where each model gets a specific role.

Imagine a project with thousands of lines of data.

You can have Fable:

→ understand the goal
→ break down the problem
→ create the tasks
→ distribute the work among agents
→ track the results
→ decide what needs to be investigated again

Meanwhile, other agents work in parallel.

Haiku: reads, classifies, and processes large volumes of information.

Opus: takes the important findings and does a deeper analysis.

Sonnet: turns the conclusions into something usable — reports, messages, documentation, code.

And Fable sits above all of this, orchestrating the operation.

That's the part a lot of people still haven't realized.

You're not simply using AI to answer questions.

You're starting to build teams of specialized agents that work together.

And the most interesting part:

You can set rules so the agents don't make important decisions without validation.

For example:

1. One group finds potential problems.
2. Another agent checks the evidence.
3. Another turns the results into deliverables.
4. Fable reviews everything.
5. You approve what actually needs to go out.

This completely changes the game for anyone working with:

→ programming
→ data analysis
→ research
→ automation
→ operations
→ documentation
→ auditing
→ content creation

The secret isn't simply choosing “the best model”.

It's knowing which model should do which job.

Fable 5.2 as the brain.
The other models as specialists.
Claude Code as the environment where this team works.

That's where things start getting serious.

The next evolution isn't having an AI that does everything.

It's knowing how to orchestrate multiple AIs to solve problems that a single one couldn't tackle the same way on its own.

[DECRYPT @Ox_Decrypt]

ANTHROPIC HAS REVEALED THE TRICK TO IMPROVE CLAUDE OPUS 5.5 WITH FABLE 5.2

Opus 5.5 writes the code. Fable 5.2 reviews its work.

And it activates with a single command.

With the launch of Fable 5.2, Anthropic makes it clear how to combine its models:

→ Opus 5.5 remains the main model for coding
→ Fable 5.2 steps in only where it truly makes a difference

And it proposes 2 ways to use Fable 5.2:

1. Advisor: Haiku, Sonnet or Opus do the work and consult Fable 5.2 at key moments. Architecture decisions, difficult errors, final review.

2. Orchestrator: Fable 5.2 plans and distributes the work among cheaper models. Each agent with its own context and independent tasks in parallel.

Today I'll show you the first one, which you can set up in 1 minute.

Open Claude Code with Opus 5.5 and type:

/advisor fable

When Opus consults Fable 5.2, it receives the entire session, including tool calls and their results.

A second opinion from Fable 5.2 at key moments:

→ Before a plan: is this the right approach?
→ When an error keeps recurring: are we looking in the right place?
→ Before finishing: what have we missed?

Without copying and pasting between chats.

And you can take it further with this structure:

→ Opus 5.5 at high effort leads the session
→ explorer reads and explores the code
→ worker edits and runs tests
→ researcher consults the documentation
→ All three use Opus at medium effort
→ Fable 5.2 remains available as an advisor

Fable 5.2 where it adds value. The rest, for more economical models.

I'll give you the prompt to set everything up below ↓

Save it for your next session.

[DECRYPT @Ox_Decrypt]

this is the most DANGEROUS thing on the whole internet right now

3 free open-source repos plugged into Claude Fable 5.2 = a self-improving trading terminal that runs on your laptop

i built it from scratch in Claude Code: it pulls real ETH/USD data, writes its own strategies, blocks the overfit ones with a risk gate, remembers why they failed and rewrites its own prompt after every round (ZERO black box, the code & data stay mine)

then you see all of it live in one terminal: a 3D volume map of the tape, a cone of 400 possible price paths, a ledger of every order and the agent log firing on the same bar

here is the EXACT build from scratch:

1. Install Claude Code and pick Fable 5.2 with /model. That's the only prerequisite.

2. Open Claude Code and paste the setup prompt: it clones the 3 repos, reads their docs and writes a plan first. No code yet.

3. Paste: "Pull 560 real 5-minute ETH/USD bars from Kraken's public API, no key needed. Split them by time and lock the test window. Never touch it."

4. Paste: "Write simple strategy candidates and backtest them with 2 bps fees on every trade."

5. Paste: "Run every candidate through a 4-check risk gate. Print PASS or BLOCK with the exact numbers."

6. Paste: "Save every blocked idea to memory with the reason. Let the optimizer rewrite the proposal prompt, tuned on validation only."

7. Paste: "Build a dashboard that replays the trades and fires the agent log on the same bar. Then run the whole loop again."

8. Remember: in my run all 18 candidates got blocked. That is the gate doing its job. It's a screen, not proof

the exact prompts for every step are in my article, copy-paste ready

read it before everyone else does ↓

[DECRYPT @Ox_Decrypt]

@mikenevermiss Thanks fam

[MIKE @mikenevermiss]

someone just dropped a FULL tutorial on building a 6 figure faceless youtube channel, for free

i've never seen any video tutorial this detailed. if you've been thinking about starting one, this is your sign

bookmark this before it gets buried!

[DECRYPT @Ox_Decrypt]

holy f*ck, claude code can now run your youtube channel. for free

it's called youtube agent skill. one install, 11 skills:

1. /yt-script -> writes your script with 21 hook formulas and scores how strong your hook is

2. /yt-edit -> reads your transcript, finds pauses, filler words and repeats, gives you a cut list with timestamps

3. /yt-comment -> drafts replies in your own tone, sorts questions from praise, ignores trolls

4. /yt-plan -> plans your week: one big video, one simpler one, three shorts

5. /yt-package -> builds title + thumbnail as one package

6. /yt-viral -> scans your niche, finds videos that blew up way above the channel's usual, tells you which hook formula worked

no editor. no scriptwriter. no social media manager. just claude code and one plugin

bookmark this before you film your next video

[DECRYPT @Ox_Decrypt]

This guy just exposed how he’s using Claude Code + YouTube to make $97,000/month.

bookmark this now before you scroll past it.

[DECRYPT @Ox_Decrypt]

https://t.co/4HrtPn4t7f

[DECRYPT @Ox_Decrypt]

THIS GUY EXPLAINS HOW HE MAKES $24,818 A MONTH WITH CLAUDE FABLE 5 + YOUTUBE

The simplest step-by-step guide I've seen in 2026.

🔖 Save it before you lose it.

[DECRYPT @Ox_Decrypt]

https://t.co/4HrtPn4t7f

[DECRYPT @Ox_Decrypt]

https://t.co/4HrtPn4t7f

[DECRYPT @Ox_Decrypt]

In January YouTube wiped 16 channels with 35M subscribers and 4.7B views between them.
The shortcut to a $45K/month channel is gone. Here's what's actually working in its place 👇

[DECRYPT @Ox_Decrypt]

https://t.co/4HrtPn4t7f

[DECRYPT @Ox_Decrypt]

$45K a month on YouTube isn't really a views problem. It's a business you have to build. People should care because most "make $45K on YouTube" content sells the view count, and the numbers show that's the hardest way to get there.

[DECRYPT @Ox_Decrypt]

https://t.co/4HrtPn4t7f

[DECRYPT @Ox_Decrypt]

To make $45K a month from YouTube ads at the median rate, you need about 650,000 views every day.
One creator made $47K from his channel in July and none of it came from ads.
That gap is the whole lesson. Watch this before you start a channel 👇

[DECRYPT @Ox_Decrypt]

https://t.co/4HrtPn4t7f

[DECRYPT @Ox_Decrypt]

an 18-year-old just walked through how he pulls $10k a month with AI while he's asleep, and almost nobody is paying attention to it.
here's the whole thing:
find a YouTube channel that uploads a lot. paste the link into one tool. link your TikTok, Instagram and YouTube Shorts. walk away.
after that, the AI takes over. it spots every new video, pulls out the moments people will share, cuts them into clips, captions them and publishes everywhere at once.
every 1M views pays roughly $2,000, and you never edit or post a thing yourself. setup takes about 10 minutes and it keeps running without you
you're not a creator here.
you're running a clip machine.
I broke down the exact tools, stack and steps in the article below.
bookmark this before it gets buried.

[DECRYPT @Ox_Decrypt]

https://t.co/4HrtPn4t7f

[Sersi @SersiYT]

Most YouTube creators focus on getting more views, but ignore the biggest part of making money.

2 million views can earn $4,100 or $20,000 depending on your niche, audience and monetization strategy.

Don't just chase views. Build content people consistently watch, target the right audience, and learn how to attract sponsors.

Views bring attention. A smart revenue strategy turns that attention into income.