kapsoul.x

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[kapsoul.x @KAPS0UL]

3 seconds into the ¥$ Vulture’s album #Kanye

[Hamidullah Khan, PhD @IamKhanPhD]

GOODBYE LOGO DESIGNERS IN 2026.

Here are 10 Claude prompts that generate brand identity, visual direction, and logo concepts without hiring anyone.

Save this before it goes viral. 👇👇

[jietang @jietang]

GLM-5.2 is Fully Open, Frontier Intelligence Belongs to Everyone

Today, the sudden restriction of certain frontier models is deeply regrettable. At a time when access to frontier models is abruptly cut off for non-technical reasons, we are even more convinced of one thing: science should be global.

The path to AGI (Artificial General Intelligence) must never be enclosed by high walls. We have always believed that AGI should be the cornerstone for all of humanity to collaboratively explore the boundaries of intelligence and solve complex challenges, rather than a privilege monopolized by a few rules and subject to revocation at any moment. In the face of external blockades and restrictions, our attitude is one of radical openness. Frontier intelligence must remain open-source, accessible, and buildable, serving every dedicated developer.

GLM-5.2 is Zhipu's most capable open-source model to date. It not only supports a truly usable 1M context window but also maintains a continuous lead in the independent completion of long-horizon tasks, providing solid foundational support for building complex agent applications. It also continues to be our main engine for creating the strongest domestic coding model.

Tonight at 5:21—at this special moment—GLM-5.2 will officially be available to all GLM Coding Plan users (including Lite / Pro / Max). The API will also go live next week.

A step closer to frontier intelligence for everyone.
The future of AI is open, and it is for the people.
ModelKey: GLM-5.2

[cvxv666 @antpalkin]

The best trader who ever lived was right 50.75% of the time.

Save this talk. It's the man himself explaining why that was enough.

Jim Simons ran Medallion to 66% a year for 30 years, the greatest track record on record.

His iron rule: never override the system.

The moment your gut argues with the model mid-drawdown, you lose. He built a machine precisely so a human panicking at 3am couldn't touch it.

That panic is why 89% of retail finished 2025 red. Not the ideas. The hands on them.

Watch the whole thing. Then take the part you can use today: describe a strategy in plain English, and Horizon tests it, sets the rules, and runs it live so your gut never gets a vote.

Save the video. It's a masterclass you'll want again.

[Ridark @ridark_eth]

The 5-Minute Polymarket Sniper: Making $52,909 on "Boring" Bitcoin Fluctuations in a Week

Profile Statistics:

> Total Profit: $52,909.10
> The Biggest Win: $18.5K
> Total Forecasts: 32,904

The Strategy: 5-Minute Scalping

> Buying the Undervalued: He enters "Down" positions when the share price is heavily discounted, usually buying between 8¢ and 56¢. Essentially, he buys probabilities that the market is mispricing.

> Mathematical Edge: By repeating this across nearly 33,000 forecasts, he leverages the law of large numbers to turn small, cheap shares into a massive avalanche of profit.

> Zero Emotion: Pure execution of short-term momentum.

Top Deals from the Dashboard:

> March 26 (2:35 AM - 2:40 AM): Bought "Down" at 49.1¢ ➔ Won $36,318.08 (+$18,478.31 / +103.58%)

> March 20 (9:35 AM - 9:40 AM): The ultimate sniper shot. Bought "Down" at just 8.2¢ ➔ Won $15,011.27 (+$11,898.33 / +382.22%)

> March 24 (10:20 AM - 10:25 AM): Bought "Down" at 48.1¢ ➔ Won $22,178.75 (+$11,502.39 / +107.74%)

Why does this work?

On 5-minute charts, bots and retail traders constantly create inefficiencies in the order book by overreacting to minor BTC ticks. This trader simply spots the mispriced odds, locks in the best risk-to-reward ratio, and walks away with $8K to $18K in net profit in just 300 seconds.

[Farea @FareaNFts]

https://t.co/9POE4UDxIF

[Recogard @recogard]

I found 12 free GitHub repos for trading on Polymarket…

Here is everything you need to automate and make your trading easier:

1. The largest Polymarket dataset with over 36 GB of real trading data, based on more than 72 million trades, analyzed by a Coinbase developer.

GitHub: https://t.co/qkoF6TyjJQ

2. A backtesting simulator that lets you test your own trading ideas and strategies on real historical markets to see your potential win rate and all possible risks.

GitHub: https://t.co/fmzzTgXAUl

3. This bot automatically manages your limit orders on Polymarket to maximize liquidity rewards.

GitHub: https://t.co/nvb96dTIwx

4. This tool analyzes any Polymarket trader’s behaviour, finds repeated patterns in his trades, shows which strategies he uses and how you can adapt them to your own trading.

GitHub: https://t.co/SzdjHtASLt

5. A tool that lets you pull historical data for any market that has ever existed with detailed statistics and charts.

GitHub: https://t.co/5c5WwUVvVi

6. A bot with 118 ready to use tools and strategies for trading on Polymarket, including Binance-Polymarket latency, Momentum, Smart Routing, Penny Clipper, Expiry Fade, DCA bots and more.

GitHub: https://t.co/2MCzD8iZG7

7. An AI trading terminal that lets Claude connect to Polymarket, analyze markets in real time, track prices, suggest possible trades and even trade for you.

GitHub: https://t.co/5kFPrvOY3E

8. A bot that finds arbitrage opportunities between Polymarket and Kalshi.

GitHub: https://t.co/icWBTLTeVg

9. A weather bot that checks forecasts, airport data and aviation observations (like METAR + SPECI) to create a detailed weather report for a specific city and day.

GitHub: https://t.co/No3sBcqMg1

10. A trading dashboard where multiple AI agents analyze markets from different angles (news, price movement, technical indicators and possible risks) and suggest the best trading decisions.

GitHub: https://t.co/02iWujLbxe

11. A tool that analyzes what happened on the web over the last 30 days and finds useful patterns, connections and recent context around the selected topic. Very useful before trading.

GitHub: https://t.co/yETdyU8jT7

12. The largest public collection of 120 useful tools and services for prediction markets, including analytics dashboards, AI agents, trading bots, educational resources and more.

GitHub: https://t.co/jqvVR9106v

All of these repos come with a step by step setup and usage guides in English.

[Chris @everestchris6]

claude opus 4.8 + OpenClaw now finds restaurants with weak food photos, rebuilds their best dish into a cinematic reel, and mails the owner a postcard with the QR...on autopilot.

here's how agencies can land recurring contracts with this system:

- scans every restaurant in a city in real time
- pulls their real reviews, ratings, and reviewer-uploaded food photos
flags the weakest shot of their signature dish
- samples the brand color straight from the restaurant's own dish photo
rebuilds that exact plate into a cinematic 9:16 reel
- writes a printed postcard about their best dish
- mails it to the registered office, addressed to the owner, with a QR to the live reel

every step from the scrape to the reel to the mailbox is automated

reply "REEL" + RT and i'll send you a free guide so you can build this too (must be following so i can DM you)

[Harman @itsharmanjot]

A TEAM OF AI RESEARCHERS JUST OPEN-SOURCED THE BLOOMBERG TERMINAL FOR QUANT FINANCE.

A Bloomberg Terminal costs $25,000 per year per seat. Banks pay for thousands of them.

This thing reads every quant paper, every financial blog, every SEC filing, every arXiv preprint, and turns it into a searchable knowledge base. For free.

It's called QuantMind.

It just got accepted to the NeurIPS 2025 GenAI in Finance Workshop.

Here's what it actually does:

→ Ingests arXiv quant papers, financial news, blogs, and reports automatically
→ Parses PDFs, HTML, tables, and figures into structured knowledge
→ Tags every paper by research area and topic
→ Builds a semantic knowledge graph you can query in plain English
→ Plugs into DeepResearch, RAG, and MCP for multi-hop reasoning
→ Two-stage architecture: extract once, retrieve forever

Here's the wildest part:

The financial research industry publishes around 500 new papers and reports every single day.

Hedge funds pay six-figure salaries to junior analysts whose entire job is reading them.

QuantMind reads all of it. Tags it. Embeds it. Lets you ask it questions.

154 stars. 22 forks. 173 commits. MIT license. Python.

One honest note: this is a framework, not a magic alpha machine. You still need to know what to ask. But the "I haven't read that paper yet" excuse is officially dead.

The thing Wall Street charges $25,000 a year for is sitting on GitHub. Free.

Link in the comments.

[pearson @MPxbt]

THIS GUY CONNECTED CLAUDE TO TRADINGVIEW VIA AN OPEN-SOURCE MCP SERVER!

Not a Bloomberg terminal, just Claude Desktop next to a TradingView tab. Yet it's reading NQ E-mini charts live, switching timeframes, drawing ICT-style liquidity zones, and labeling higher-timeframe bias directly in the browser.

The server is on GitHub (1.7k stars): 30+ indicators, backtests for 6 strategies, multi-exchange support (Binance, KuCoin, Bybit), no API key.

What looks like a weekend build replaces a typical retail stack:

$200/month screeners, $50 indicator packs, and manual zone-drawing at 6am.

With one prompt, Claude installed the server, configured it, connected to TradingView, and began annotating live charts autonomously, internal liquidity, external targets, HTF bias.

No subscriptions. No screenshot copy-paste into ChatGPT.

AI-native trading infrastructure isn't coming. It's already a repo away.

[VALIX @RetroValix]

This guy built a trading bot with Claude and made $416,000 on Polymarket

His bot trades crypto Up/Down markets. It tracks real BTC/ETH/XRP price movements and enters positions when Polymarket prices lag behind the underlying asset

His strategy is simple:

> Uses limit orders
> Finds mispricings with his own probability model
> Buys the other side as a hedge

This guy’s Polymarket account:
https://t.co/TUBSyic1At

With this strategy, he generates consistent profit and keeps growing his deposit

[wluha @cryptowluha]

A veteran dev replaced a $210/month AI agent stack with a $1,198 Mac Mini setup.

Just 2 Mac Minis running Hermes locally.

Everything on-device:

memory, tools, workflows.

Most people keep paying monthly to repeat the same work.

This setup pays once and reuses forever.

$2,520/year vs $1,198 once.

The real shift isn’t chat.

It’s owning the workflow.

Most people will see this too late.

Follow @cryptowluha to learn more useful information

[Roan @RohOnChain]

i can't believe this man just gave away the exact math every Jane Street & Citadel quant secretly studied to get the job:

[Raunak Yadush @raunak_yadush]

You missed eCom in 2015
You missed TikTok in 2019
You missed Saas in 2022

Now don't miss AI Publishing in 2026.

It’s boring... but if you start today, you could make $3,000 by the end of June 2026.

I’ve spent 5+ hours breaking down:

• My AI prompts
• The exact AI workflow
• Niche research method

If you want the full breakdown, comment “Send” and I’ll send it over.

[vorty @vorty279]

Jane Street, Goldman Sachs, JP Morgan, BlackRock, Hudson River Trading, Two Sigma, D.E. Shaw

The most expensive engineering teams in the world released their financial tools on GitHub. Here are 7 repos, one from each

1. Jane Street, janestreet/magic-trace
https://t.co/rrnHcsd1fX
5.3k stars. Process tracer powered by Intel PT. When your profiler is blind, magic-trace sees every CPU instruction

2. Goldman Sachs, goldmansachs/gs-quant
https://t.co/sWGd66i4Ua
Derivative pricing the GS traders use at their desks. MIT licensed

3. JP Morgan, finos/perspective
https://t.co/9lxmtpZZK4
What JPM traders use to watch markets in real time. A $24k/year terminal, for free

4. BlackRock, blackrock/lcso
https://t.co/A6HqOL92dc
Rust optimizer for portfolio problems. Where scipy gives up, this works

5. Hudson River Trading, hudson-trading/corral https://t.co/2qwykYhkWj
Structured concurrency for C++20. The foundation of HFT infrastructure at one of the largest U.S. trading firms

6. Two Sigma, twosigma/flint
https://t.co/g42jxIH30f
Time-series joins on Apache Spark with temporal tolerance. Built for billions of ticks

7. D.E. Shaw, deshaw/pyflyby https://t.co/w8A7CjJcun
Auto-import for IPython and Jupyter. D.E. Shaw also funded the development of IPython itself

Bookmarked it

[0xMarioNawfal @RoundtableSpace]

18-YEAR-OLDS ARE MAKING $20K+/MONTH FROM AI CLIPPING

AND MOST PEOPLE STILL THINK THE OPPORTUNITY IS GONE

[kapsoul.x @KAPS0UL]

@Codie_Sanchez SMB

[Himanshu Kumar @codewithimanshu]

A Chinese student in Japan turned $0.90 into $408,292 on Polymarket in 2 days.

Almost nobody is watching.

His profile is Gravia. Been on Polymarket for 48 hours. Zero viewers.

He posted his terminal.

I reverse-engineered it and had Claude rebuild the same strategy.

One prompt. 20 minutes. Done.

This is not ordinary trading.

It's a Polymarket BTC UP/DOWN 5MIN scalper:

→ Pulls real-time BTC data from Binance WebSocket + 5M K-lines
→ Cross-references TradingView signals + CryptoQuant exchange flows
→ Uses Mirofish force-graph engine to map 100 nodes / 180 edges, detecting BEAR/BULL cluster convergence
→ Catches moments when Polymarket CLOB lags spot price by 0.3%+
→ Executes in under 100ms before contract repricing
→ In the UP/DOWN 5MIN market, 1,000+ orders per second
→ Grabs 0.3 to 0.8% per trade
→ Skips if no edge, low liquidity, signal conflicts, or daily cap hit

Risk controls are clean:

Per-trade risk: 0.5%
Daily cap: 2%
Hard stop: -0.4%
Runs on local terminal
No cloud dependency
No GPU needed

The edge is not predicting BTC.

It's exploiting the time gap between spot price, signal convergence, and CLOB repricing.

The real questions:

How far can this 5MIN high-frequency scalper scale?

Will Polymarket ban it?

You only need Claude + device + 1 hour per day.

Giving this free for 24 hours.

To get it:

1. Comment the word "Scalper"
2. Like and retweet this
3. Follow me @codewithimanshu so I can DM you

Save this post. Build the scalper this week. Start with $100. Scale on evidence.

[kapsoul.x @KAPS0UL]

@codewithimanshu SCALPER

[AIVersePlay @AIVersePlay]

ÇİNLİ BİR ADAM RESMEN PARA BASMA MAKİNESİ OLUŞTURDU.

Github'da 13.000 yıldız almış bir araç var.
Adı moneyprinterturbo.

Bir çinli geliştirici yaptı.

Ücretsiz ve tamamen açık kaynak.
Tiktok, reels, youtube shorts için tam videoları otomatik üretiyor.

Nasıl çalışıyor.
Tek bir iş akışında her şeyi hallediyor.
Senaryo üretimi, seslendirme, altyazı, görsel kaynaklar, düzenleme, hepsi dakikalar içinde.

Yayına hazır video çıkıyor.
Sen hiçbir şeye dokunmuyorsun.

Şimdi neden bu kadar popüler oldu.
Çünkü normalde bu süreç şöyle işliyor.

Senaryo için ayrı araç, seslendirme için ayrı araç, altyazı için ayrı araç, görsel için ayrı araç, düzenleme için ayrı araç.

Her biri ayrı para istiyor, ayrı zaman istiyor, ayrı öğrenme istiyor.
Moneyprinterturbo hepsini tek çatıda birleştirdi.
Ücretsiz, sınırsız ve kategorisindeki en popüler açık kaynak proje haline geldi.

Tiktok shop ve youtube shorts kanalları aylık 6 ila 10 bin dolar kazanıyor.
Bunlar bu süreci kullanıyor.

Fark şu:

Onlar araçlar için para ödüyor.
Sen ödemiyorsun.
Kurulumu 5 dakika.
Github'da ara.
Kur, çalıştır, içerik üret hepsi tamamen senin elinde.

[robert. @robrtcode]

Un nerd de 33 años acaba de convertir $1.000 en $946.207 operando Bitcoin, con un truco que robó de los pronósticos de huracanes.

Sin título en finanzas. Sin mesa de trading. Solo un truco que todo meteorólogo aplica y todo trader olvida.

Wallet pública:
https://t.co/J65WvxHpdC

El truco: los meteorólogos nunca pronostican el mañana con un solo modelo. Corren 31 y cuentan los votos. Él apuntó exactamente ese mismo truco hacia Bitcoin.

Un agente de Claude lee cada mercado de BTC de 5 minutos y lo mete en MiroFish, una simulación que corre 31 rutas de modelo y solo dispara cuando 28 de ellas coinciden. Por debajo de 26 votos, mata la operación.

La velocidad de cobertura del sistema de agentes es muchísimo mayor que la de cualquier equipo de trading de élite.

Recopilan datos 24/7 y corren simulaciones con esos datos en el motor de MiroFish, de forma completamente autónoma.

Cada operación es un ciclo perfecto. Cada dólar ganado es pura explotación de la ineficiencia del mercado.

Esa es toda la ventaja. No una predicción. Un quórum.

Dimensiona con Kelly y aprieta un botón. La mayoría de las señales nunca pasan la votación, así que la mayoría de los días se queda quieto.

Pasó años aprendiendo que la certeza es una estafa y el consenso es la ventaja.