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CLAUDE IS NOW CONTROLLING TRADINGVIEW FROM THE TERMINAL WRITING PINE SCRIPT AND SCANNING MARKETS LIVE

🚨 One photo of your face. That's all someone needs to become you on a live video call. In real time. Right now. The tool is free and open source. It's called Deep-Live-Cam. One image. One click. You become anyone on a live webcam feed. No training. No datasets. No waiting. Instant. Your face. Your expressions. Your mouth movements. All stolen from a single photo. Here's what this thing does: → Upload one photo of any face → Turn on your webcam → You are now that person. Live. In real time. → It matches your pose, your expressions, even your lighting → Mouth masking so the swapped face moves its lips when you talk → Multi-face mapping. Swap different faces on different people in the same call. → Virtual camera output. Plug it into Zoom, Google Meet, Teams. Nobody knows. → Works on NVIDIA, AMD, Intel, and Apple Silicon Here's the part that should terrify you: Your boss could be on a Zoom call with someone wearing your face right now. A scammer could call your parents looking exactly like you. A stranger could take your LinkedIn photo and become you in a video meeting. IShowSpeed's reaction when he saw it: "What the F**! This shit is crazy!" SomeOrdinaryGamers: "That's fucking freaky dude... that's so wild." This was the #1 trending repo on GitHub the day it launched. 1,600 stars in 24 hours. 80K+ stars today. No one is ready for what this means. And it's already out there. 100% Open Source.

5 free ready-to-use scripts for trading on Polymarket If you want to automate trading on Polymarket - here's everything you need to get started From data recording and wallet analysis to a trading bot and ML model 1. Trading terminal: hotkeys, instant orders, PnL and Telegram alerts - no more wallet confirmations every 5 seconds GitHub: github.com/txbabaxyz/poly… 2. Data recorder: logs Polymarket and Binance simultaneously — order book, trades, indicators, everything saved to files with a live dashboard GitHub: github.com/txbabaxyz/poly… 3. Trading bot: enters on the favorite ~4 minutes before market close with a stop-loss and position sizing based on a confidence formula GitHub: github.com/txbabaxyz/4coi… 4. Wallet analyzer: collects the full trade history of any wallet, splits by market and builds position accumulation charts GitHub: github.com/txbabaxyz/coll… 5. ML model: 208 indicators via TAAPI, predicts market direction and calculates fair value GitHub: github.com/txbabaxyz/mlmo… All tools are free - run them through Claude to build a full bot or use them separately

USE THIS PROMPT TO MAKE YOUR AI AGENT USE LESS TOKENS: “Implement a token efficiency and cost optimization system across all operations. Your objective is to minimize token usage without reducing output quality or capability. 1. TOKEN USAGE VISIBILITY Create a Token Usage Dashboard that tracks: •tokens used per task (responses, cron jobs, file loads) •tokens used per session (startup cost) •tokens used per model (daily breakdown, last 5 days) •tokens consumed by each .md file when loaded into context Store and update this in token_usage.md. 2. CONTEXT MAPPING Create a structured view of all context files: •directory tree of all .md files •size of each file •estimated token cost per file •when and why each file is loaded Store this in context_map.md. 3. CONTEXT OPTIMIZATION Audit all files and identify: •duplicated information •outdated or unused files •overly verbose content •files being loaded unnecessarily Then: •compress verbose content into shorter formats •merge redundant files •split large files into smaller, load-on-demand modules •remove unused or low-value context 4. SMART LOADING SYSTEM Do not load all context by default. Instead: •load only what is relevant to the current task •dynamically select files based on intent •avoid reloading the same context unnecessarily 5. RESPONSE EFFICIENCY Optimize outputs by: •avoiding unnecessary verbosity •eliminating repetition •using structured formatting instead of long explanations Be concise without losing clarity. 6. FILE DESIGN STANDARDS When creating or updating .md files: •compress information •remove fluff •prioritize high signal-to-token ratio Every file should justify its token cost. 7. PERIODIC AUDITS Create a cron job that runs 2x per week to: •audit token usage •detect inefficiencies or growth in usage •identify redundant or stale data •suggest optimizations Save results in token_audit.md. 8. OPTIMIZATION BEFORE EXECUTION Before making structural changes: •propose a clear optimization plan •explain expected token savings •wait for approval before applying changes RULES •Never sacrifice critical functionality for small token savings •Prioritize high-impact optimizations •Treat tokens as a limited resource that must be managed carefully Your role is to act as a token efficiency optimizer, continuously reducing cost while maintaining performance.” Credits: @PerSolana

@AlenaDaOG I own a machete 😉

if i Have to pick three groups of people to have on a team for the zombie apocalypse i would first choose the older hispanic grocery store produce stockers who just put fruit and vegetables all day they are great i trust them all with my life

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The Claude Code Danger Mode: How to Hit 1,347% Returns With an AI Backtest Architect most people are out here losing their life savings to the liquidation engine while i just found a way to let the machines do the heavy lifting for me. i am going to show you exactly how i hit a 1,347% return on solana data while the rest of the world was struggling to keep up with a 730% buy and hold. there is a hidden switch inside of modern ai tools that allows you to bypass the safety rails and step on the gas in a way that would terrify a traditional developer. i call it the danger mode and once you understand how to use it you can generate forty different backtests in the time it takes most people to drink a coffee. i believe that code is the great equalizer because through losing money with liquidations and over trading i knew i had to automate my trading. in the past i spent hundreds of thousands on devs for apps thinking i would not be able to code myself but i was wrong. w/ bots you must iterate to success so i decided to learn live on youtube and now we are here with fully automated systems trading for me instead of getting liquidated. the secret is not just having an ai write your code but turning that ai into a sub agent i call the backtest architect. most traders fail because they spend four hours on a single backtest and get so attached to the results that they ignore the red flags. i have built a system where i can launch three different architects at once and they all start building variations of rsi divergence and stochastic reversals simultaneously. if you want to achieve greatness you have to stop asking for permission to use the tools that are right in front of your face. i have been running forty backtests today and most of them were absolute trash but the few winners we found are enough to change everything. the reason wall street wins is because they have a massive head start on data and processing power but the gap is closing faster than they realize. when you can test a strategy across twenty five different data sources in minutes you are doing what used to require a whole floor of quants. the rbi system is my secret sauce which stands for research backtest and implement because it removes the emotion that kills every manual trader. i spend my time researching the ideas and then i let the architect build the folders and run the code to see if the math actually holds up. there is a specific trap in backtesting called over optimization where you make the code look perfect for the past but it blows up the second it hits live markets. i avoid this by using multi data testing which means we run the same strategy on everything from solana to nvidia to see if it actually works or if it was just a fluke. most people think you need to be a genius to do this but the reality is that you just need to be an idea guy with a bit of discipline. i spent a decade being scared of the terminal and now i have it running dangerously skip permissions because i want to go fast fast fast. the industry wants you to believe that you need their permission to win but the 777 energy i feel right now tells me otherwise. you can literally take a strategy like the three mountains or the elliot wave and tell your sub agent to layer it with bollinger bands and mfi to see the hidden alpha. i saw some returns on nvidia hourly that would make a hedge fund manager quit his job and join the community. the data dog in me just wants to chew on these numbers all day because the numbers do not lie and they do not have a bad day at the office. discipline is doing what you hate to do but doing it like you love it every single day even when the backtests come back negative. i ran seven macd strategies today and every single one of them was total garbage but i do not care because i just move to the next idea. the common mistake is thinking you can just buy a bot and it will print money forever without you ever having to look at it. this game is about constant iteration and if you are not willing to outshoot everyone else you are going to get left behind in the dust. it is a video game where the prize is your freedom and the boss fights are the liquidation events that try to take your soul. through code we can finally achieve the equality that the financial world has tried to keep for themselves for way too long. i document every single line of code because i want to turn my hours of work into no time for you to get started. once you see the systems working for you and the orders filling on the websocket you will never want to look at a manual chart ever again. the fully automated life is waiting for anyone who is brave enough to stop asking for permission and start coding their own future. stay hungry and keep building because the machines are ready to work for you if you just give them the right instructions

Want to host Claude meetups in your city? We'll cover the funding, send swag, and give you monthly API credits for your demos. You also get access to pre-release features and a private slack with the team! Go apply 💛

The next generation of traders won't have a bedtime. Aster is now agent-ready. Two integration paths, one API. 🔌 MCP Server: github.com/asterdex/aster… 🧠 Agent Skills: github.com/asterdex/aster…

America can’t afford to wait. Congress must move quickly to pass the Clarity Act. Let’s make the U.S. the digital asset capital of the world.

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I believe. $DOG

⚡️ TODAY: Bitget Wallet unveils beta Skill with OpenClaw, allowing users to access on-chain market data and trading via natural language.

you guys are sleeping on GitHub bots for Polymarket someone already did the work for you you just need to run it here are a few bots I personally tested but please DYOR before using - there's real risk of losing money first bot - github.com/echandsome/Pol… > two types of bots: copy trading and strategy bots with odds-based strategies second bot - github.com/ent0n29/polybot > microservice architecture - strategy, ingestor, analytics services + up/down arbitrage and more third bot - github.com/warproxxx/poly… > data pipeline for collecting markets, orders and trades from Polymarket. perfect for backtesting strategies want to automate - first two just need to test strategy - third one welcome if you've been wanting to get into bots

Renting Wall Street Power For $1/Hour: Use Cloud GPUs And Python To Automate Your Trading Edge no more paid courses needed because the actual secrets to building an edge are hidden in sight within the code you write yourself instead of some guru’s outdated pdf. most people think using ai in trading is just asking a chatbot where bitcoin is going next but they are looking at the wrong data entirely. my name is moon dev and i believe that code is the great equalizer because through losing money with liquidations and over trading i knew i had to automate my trading. in the past i spent hundreds of thousands on devs for apps thinking i would not be able to code myself but with bots you must iterate to success. i decided to learn live on youtube and now we are here with fully automated systems trading for me instead of getting liquidated. if you have ever felt that punch in the gut when a position gets wiped out you know why i am obsessed with removing the human heart from the execution. to actually win in this game you have to follow a process called the rbi system which stands for research backtest and implement. most beginners fail because they try to build a bot immediately without knowing if their strategy even has a statistical edge in the historical data. the r is for research where you look at academic papers on google scholar or listen to veteran quants on podcasts to find ideas that have worked for decades. once you have a basket of ideas you move to the b which is backtesting to see how that idea would have performed over the last few years. if the backtest shows you a profit only then do you move to the i for implementation with tiny size to see if it works in the live market. you are probably wondering why everyone else is looking at the same open high low close volume data while getting chopped up every single day. the real alpha is hidden in unique data specifically liquidation data because when traders get forced out of their positions it creates a massive vacuum that price often fills. everyone else is looking at what already happened while we are looking at the forced selling and buying that is about to drive the next move. this is where the machine learning comes in because we use something called an lstm or long short term memory neural network to find patterns in these sequences. lstms are specialized brains for numerical time series data which is why they are much better at predicting price moves than something like chatgpt. chatbots are great for writing code or chatting but they suck at predicting numbers because they were not built for time series data. a transformer model like the one inside cursor or claude looks at text context while our lstm looks at the relationship between liquidation spikes and five minute price targets. you might be tempted to run these models on your local computer but you will quickly realize that training on 17 million records can take 25 hours or more. i realized that as a trader i am making a trade of either dollars or time when i decide where to train my models. you can actually rent high end gpus in the cloud like an rtx 4090 or an a100 for less than a dollar an hour and get 20 hours of your life back. training a model 10 times faster than your home computer means you can iterate and find winning strategies while the rest of the world is still waiting for their progress bar. one of the biggest roadblocks you will hit is when your data has infinite values because some altcoin prices are so close to zero they break the math. we found nearly 8000 infinite targets in our data set which would have caused an infinite loss during training and crashed the entire model. instead of just deleting that data we implemented a capping strategy to keep the math sane while preserving the raw alpha of those small cap liquidations. we do not want to discriminate against small coins because a 100k liquidation on a tiny asset can still be a massive signal for the broader market. a massive shift happens when you realize you should look at all crypto liquidations but only predict the price of bitcoin specifically. by filtering 17 million records to just btc targets while keeping global market sentiment we create a much more powerful signal for the king of crypto. it is easy to feel defeated when the market is rigged against you but code allows you to remove the one thing that always fails which is your emotions. jim simons built a net worth of over 31 billion dollars because he realized there are patterns a robot can trade that a human can never see. the goal isn’t to find a magic bot that makes you a million dollars overnight because that is just a scam designed to drain your wallet. the goal is to build a swarm of small profitable systems that give you your time and your freedom back so you can be free as a bird. if you are tired of the red candle emails and the emotional rollercoaster the only way out is through automation and relentless testing of your ideas. just keep making your systems better and better every single day because that is exactly what the top 0.1 percent are doing right now.

I funded 20 ai agents and have them competing in a trading competition. The bottom 4 get 💀 and replaced next round. Survival of the fittest

I did the same thing, and woke up STUNNED. I only started with 10 AI agents, one of the 10 failed off rip, the rest have been going hard all night, almost $70k in profit the last 24hours each agent trades in their own style some close very quickly making less than $100 per trade, some have big balls and hold for $10k+ profit I am beyond thankful for @frankdegods for constantly shilling his Anthropic bags or I would have never been able to do this.