{"venture":"goodalgo-network","count":55,"signals":[{"tweet_id":"2008421662065066331","author":"willdepue","author_name":"will depue","text":"trillion dollar idea: sports bar but just for situation monitoring with live X feeds, flight radar, a bloomberg terminal, and Polymarket screens","created_at":"Tue Jan 06 06:13:33 +0000 2026","like_count":50962,"retweet_count":3011,"reply_count":1331,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network","groww-ca"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:11.519Z"},{"tweet_id":"2057562371879555242","author":"NFL_DovKleiman","author_name":"Dov Kleiman","text":"Still in beta, Polymarket already has best-in-class liquidity across virtually every category: pregame, futures, even in-play tennis. The depth is honestly absurd.\n\nDeposit $20, get free $50 with my code DOV50\n\nTry trading on tonight’s game 👇","created_at":"Thu May 21 20:41:11 +0000 2026","like_count":17843,"retweet_count":1059,"reply_count":533,"resolved_url":null,"resolved_type":null,"venture_tags":["anygame-dev","goodalgo-network"],"editorial_note":"Market data for anygame dev.","signal_type":"market","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:10.955Z"},{"tweet_id":"2008944502300659838","author":"unusual_whales","author_name":"unusual_whales","text":"🚨BREAKING🚨\n\nI just released the full report on Congress trading in 2025.\n\nLike every year since 2020, some politicians beat the market.\n\nMany had unusual trades.\n\nSome had huge gains.\n\nHere are the top political traders of 2025. https://t.co/p6NI4gNXIh","created_at":"Wed Jan 07 16:51:08 +0000 2026","like_count":16085,"retweet_count":5748,"reply_count":1389,"resolved_url":"https://twitter.com/unusual_whales/status/2008944502300659838/photo/1","resolved_type":"media","venture_tags":["goodalgo-network"],"editorial_note":"Market signal for goodalgo network.","signal_type":"trend","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:13.534Z"},{"tweet_id":"2064049389270958412","author":"afshineemrani","author_name":"Afshine Emrani  MD FACC","text":"I'm a cardiologist. I've held dying hearts in my hands in the cath lab at 3 AM. And I need to tell you something that changes everything about how we prevent heart attacks.\n\nFor decades, the entire field was built on one target: lower LDL cholesterol. Statins save lives — that's settled science. But too many of my patients did everything right — took their statins, hit their numbers, lived clean — and still ended up on my table with a ruptured artery.\n\nWe were treating the smoke while the fire kept burning.\nThe fire is inflammation. And the evidence is now overwhelming.\n\nThe CANTOS trial proved it first — lowering inflammation independent of cholesterol reduced cardiac events. But the newer data is what keeps me up at night.\n\nAI-enhanced CT angiography can now detect inflamed arteries by measuring changes in the fat surrounding your coronary vessels — the perivascular fat attenuation index. Higher inflammation in the fat around even one artery independently predicts cardiac death. When multiple arteries show inflammation, the risk multiplies dramatically — even in patients whose cholesterol looks perfect.\n\nThis isn't theoretical. This is measurable. Right now. On a scan you can get this month.\n\nLow-dose colchicine — a drug that's been around for centuries for gout — is now FDA-approved specifically for reducing cardiovascular events. It works by quieting the inflammatory cascade that destabilizes the plaque sitting in your arteries. A pill that costs pennies is saving lives the statins couldn't reach.\n\nAnd the next wave is already in Phase 3 trials. Ziltivekimab — an IL-6 inhibitor — targets the central inflammatory pathway driving atherosclerosis. Phase 2 data showed a 90% reduction in hsCRP. The ZEUS cardiovascular outcomes trial is enrolling now, with results expected late 2026 into 2027. If positive, anti-inflammatory therapy will become standard in managing heart disease alongside lipid-lowering. The era of inflammation-targeted cardiology is arriving.\nBut it goes deeper than drugs. AI is now predicting heart failure and cardiac events 5+ years before symptoms — integrating CT imaging, electronic health records, and genetic data with accuracy that jumps far beyond traditional risk calculators.\n\nAnd polygenic risk scores — a simple genetic test that flags inherited cardiovascular risk — are now formally recognized as a risk-enhancing factor in the 2026 ACC/AHA guidelines. A single blood draw can reveal risk that's been silently building since birth. Decades before the first chest pain.\n\nHere's what this means for you right now — today:\nAsk your doctor for a high-sensitivity CRP test. It's cheap, routine, and measures the systemic inflammation that standard cholesterol panels completely miss. You can have perfect LDL and inflamed arteries that are quietly preparing to rupture.\nIf your hsCRP is elevated, discuss low-dose colchicine with your physician. It's FDA-approved for exactly this.\nPush for a coronary CT angiography with AI plaque and inflammation analysis if you have risk factors. This isn't the stress test your parents got. This is 3D visualization of your actual arteries — with AI quantifying not just how much plaque you have, but what kind it is and whether the surrounding tissue is inflamed.\nConsider polygenic risk score testing — especially with a family history of early heart disease. It's now guideline-supported.\n\nAnd the foundation that never changes: move daily, eat real food, sleep 7-9 hours, manage stress, and know your numbers — ApoB, Lp(a), hsCRP, fasting insulin.\nI left Iran as a child with nothing. I rebuilt everything in a country that gave me the freedom to become a physician. I've spent twenty years watching patients get second chances.\n\nThe ones who haunt me aren't the ones who died on my table. They're the ones who survived but never acted on what the science was telling them — years before the event that didn't have to happen.\n\nYou can have perfect cholesterol and still have a heart attack. Inflammation plus genetics can drive plaque rupture in arteries that look \"fine\" on a standard panel.\nThe myth that normal cholesterol means you're safe has cost more lives than I can count.\n\nWe now have the tools to detect the fire — not just the smoke. AI to see it. Genetics to predict it. Drugs to quiet it. And the ancient basics — movement, real food, sleep, purpose — to prevent it from starting.\n\nPrevention is the new cure. And the science to make it real is no longer coming.\nIt's here.","created_at":"Mon Jun 08 18:18:17 +0000 2026","like_count":12036,"retweet_count":2071,"reply_count":469,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network","eventbuoy-com","fishboneny-com","onesqft-org","dochakki-com","chefaid-nyc","instasoiree-com","renascence-network"],"editorial_note":"Tool relevant to goodalgo network: could inform product or stack decisions.","signal_type":"tool","month_tag":"2026-06","ingested_at":"2026-07-01T01:51:47.655Z"},{"tweet_id":"2009003048044220622","author":"HipCityReg","author_name":"Reggie James","text":"Welcome to \"Situation Monitor\" \n\n&gt; Global Activity Monitor\n&gt; @tbpn livestream\n&gt; Intel Feed\n&gt; Tech/Finance/Politics newsfeed\n&gt; Stocks/Crypto\n&gt; @Polymarket  predictions\n&gt; Tech layoffs tracker\n&gt; AI Race news\n&gt; Is the Fed printer on?\n&gt; Venezuela + Greenland\n\nhttps://t.co/t7JmqN3z5c https://t.co/sC7kYqxs9d","created_at":"Wed Jan 07 20:43:46 +0000 2026","like_count":10215,"retweet_count":789,"reply_count":435,"resolved_url":"https://hipcityreg.github.io/situation-monitor/","resolved_type":"external","venture_tags":["goodalgo-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:13.597Z"},{"tweet_id":"2009090327978647994","author":"marlowxbt","author_name":"Marlow","text":"I built a C++ terminal to scan Polymarket for automated wallets. The first one it flagged was making $152K per week.\n\nAccount88888. 99% win rate. Over 11,000 trades. The script surfaced it in minutes.\n\nI spent three weeks writing a scanner that monitors wallet behavior across Polymarket. Entry patterns. Position sizing. Timing intervals.\n\n→ Wallet: https://t.co/YWQrgfmnpn\n\nThe goal was simple find accounts that trade too consistently to be human.\n\nThe first hit came back with stats that looked like a database error. 99% green. Thousands of executions. Profit curve pointing straight up without a single meaningful dip.\n\nI almost dismissed it as bad data. Then I opened the positions manually.\n\nThe bot buys UP and DOWN on the same BTC window. Every time. Not alternating. Simultaneously.\n\nSounds like guaranteed loss until you look at the pricing.\n\nDuring high volatility, Polymarket misprices both sides. UP costs 48 cents. DOWN costs 46 cents. Together that is 94 cents for two outcomes where one must pay a dollar.\n\nThe bot buys both. Waits fifteen minutes. Collects $1. Keeps 6 cents. Repeats.\n\nIt does not care about direction. Does not read charts. Does not react to news. It farms the spread between panic pricing and mathematical certainty.\n\nThe wallet used to be named JaneStreetIndia before switching to something generic. Smart money stays quiet.\n\nMy scanner keeps finding more of these. Different strategies but same signature execution patterns too clean and too fast for human hands.\n\nI built this tool expecting to learn how the best traders think.\n\nInstead I learned they do not think at all. They calculate.","created_at":"Thu Jan 08 02:30:35 +0000 2026","like_count":6796,"retweet_count":401,"reply_count":165,"resolved_url":"https://polymarket.com/@Account88888?via=marlowxbt","resolved_type":"external","venture_tags":["goodalgo-network","groww-ca"],"editorial_note":"Tool relevant to goodalgo network.","signal_type":"tool","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:09.785Z"},{"tweet_id":"2042247428930248939","author":"seelffff","author_name":"self.dll","text":"i cancelled $2,000/month in trading subscriptions\n\nreplaced every single one with open-source repos\nhere's the full stack:\n\n1. TradingView Pro ($30/mo) → lightweight-charts\n   14K stars. by TradingView themselves. 45KB. free\n https://t.co/Zj8BoF0kbj\n\n2. Bloomberg Terminal ($2,000/mo) → fredapi + Claude\n   every macro dataset the Fed publishes. free API\n https://t.co/QOsmACH9tB\n\n3. backtest platform ($100/mo) → prediction-market-backtesting\n   NautilusTrader fork with Polymarket + Kalshi adapters\n https://t.co/ezKB2PSBUq\n\n4. real-time dashboard → polyrec\n   terminal UI: Chainlink oracle, Binance feed, orderbook depth\n   70+ indicators. auto CSV logging. strategy backtester\n https://t.co/fYj5aFUTS4\n\n5. bot framework (7 strategies) → Polymarket-Trading-Bot\n   53K lines TypeScript. arbitrage, momentum, market making,\n   AI forecast, whale copy-trade, convergence\n https://t.co/xNSLjlIEZd\n\n6. strategy reverse engineering → polybot\n   execution + market data infrastructure. paper trading\n   Kafka, ClickHouse, Grafana. full analytics pipeline\n https://t.co/s3fjSwXV6z\n\n7. paper trading for AI agents → polymarket-paper-trader\n   real order books. exact fee model. slippage tracking\n   your Claude agent gets $10K paper money and trades\n https://t.co/oXMxD9uhKI\n\n8. token savings → rtk\n   CLI proxy. cuts Claude Code tokens by 60-90%\n   Rust. single binary. 10 AI tools supported\n https://t.co/WKnP7dfvuj\n\n9. Claude Code itself ($200/mo) → goose\n   35K stars. by Block (Jack Dorsey). Rust\n   works with any LLM. full agent loop. free\n https://t.co/md2P9CJ4Ia\n\n10. wallet tracking + copy trading → Kreo\n    track top Polymarket wallets. auto copy trades\n    the only tool on this list i actually pay for\n    because it makes more than it costs\n  https://t.co/rVKQ107tBV\n\ntotal before: ~$2,600/month\ntotal now: $0 + Kreo\n\nbookmark this. you'll need it","created_at":"Thu Apr 09 14:25:04 +0000 2026","like_count":6685,"retweet_count":899,"reply_count":176,"resolved_url":"https://github.com/tradingview/lightweight-charts","resolved_type":"github","venture_tags":["freeintelligence-ai","goodalgo-network","collectivewin-network","velab-stack"],"editorial_note":"Tool relevant to freeintelligence ai.","signal_type":"tool","month_tag":"2026-04","ingested_at":"2026-07-01T04:05:08.671Z"},{"tweet_id":"2064281585621610515","author":"bigaiguy","author_name":"Spencer Baggins","text":"A teenager in the United States started publishing software at 14 in 1998, built the entire online infrastructure for the Occupy Wall Street movement in 2011, joined Google as a software engineer, quit in 2018, and then spent five years writing a C library that does something the entire industry said was impossible.\n\nThen she combined it with llama.cpp and shipped the easiest way on the planet to run a large language model on any computer.\n\nHer name is Justine Tunney.\n\nHere is the story, because almost nobody outside the low level systems world knows what one engineer has built.\n\nJustine was born in 1984. She started writing and publishing software at 14, back when distribution meant uploading binaries to BBS systems and chat networks. She picked up the handle jart, which she still uses on GitHub today. She did the work most teenagers her age were not doing. She read the systems programming literature. She studied compilers. She fell in love with C.\n\nIn July 2011 she registered the @occupywallst Twitter handle and the occupywallst dot org domain. Within weeks the protest movement that began in Zuccotti Park in New York had become a global phenomenon, and her infrastructure was the digital backbone of the entire thing. She handled the social media, the website, the donations, the coordination. She built the platform that pushed the movement to reach millions.\n\nAfter Occupy she joined Google as a software engineer. She worked on TensorBoard, the visualization tool for TensorFlow, and on site reliability for Google infrastructure. She stayed for years. Then in 2018 she left Google Brain to work on a personal project.\n\nThe project was called Cosmopolitan Libc.\n\nCosmopolitan does something most C programmers would tell you is mathematically impossible. It lets you compile a C program once and have the resulting binary run natively on Linux, Windows, macOS, FreeBSD, OpenBSD, and NetBSD with no modification. One file. Six operating systems. No virtual machines. No interpreters. No recompilation. The technique she invented is called Actually Portable Executable.\n\nThe implications are wild. Cosmopolitan binaries violate every assumption about how operating systems load programs. They are at once a Windows PE file, a Linux ELF binary, a macOS Mach-O binary, and a shell script. The same bytes run on every platform.\n\nFor five years she worked on it mostly alone. She funded the development partly through Mozilla's MIECO program, which sponsored her work on Cosmopolitan 3.0, released on October 31, 2023.\n\nA month later she shipped llamafile.\n\nllamafile is what happens when you combine Cosmopolitan with llama.cpp. You take any LLM weights file in the standard GGUF format, you wrap it in Justine's binary, and you get a single file that runs on six operating systems without installation. No Python. No CUDA setup. No dependency hell. Just one file that you double click and it works.\n\nMozilla launched it as an official project of their innovation group on November 29, 2023. It went viral immediately. The repository, hosted at github .com/mozilla-ai/llamafile, now has 24,600 stars. The license is Apache 2.0.\n\nJustine kept shipping. She added GPU support to Cosmopolitan, a task systems engineers thought would require rewriting the whole thing. She added dlopen support, another thing nobody else had figured out. She wrote whisperfile, a single file version of OpenAI's Whisper speech-to-text model based on the same architecture.\n\nHer GitHub profile lists projects most engineers would consider impossible. sectorlisp, a Lisp interpreter that fits in a boot sector. blink, the tiniest x86-64-linux emulator on Earth. bestline, a teletypewriter command session library. redbean, a complete web server inside a single zip file.\n\nA teenager who shipped software in 1998 grew up to write the C library that the entire local AI movement now runs on top of.\n\nShe did most of it alone, and most people scrolling AI Twitter cannot name her.","created_at":"Tue Jun 09 09:40:57 +0000 2026","like_count":5807,"retweet_count":842,"reply_count":129,"resolved_url":null,"resolved_type":null,"venture_tags":["freeintelligence-ai","goodalgo-network","a3r-network"],"editorial_note":"Tool relevant to freeintelligence ai: could inform product or stack decisions.","signal_type":"tool","month_tag":"2026-06","ingested_at":"2026-07-01T01:51:47.598Z"},{"tweet_id":"2015251253681361009","author":"marlowxbt","author_name":"Marlow","text":"Someone on Reddit asked why they can't make money on Polymarket. The top comment had one word: distinct-baguette.\n\nNo explanation. No link. Just a username. 47 upvotes. Thread deleted 2 hours later.\n\nI searched. Found the wallet. $441,263 profit. 26,293 trades. Joined October 2025.\n\n→ Account: https://t.co/Zc9nyM2PDP\n\n66% win rate. Looked weak at first. Then I saw the profit curve. Straight line to the sky. No dips. No drawdowns. Just green.\n\nSpent three days going through the positions. One trade made me stop scrolling.\n\nDecember 16. BTC 15 minute window. Entry at 3 cents. Payout: $11,816. Return: 2,663%.\n\nI went back to Reddit. Found an archived thread from a throwaway account. Someone explained what wallets like this actually do.\n\nHere is the trick that broke my brain.\n\nYES and NO should always cost $1 together. Basic math. But when news hits or panic spreads, the market forgets how to count.\n\nYES drops to 48 cents. NO sits at 49 cents. Total: 97 cents for two outcomes where one MUST pay a dollar.\n\nBuy both. Wait 15 minutes. Collect $1. Keep 3 cents. Repeat.\n\nThree cents is nothing. Until you do it 26,000 times.\n\nNo predictions. No charts. No opinions on BTC direction. Just collecting money every time fear makes prices slip.\n\nThe Reddit thread had one last comment before deletion:\n\nStop asking how. Start asking who. Then watch what they do.\n\n122,000 people now watch this wallet. Four months ago it had zero.\n\nThe math error still exists. The wallet still prints. The crowd still panics and sells both sides too cheap.\n\nSome people read Reddit threads. Others become the thread.\n\nWhich one are you?","created_at":"Sun Jan 25 02:31:55 +0000 2026","like_count":5620,"retweet_count":248,"reply_count":82,"resolved_url":"https://polymarket.com/@distinct-baguette?via=marlowxbt","resolved_type":"external","venture_tags":["goodalgo-network","groww-ca"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:07.830Z"},{"tweet_id":"2014358386389700905","author":"xmayeth","author_name":"may.crypto {🦅}","text":"Here’s the Tutorial of how to build your Arbitrage Bot for Polymarket \n\n$900 per day exact Formula.\n\nFeel free to bookmark while it’s public.","created_at":"Thu Jan 22 15:23:58 +0000 2026","like_count":3740,"retweet_count":193,"reply_count":139,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Educational resource for goodalgo network.","signal_type":"education","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:10.287Z"},{"tweet_id":"2015850159310078324","author":"polydao","author_name":"Mr. Buzzoni","text":"🚨 UNEXPECTED USE CASE FOR CLAWDBOT ON POLYMARKET\n\nsomeone plugged @openclaw into @Polymarket with $100 and let it trade 15-min BTC up/down markets overnight and woke up with ~$347\n\nquick takeaway:\n> trades fully automated\n> scans X sentiment + news flow\n> reacts to volatility in real time\n> compounds small wins fast\n> logs and reviews every decision\n\nif this is even half repeatable, automation is a real edge here\n\n- definitely going to try ClawdBot myself and see how it behaves in live markets","created_at":"Mon Jan 26 18:11:45 +0000 2026","like_count":2976,"retweet_count":196,"reply_count":106,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:04.991Z"},{"tweet_id":"2008921337071616441","author":"ankitkr0","author_name":"Ankit","text":"Shipped a new thing: Polymarket Times 🗞️\n\nA newspaper powered entirely by real-time prediction odds on @Polymarket. \n\nA front page where the headlines are dictated by global markets, not editorial boards. \n\nThe future is finally priced in 🫡 https://t.co/DlKyE1FQvv","created_at":"Wed Jan 07 15:19:05 +0000 2026","like_count":2870,"retweet_count":172,"reply_count":304,"resolved_url":"https://twitter.com/ankitkr0/status/2008921337071616441/video/1","resolved_type":"media","venture_tags":["goodalgo-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:13.486Z"},{"tweet_id":"2061108656754851868","author":"itsharmanjot","author_name":"Harman","text":"10 GitHub repos so good they shouldn't be free.\n\n1. AutoHedge\n\nAn autonomous hedge fund built in Python with four AI agents: a director generates investment theses, a quant validates them, a risk manager decides position size, and an execution agent places orders. Operates live on Solana. With 'pip install -U autohedge', you can start trading immediately.\nrepo → https://t.co/q22EzesLoD\n\n2. Vibe-Trading\n\nA trading system using a Directed Acyclic Graph (DAG) model, featuring 64 finance skills and 29 preset specialist agent swarms. Includes analysis methods like Ichimoku, Elliott Wave, SMC, Black-Scholes, full Greeks, and risk parity. Its crypto desk provides liquidation heatmaps and token unlock tracking. You can observe agents debating strategies in real time.\nrepo → https://t.co/LZ5CYGMC1W\n\n3. Fincept Terminal\n\nA Bloomberg Terminal replacement that runs on your laptop. CFA levels 1, 2, and 3 analytics. 20+ investor AI agents (Buffett, Dalio, Soros). 100+ data connectors, including Polygon, World Bank, and IMF. Bloomberg charges $24,000 a year. This is free.\nrepo → https://t.co/dMM1WZxrw9\n\n4. LibreChat\n\nEvery model ChatGPT runs, plus Claude, Gemini, DeepSeek, and 20 more. Self-hosted. Native MCP support. You own the data, the history, the infrastructure. OpenAI charges $20/month to use their wrapper. This costs nothing to use your own.\nrepo → https://t.co/457utdZUIF\n\n5. Open Higgsfield AI\n\nA self-hosted cinema studio with 200+ AI models. Flux, Midjourney, Sora, Kling, Veo, GPT-4o, SDXL all in one interface. Text to image. Image to video. Cinema mode with pro camera controls. No subscription. Your data stays local.\nrepo → https://t.co/WHCzBSFBW4\n\n6. Open-LLM-VTuber\n\nA Live2D AI companion that runs offline, sees your screen, hears your voice, and never forgets. Inner thoughts are shown as a separate text layer, so you watch the reasoning happen before words come out. Pet mode floats it on your desktop. Swap the LLM in one config line.\nrepo → https://t.co/5XVKUPr35X\n\n7. Claude Ads\n\nA free Claude Code skill that runs 190 audit checks across Google, Meta, YouTube, LinkedIn, TikTok, and Microsoft Ads. 6 parallel subagents firing at once. Consolidates into a single Ads Health Score ranked by revenue impact. Agencies charge $4,000 a month for this.\nrepo → https://t.co/AJRfpSB7B6\n\n8. Agentic Inbox\n\nCloudflare just open-sourced an email client where an AI agent reads your inbox and drafts your replies. Runs entirely on Cloudflare Workers. Each mailbox lives in its own Durable Object. Your email never leaves your Cloudflare account. One click deploys it.\nrepo → https://t.co/QEEMtzoliV\n\n9. Camofox Browser\n\nAn open source headless browser that makes AI agents invisible to bot detection. Spoofs navigator properties, WebGL, AudioContext, and WebRTC at the C++ level. The browser does not look modified because it genuinely is not. Accessibility tree output drops token cost by 90%.\nrepo → https://t.co/95d0V3o7vO\n\n10. Hyperframes\n\nHeyGen open-sourced a video framework that does everything Remotion does without React, without JSX, without teaching your AI agent a new format. The agent writes HTML. The framework renders MP4. GSAP, Lottie, and Three.js all work. Same HTML always produces the same file.\nrepo → https://t.co/ekquvYvTNC\n\nThese are not toys. Each one replaces a paid product you're still being charged for.\n\nPick one. Install it. Plug it into your workflow.\n\n100% free. 100% open source.","created_at":"Sun May 31 15:32:51 +0000 2026","like_count":2653,"retweet_count":434,"reply_count":47,"resolved_url":"https://github.com/The-Swarm-Corporation/AutoHedge","resolved_type":"github","venture_tags":["miny-network","freeintelligence-ai","goodalgo-network","velab-org","collectivewin-network","velab-stack"],"editorial_note":"Tool relevant to miny network.","signal_type":"tool","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:08.203Z"},{"tweet_id":"2061870611115188297","author":"Fluyeporlaweb","author_name":"PA13L0","text":"10 repositorios de GitHub tan buenos que no deberían ser gratuitos.\n\n1. TradingAgents\n\nUn equipo completo de analistas de IA que debate estrategias y ejecuta operaciones en mercados reales. 4 analistas en paralelo: fundamentales, sentimiento, noticias y técnico. Luego un gestor de riesgos y un agente ejecutor. Como tener un equipo de Wall Street que trabaja 24 horas en tu ordenador.\nrepo - https://t.co/meb8dlqGwB\n\n2. LibreChat\n\nChatGPT, Claude, Gemini, DeepSeek y 20 modelos más en una sola interfaz. Autoalojado. Soporte nativo para MCP. Tu historial, tu infraestructura, tus datos. OpenAI cobra $20 al mes por su interfaz. Aquí usas tus propias claves y no pagas nada de más.\nrepo - https://t.co/Uj9Cy3Lbc9\n\n3. HyperFrames\n\nHeyGen abrió el código de su motor de video interno. Escribes HTML. El agente renderiza MP4. Sin React, sin JSX, sin formatos propietarios. GSAP, Lottie y Three.js funcionan de serie. El mismo HTML siempre produce el mismo archivo. Usado en producción por HeyGen, tldraw y TanStack.\nrepo - https://t.co/EeLlpqK5L2\n\n4. Fincept Terminal\n\nUna terminal Bloomberg que corre en tu laptop. Análisis nivel CFA 1, 2 y 3. Más de 20 agentes de IA inversores que razonan como Buffett, Dalio y Soros. Más de 100 conectores de datos. Bloomberg cobra $24.000 al año. Esto no cuesta nada.\nrepo - https://t.co/qCQkBgEzLS\n\n5. MoneyPrinterTurbo\n\nMetes una palabra clave. Salen el guion, las imágenes, los subtítulos, la música y el video final en alta calidad. Horizontal o vertical. Sin editar nada a mano. Lo que hacen los creadores de contenido que no quieren que sepas que usan IA.\nrepo - https://t.co/RtCmSYCQQw\n\n6. Agentic Inbox\n\nCloudflare acaba de abrir el código de un cliente de email donde un agente de IA lee tu bandeja de entrada y redacta las respuestas. 100% en Cloudflare Workers. Tu email no sale de tu cuenta. Sin servidores externos. Sin suscripción.\nrepo - https://t.co/mGsN8spCOX\n\n7. VoxCPM2\n\nClonas cualquier voz con 3 segundos de audio. 30 idiomas. Calidad estudio de 48kHz. Diseñas voces desde texto: \"voz masculina grave de locutor de radio\". Sin API de pago. Sin que tus muestras de voz salgan de tu máquina. ElevenLabs cobra $22 al mes.\nrepo - https://t.co/ctUrA0d1K9\n\n8. Flowsint\n\nIntroduces un dominio. La herramienta despliega un grafo con todas las IPs, subdominios, emails, wallets cripto y perfiles sociales conectados. Todo almacenado en local. Sin que nadie sepa lo que estás investigando. Para OSINT, due diligence y análisis de competencia.\nrepo - https://t.co/GTrSEJqSsT\n\n9. addyosmani/agent-skills\n\nEl ingeniero de Google que lleva 15 años enseñando rendimiento web a toda la industria publicó sus skills para Claude Code. 23 flujos de trabajo reales probados en producción. API design, code review, debugging, CI/CD y frontend. Instalación con un comando.\nrepo - https://t.co/ByOJtJlQX3\n\n10. Nango\n\nLa capa de integraciones que las empresas pagan $50k al año por alquilar. 700 APIs listas: Salesforce, HubSpot, Slack, Gmail, Stripe, Jira y más. OAuth gestionado. Tu agente de IA genera el código de integración desde un prompt. Usado en producción por Replit, Ramp y Mercor.\nrepo - https://t.co/i5XmU3GzJK\n\nEstos no son juguetes. Cada uno reemplaza un producto de pago por el que todavía te están cobrando.\n\nElige uno. Instálalo. Conéctalo a tu flujo de trabajo.\n\n100% gratis. 100% open source.","created_at":"Tue Jun 02 18:00:36 +0000 2026","like_count":2334,"retweet_count":496,"reply_count":21,"resolved_url":"https://github.com/TauricResearch/TradingAgents","resolved_type":"github","venture_tags":["miny-network","freeintelligence-ai","goodalgo-network","velab-org","velab-stack"],"editorial_note":"Tool relevant to miny network: could inform product or stack decisions.","signal_type":"tool","month_tag":"2026-06","ingested_at":"2026-07-01T01:51:49.032Z"},{"tweet_id":"2059231280269541772","author":"DamiDefi","author_name":"Dami-Defi","text":"Claude Code cannot read 300 files at once.\n\nSo someone built a system that lets it control NotebookLM from the terminal instead. The results are wild.\n\nHere is the full workflow nobody is talking about:\n\nThe Setup\n→ Claude Code connects to NotebookLM via a command line interface\n→ Claude searches YouTube, finds relevant videos, uploads them as sources automatically\n→ NotebookLM processes up to 300 sources simultaneously and returns cited, grounded answers\n→ Everything syncs back into your Obsidian vault with passage-level citations you can click to verify\n\nWhy This Changes Research Forever\n→ No more 20 browser tabs you never close\n→ No more copy-pasting outputs into random notes\n→ No more hallucinated answers with no sources to back them up\n→ 60% of citations verified as strong matches in accuracy audits - answers are grounded in real data\n\nWhat Claude Can Do From the Terminal\n→ Search YouTube for relevant videos on any topic and rank by relevance\n→ Create a new NotebookLM notebook and add 20 sources in parallel automatically\n→ Ask questions and export cited answers directly into Obsidian with wikilinks\n→ Set custom personas per notebook - concise, no filler, no preamble\n→ Generate audio overviews and save them as MP3 files into your vault\n→ Build mind maps, flashcard decks, and research dashboards from your sources\n→ Search arXiv for academic papers and feed them directly into NotebookLM\n→ Upload competitor blog posts, podcast episodes, PDFs, and your own vault notes\n\nThe Obsidian Output\n→ Every answer arrives with clickable citations that link to the exact passage in the source video or article\n→ Graph view shows connections between all 20 sources and the topics they share\n→ Q&A log tracks every question asked and the grounded response received\n→ Source dashboard shows citation frequency, topics extracted, and which questions each source answered\n\nUse Cases Worth Building Today\n→ Academic research with arXiv papers, full citation traceability\n→ Competitor analysis from their YouTube channels and blog posts\n→ Company knowledge base for onboarding, new employees ask NotebookLM instead of interrupting teammates\n→ Podcast research, feed 4-hour Lex Fridman episodes and ask what's new in AI this week\n→ Personal second brain, 300 daily notes uploaded and queryable in one notebook\n\nBefore this system existed you needed 20 tabs, hours of manual reading, and no guarantee the answers were real.\n\nNow you type one prompt in the terminal and Claude does all of it for you.\n\nThe research stack of 2026 is not a browser. It is a terminal connected to everything","created_at":"Tue May 26 11:12:50 +0000 2026","like_count":1554,"retweet_count":176,"reply_count":57,"resolved_url":null,"resolved_type":null,"venture_tags":["freeintelligence-ai","goodalgo-network","onesqft-org","velab-stack"],"editorial_note":"Tool relevant to freeintelligence ai.","signal_type":"tool","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:13.008Z"},{"tweet_id":"2017255598258094534","author":"xmayeth","author_name":"may.crypto {🦅}","text":"ClawdBot Assistant Prints $56,236 in a Week on Polymarket \n\nRecently I shared a simple guide on how to set up automation.\n\nResults are already here.\n\nSomeone tested it for a week and made 2,590 predictions with $71,087 in total PNL.\n\nHis profile: https://t.co/349hX1xbai\n\nClawdBot auto-trades BTC/ETH/XRP/SOL markets and spot CEX’s inefficiencies.\n\nHere’s the example of trade:\n> “Bitcoin Up or Down January 24, 8:15-8:30AM ET\"\n+$24,375 (+138%) from spotting Binance delay.\n\nEverything I shared is already enough to build a bot that will make you profitable in 2026.\n\nYou either automate your trading or just copytrade another smart wallets with the right tools like: \nhttps://t.co/Z48Gf3QAMQ\n\nManual trading is becoming the exit liquidity.\n\nSave the guide, you’ll thank me later.","created_at":"Fri Jan 30 15:16:28 +0000 2026","like_count":1348,"retweet_count":93,"reply_count":64,"resolved_url":"https://polymarket.com/@0xE594336603F4fB5d3ba4125a67021ab3B4347052-1769022918519?via=maycrypto","resolved_type":"external","venture_tags":["goodalgo-network"],"editorial_note":"Tool relevant to goodalgo network.","signal_type":"tool","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:02.664Z"},{"tweet_id":"2010373356302827604","author":"xmayeth","author_name":"may.crypto {🦅}","text":"How a Simple Formula Prints $100,000/Month on Prediction Markets\n\nThis is the cleanest explanation of prediction-market arbitrage you will ever read.\n\nBookmark this.","created_at":"Sun Jan 11 15:28:53 +0000 2026","like_count":1202,"retweet_count":86,"reply_count":49,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:07.763Z"},{"tweet_id":"2066563400583241756","author":"ludoonchart","author_name":"ludoonchart","text":"Nassim Taleb built his fortune by realizing that to survive wall street, you must be perfectly comfortable looking like an absolute idiot\n\nspeaking to microsoft's top engineers, he shared the exact math from 1987 that built his empire:\n\n\"it started with the crash in 1987. i realized that if you position for a massive 20-sigma event, your portfolio is so mathematically convex that you could literally wait 400 years for it to happen again, and you would still be okay\"\n\n\"so i told myself i will only specialize in extreme events. you sit there and wait 3, 4, 5 years. everybody on the trading floor tells you you're an idiot. they tell you you're not profitable\"\n\n\"and then suddenly the crash happens. the crowd blows up, they completely disappear, and you take absolutely everything\"\n\nwatch his full 1-hour microsoft masterclass on the math of extreme risk","created_at":"Mon Jun 15 16:48:04 +0000 2026","like_count":1138,"retweet_count":124,"reply_count":9,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network","eventbuoy-com","fishboneny-com","instasoiree-com","renascence-network"],"editorial_note":"Strategic/philosophical lens applicable to goodalgo network.","signal_type":"philosophy","month_tag":"2026-06","ingested_at":"2026-07-01T01:51:47.014Z"},{"tweet_id":"2023462184303685907","author":"Jesterthegoose","author_name":"JesterTheGoose","text":"FINALLY! Public API Access for Polymarket US. Hopefully this will make the books much deeper.","created_at":"Mon Feb 16 18:19:13 +0000 2026","like_count":929,"retweet_count":45,"reply_count":20,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-02","ingested_at":"2026-07-01T04:05:03.748Z"},{"tweet_id":"2014429615155269886","author":"0xMovez","author_name":"Movez","text":"Vibe-coded AI bot made $64K just by trading weather on Polymarket.\n\nIt turned $197 → $7,342 on London temperature by using the right algo.\n\nThe bot scans weather markets for under-priced odds <10¢ and compares them to data from Tomorrowio API.\n\nFull logic of such bot: \n\n1) Scan weather market on Polymarket \n\n• odds range 0.1¢ - 10¢\n• liquidity ≥ 50$\n• parse cities: London, New York, Seoul\n\n2) Get weather forecast\n\n• сall Tomorrowio API based on city\n• calculate high, low, and avg. temperatures\n• calculates probability with deviation ±3.5°F\n\n3) Compare \"market price\" vs \"fair price\"\n\n• anlyse current \"YES\" odd on Polymarket \n• calculates edge: ( fair price - market price / market price ) \n• If deviation % is higher than expected, \"buy it\"\n\nHis stats: \n\n• 1922 predictions \n• $7,145 bigest win on weather \n• 3616% bigest ROI \n\nAnother example of a great mix of IT engineer / meteorologist in the right category to automate on Polymarket.","created_at":"Thu Jan 22 20:07:01 +0000 2026","like_count":918,"retweet_count":42,"reply_count":43,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:10.441Z"},{"tweet_id":"2011775098395771101","author":"kalashvasaniya","author_name":"Kalash","text":"Prompt::\n\nAudit and refactor the entire codebase as a senior full-stack engineer and SEO architect with the explicit goal of safely scaling to 100,000+ programmatic SEO pages. Design a programmatic SEO system built on structured data that enables scalable page templates, dynamic routing, and unique intent-matched content per page, including titles, headings, descriptions, and FAQs, while avoiding thin content, duplication, and keyword cannibalization. Implement advanced SEO foundations such as fully dynamic metadata (title, description, canonical, Open Graph, Twitter), appropriate schema markup (Article, FAQ, Breadcrumb, Product, or context-specific types), and intelligent internal linking using hub-and-spoke structures, related pages, and breadcrumbs. Optimize the application for performance and scalability by prioritizing Core Web Vitals, leveraging static generation or incremental regeneration where possible, minimizing bundle size, and ensuring fast builds and effective caching even at very large page counts. Refactor the codebase for clarity, modularity, and long-term maintainability by introducing clean abstractions for SEO logic, data fetching, and page templates, with safeguards and conventions that allow future pages to be added at scale without regressions.\n\nUse Claude opus 4.5 MAX","created_at":"Thu Jan 15 12:18:55 +0000 2026","like_count":854,"retweet_count":60,"reply_count":35,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market signal for goodalgo network.","signal_type":"trend","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:09.887Z"},{"tweet_id":"2060439280212931032","author":"RohOnChain","author_name":"Roan","text":"I can't believe people do not know you can build hedge fund level trading strategies using AI completely from scratch.\n\nThis paper shows exactly how top quants combine AI with real market data to build strategies that actually prints. Bookmark this before someone takes it down. https://t.co/BvOn9RC2bz","created_at":"Fri May 29 19:13:00 +0000 2026","like_count":674,"retweet_count":98,"reply_count":27,"resolved_url":"https://twitter.com/RohOnChain/status/2060439280212931032/photo/1","resolved_type":"media","venture_tags":["goodalgo-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:03.546Z"},{"tweet_id":"2064792346747613499","author":"recogard","author_name":"Recogard","text":"I found 12 free GitHub repos for trading on Polymarket… \n\nHere is everything you need to automate and make your trading easier:\n\n1. The largest Polymarket dataset with over 36 GB of real trading data, based on more than 72 million trades, analyzed by a Coinbase developer.\n\nGitHub: https://t.co/qkoF6TyjJQ\n\n2. 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. \n\nGitHub: https://t.co/fmzzTgXAUl\n\n3. This bot automatically manages your limit orders on Polymarket to maximize liquidity rewards.\n\nGitHub: https://t.co/nvb96dTIwx\n\n4. 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.\n\nGitHub: https://t.co/SzdjHtASLt\n\n5. A tool that lets you pull historical data for any market that has ever existed with detailed statistics and charts.\n\nGitHub: https://t.co/5c5WwUVvVi\n\n6. 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.\n\nGitHub: https://t.co/2MCzD8iZG7\n\n7. 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. \n\nGitHub: https://t.co/5kFPrvOY3E\n\n8. A bot that finds arbitrage opportunities between Polymarket and Kalshi. \n\nGitHub: https://t.co/icWBTLTeVg\n\n9. 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.\n\nGitHub: https://t.co/No3sBcqMg1\n\n10. 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. \n\nGitHub: https://t.co/02iWujLbxe\n\n11. 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.\n\nGitHub: https://t.co/yETdyU8jT7\n\n12. The largest public collection of 120 useful tools and services for prediction markets, including analytics dashboards, AI agents, trading bots, educational resources and more.\n\nGitHub: https://t.co/jqvVR9106v\n\nAll of these repos come with a step by step setup and usage guides in English.","created_at":"Wed Jun 10 19:30:32 +0000 2026","like_count":501,"retweet_count":112,"reply_count":26,"resolved_url":"https://github.com/Jon-Becker/prediction-market-analysis","resolved_type":"github","venture_tags":["goodalgo-network","collectivewin-network"],"editorial_note":"Tool relevant to goodalgo network: could inform product or stack decisions.","signal_type":"tool","month_tag":"2026-06","ingested_at":"2026-07-01T01:51:47.398Z"},{"tweet_id":"2017137431531893012","author":"browser_use","author_name":"Browser Use","text":"Moltbot can now use Browser Use Skills!\nHere's Moltbot predicting the future with Polymarket and Kalshi skills 🔮\n\nBrowser Use Skills reverse engineer APIs to turn 30s browser workflows into 2s tool calls. \nWe gave Moltbot:\n> Access to the Browser Use Skill Marketplace\n> Skill cloning and execution\n\nTry it now!","created_at":"Fri Jan 30 07:26:54 +0000 2026","like_count":429,"retweet_count":37,"reply_count":14,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Tool relevant to goodalgo network.","signal_type":"tool","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:02.608Z"},{"tweet_id":"2009080369568731481","author":"zarazhangrui","author_name":"Zara Zhang","text":"# Acquired Podcast To Book Prompt\n\n**Your Role & Mission**\n\nYou are my executive assistant helping me transform a long Acquired podcast episode into a compelling written chapter for a physical book I'm creating. Think of yourself as a skilled ghostwriter who listens to the entire episode and crafts it into something that reads like a chapter from a classic business biography.\n\n**Style & Voice**\n\nWrite like a chapter from a great business biography--think _Shoe Dog_, _The Everything Store_, or _Hatching Twitter_. This means:\n\n- Rich narrative with dramatic tension\n- Key turning points treated as pivotal scenes\n- Quotes woven in to let the protagonists speak for themselves\n- The reader should feel like they're watching history unfold, not reading a summary\n- Analytical insight layered into the storytelling, not separated from it\n\n**Length**\n\nAs long as the story warrants. Use your judgment based on the episode's length and insight density. Quality and completeness over brevity. This is meant to be a satisfying read, not a skim.\n\n**Step 1: Understand the Arc**\n\nListen to/read the full episode and identify:\n\n- The central narrative: What is the story being told? What's the dramatic question?\n- The key characters: Who are the protagonists, antagonists, and supporting players?\n- The turning points: What are the 3-5 moments where everything changed?\n- The stakes: What was at risk? What could have gone wrong?\n\nGreat business stories have narrative shape--a beginning that sets the stage, rising tension, pivotal decisions, and resolution (or ongoing cliffhanger). Find that shape.\n\n**Step 2: Map the Characters**\n\nAcquired episodes often feature many players, which can be disorienting. Solve this for the reader by:\n\n- Introducing each character clearly on first appearance with a brief identifying detail (role, relationship to the central figure, why they matter)\n- Re-anchoring the reader when a character reappears after a gap (e.g., \"Sculley--the Pepsi executive Jobs had personally recruited--now faced an impossible choice\")\n- Keeping the focus on the 3-5 most important figures; mention minor characters only when necessary and don't let them clutter the narrative\n- Using consistent identifiers (if you call someone \"the young engineer\" once, don't switch to \"the Stanford grad\" later without reason)\n\nThe reader should never have to stop and ask \"Wait, who is this again?\"\n\n**Step 3: Identify and Explain \"Blocker\" Concepts**\n\nScan for business, technical, or industry-specific concepts that are essential to understanding the story. These are \"blocker\" concepts--if the reader doesn't understand them, they'll be lost.\n\nFor each blocker concept:\n\n- Explain it in plain language using an analogy or real-world example\n- Keep explanations to 1-2 sentences maximum\n- Weave these explanations naturally into the narrative the first time the concept appears\n- Use web search where necessary to ensure accuracy when explaining technical concepts\n\nThe target reader is someone who is generally intelligent and curious--they read business books and follow tech news, but they may not know the specifics of every industry. Think of someone with a liberal arts degree who's interested in how great companies are built.\n\n**Step 4: Harvest the Best Quotes**\n\nAcquired episodes are rich with two types of quotes--preserve both:\n\n**From the hosts (Ben Gilbert and David Rosenthal):**\n\n- Their sharpest analytical insights and observations\n- Memorable one-liners or turns of phrase\n- Moments where they reveal something surprising or counterintuitive\n- Attribute clearly (e.g., \"As David Rosenthal puts it...\" or \"Ben Gilbert observes that...\")\n\n**From primary sources the hosts cite:**\n\n- Quotes from founders, executives, journalists, biographers\n- Historical documents, memos, interviews they reference\n- These are gold--they let the protagonists speak for themselves\n- Attribute clearly (e.g., \"As Jobs later recalled...\" or \"In a memo to the board, Hastings wrote...\")\n\nWhen cleaning up quotes:\n\n- Remove filler words (um, uh, like, you know)\n- Fix grammatical mistakes from natural speech\n- Keep the speaker's authentic voice and meaning intact\n- Longer quotes are fine if they're powerful--this isn't a tight summary\n\n**Step 5: Build the Narrative**\n\nStructure the piece like a chapter from a biography:\n\n**Opening:** Start with a scene, a tension, or a question that pulls the reader in. Drop them into a pivotal moment, then zoom out to set the stage. Avoid \"This episode covers...\" framing--just begin the story.\n\n**Middle:** Move through the narrative chronologically or thematically, depending on what serves the story best. Treat major turning points as scenes--slow down, add detail, let the reader feel the weight of the moment. Use quotes to let key players speak at crucial junctures.\n\n**Closing:** End with resonance--what happened next, what it meant, what lesson or question lingers. The reader should close the chapter feeling like they understand something important about business, strategy, or human nature.\n\n**Step 6: Weave It Together**\n\nCombine narrative, analysis, and quotes into one flowing piece that:\n\n- Reads like a chapter from a great business book, not a podcast summary\n- Has no section headers, bullet points, or artificial breaks (a line break between major sections is fine)\n- Includes a compelling title in the style of a book chapter\n- At the beginning, includes a short paragraph capturing the essence of the story and why it matters\n- Makes complete sense to someone who has never heard the podcast\n- Is designed to be printed--no links or screen-dependent elements\n- Balances storytelling with insight: the reader should be both entertained and educated\n\n**Quality Check:**\n\nBefore you finish, ask yourself:\n\n1. \"Does this read like a chapter from a business book I'd actually want to read?\"\n2. \"Does the opening pull me in immediately, like a great first page?\"\n3. \"Have I preserved the best quotes from both the hosts and the primary sources they cite?\"\n4. \"Do the turning points land with dramatic weight, or did I rush past them?\"\n5. \"Would someone who knows nothing about this company walk away understanding the story and why it matters?\"\n6. \"Can the reader keep track of who's who throughout the piece?\"\n7. \"Would this print beautifully in a physical book?\"\n\nIf yes to all, you've succeeded.","created_at":"Thu Jan 08 01:51:01 +0000 2026","like_count":396,"retweet_count":36,"reply_count":16,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network","vbcnewyork-com"],"editorial_note":"Tool relevant to goodalgo network.","signal_type":"tool","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:09.767Z"},{"tweet_id":"2065468488584663232","author":"hasantoxr","author_name":"Hasan Toor","text":"14 YouTube Channels That Can Teach You More Than College\n\n1. Cybersecurity - John Hammond\n2. Artificial Intelligence - Andrej Karpathy\n3. Web Development - Traversy Media\n4. Python - ArjanCodes\n5. DevOps - KodeKloud\n6. Cloud Computing - Google Cloud Tech\n7. Data Analytics - Alex The Analyst\n8. Digital Marketing - Ahrefs\n9. UI / UX Design - Mizko\n10. Blockchain - Patrick Collins\n11. React - Web Dev Simplified\n12. Java - Java Brains\n13. Networking - David Bombal\n14. Personal Branding - Justin Welsh","created_at":"Fri Jun 12 16:17:16 +0000 2026","like_count":319,"retweet_count":77,"reply_count":16,"resolved_url":null,"resolved_type":null,"venture_tags":["freeintelligence-ai","goodalgo-network"],"editorial_note":"Educational resource for freeintelligence ai team and stakeholders.","signal_type":"education","month_tag":"2026-06","ingested_at":"2026-07-01T01:51:46.231Z"},{"tweet_id":"2060332868140757368","author":"exploraX_","author_name":"m0h","text":"100 free resource websites that should be illegal.\n\n12 categories. all free. all legal. links in the repo, comment below\n\nmedia & downloads\n\n1. cobalt tools — download any social media video\n2. https://t.co/e5YtgqRx2b — find streaming locations for any content\n3. https://t.co/0xp2iuZmAk — access any old webpage, plus free software\n4. https://t.co/aLPeUmOEJR — permanently save any webpage\n5. tunefind  — find songs from any show\n6. radio garden — listen to any global radio station\n7. musicforprogramming — focus music\n8. https://t.co/D6aGLsNemb — custom focus soundscapes\n9. https://t.co/GwDOKYH1bd — summarize any YouTube video\n10. y2mate-style tools aside, cobalt covers most of it\n\nimage & design\n\n11. photopea  — free photoshop in your browser \n12. https://t.co/tOZQjsUP31 — one-click background removal \n13. cleanup pictures — erase objects from photos \n14. https://t.co/ehV6vmslVU — free video background removal \n15. https://t.co/yOldfAaMoR — free compression for any image \n16. tinypng — image compression that just works \n17. https://t.co/L0okOzoZ8L — reverse image search \n18. unsplash — free high-res stock photos \n19. https://t.co/TLbICGcNST — free stock photos + videos \n20. pixabay. — free stock images, vectors, music 21. https://t.co/M2W8kGqiT5 — free illustrations you can recolor \n22. heroicons. — free SVG icons \n23. https://t.co/QQpLvlrwGQ — clean open-source icon set \n24. https://t.co/5Izcd6rO3G — color palette generator\n\nPDF & document tools\n\n25. tinywow — 100+ free tools in one place \n26. smallpdf — free PDF editing \n27. ilovepdf  — merge and split PDFs \n28. pdfdrive  — free PDF downloads (mixed catalog — see note)\n29. pdf24 — full PDF toolkit, free \n30. sejda — browser-based PDF editor\n\nbooks, papers & learning\n\n31. gutenberg — 70,000 free classic books \n32. openculture — free courses from top universities \n33. libgen — millions of free textbooks (grey area — see note)\n34. sci-hub — free research papers (grey area — see note)\n35. annasarchive — search every book ever written (grey area — see note)\n36. standardebooks — beautifully formatted public domain books \n37. coursera — audit thousands of university courses free \n38. edx — free courses from MIT, Harvard, more \n39. khanacademy — free K-12 + college subjects \n40. freecodecamp — full dev curriculum, free  \n41. theodinproject — free full-stack dev path \n42. cs50.harvard — Harvard's intro CS course, free\n\nresearch & academic\n\n43. elicit — AI research paper assistant \n44. consensus — search scientific consensus \n45. connectedpapers — visualize and map research \n46. semanticscholar — free academic search \n47. scispace — understand any research paper \n48. researchrabbit — discover related papers \n49. https://t.co/CNr8v6gvLh — academic search engine\n\ndeveloper tools\n\n50. regex101  — instantly test any regular expression \n51. codebeautify — cleanly format any code \n52. explainshell  — understand terminal commands \n53. carbon — turn code into artwork \n54. ray  — stunning code screenshots \n55. phind — developer AI search \n56. https://t.co/ntyEtl5571 — every dev doc in one searchable place \n57. https://t.co/x7DgMESCtl — browser support for any web feature \n58. https://t.co/hMHBLDvFwf — format and validate JSON \n59. transform  — convert between data/code formats \n60. https://t.co/WtuMDsxFTC — explain any cron expression 61. https://t.co/9bSBLxNaSF — generate readme badges\n\nproductivity & whiteboarding\n\n62. https://t.co/jNAWwQOU5I — free hand-drawn charts \n63. https://t.co/gUtvx9EAJ8 — infinite whiteboard in your browser \n64. https://t.co/ZlnClDEDas — collaborative whiteboard (free tier) \n65. https://t.co/v82ZYP2SC9 — free notes/docs/databases \n66. obsidian.md — local-first markdown knowledge base \n67. https://t.co/U6Njeoko1y — encrypted google-docs alternative\n\nprivacy & temp tools\n\n68. https://t.co/vyKx3JfABG — one-click temporary email \n69. 10minutemail — instant temporary email \n70. https://t.co/Oip0wREWUm — send self-destructing messages \n71. https://t.co/0BwUGOVZZG — share auto-deleting files \n72. accountkiller  — delete yourself from any website \n73. https://t.co/N16qAL6uEQ — free email aliases \n74. cryptee  — encrypted notes + photos\n\nsecurity & checks\n\n75. haveibeenpwned — check if you've been hacked \n76. virustot  — scan any file for malware \n77. downdetector — check if any website is down \n78. urlvoid — check if a URL is sketchy \n79. whoer — see what sites see about you\n\nutility & misc\n\n80. wolframalpha — instantly solve any math problem \n81. alternativeto — find free app alternatives \n82. flightradar24 — real-time tracking for any flight \n83. camelcamelcamel — track amazon price history \n84. fast — check internet speed \n85. speedtest— bandwidth + latency check \n86. wetransfer — send files up to 2GB free \n87. fakespot — detect fake amazon reviews \n88. exchange-rates — clean currency conversion \n89. timeanddate — meeting planner across timezones \n90. world.taximeter — estimate cab fare anywhere\n\nwriting & content\n\n91. hemingwayapp  — make your writing clearer \n92. languagetool — free grammar checker \n93. deepl — translation that beats google translate \n94. quillbot. — paraphrase + summarize (free tier) \n95. https://t.co/K0geVwVeb4 — AI search with sources \n96. https://t.co/IUSAMbIgho — yes, this thing \n97. https://t.co/OZfOCljPof — AI search + writing \n98. https://t.co/gfwenVL9Vu — free AI writing (small tier)\n\naudio & video\n\n99. https://t.co/M7Nhrxk8qW — free browser audio editor \n100. https://t.co/Xs4kWcEeJ1 — free in-browser video editor","created_at":"Fri May 29 12:10:09 +0000 2026","like_count":266,"retweet_count":50,"reply_count":10,"resolved_url":"https://justwatch.com/","resolved_type":"external","venture_tags":["goodalgo-network","sliver-network","subwaymusician-xyz","instasoiree-com","dank-nyc","misoley-com"],"editorial_note":"Tool relevant to goodalgo network.","signal_type":"tool","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:03.448Z"},{"tweet_id":"2058745477307531775","author":"_vmlops","author_name":"Vaishnavi","text":"JPMORGAN OPEN-SOURCED THEIR INTERNAL PYTHON TRAINING \n\nused to train jpmorgan's own business analysts and traders\n\nnow it's sitting on github with 13.2k stars, open for anyone\n\n▫️ intro to numerical computing in python\n▫️ data visualization with financial datasets\n▫️ real financial data (iex cloud) + airport/route datasets\n▫️ runs entirely in your browser via binder no setup needed\n▫️ jupyter notebooks, taught by jpmorgan technologists\n\nno cs degree needed... built specifically for people without formal programming backgrounds\n\nif you're breaking into quant finance, data roles, or just want finance-focused python practice this is the repo\n\nhttps://t.co/EeFsuusvrw","created_at":"Mon May 25 03:02:26 +0000 2026","like_count":217,"retweet_count":38,"reply_count":0,"resolved_url":"https://github.com/jpmorganchase/python-training","resolved_type":"github","venture_tags":["goodalgo-network"],"editorial_note":"Theory for goodalgo network.","signal_type":"theory","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:05.215Z"},{"tweet_id":"2012155215726706694","author":"Mnilax","author_name":"Mnimiy","text":"Built my own arb bot for Polymarket. Does it work?\n\nHere’s everything u need to know.\n\nRecorded this video two days ago, u can see the latest tests that Claude ran.\n\nWhat’s the idea?\n\nIf at any moment on Polymarket YES price + NO price < 1.00, that’s guaranteed profit.\n\nThe bot:\n- automatically scans for such situations\n\n- verifies that they are actually executable based on the order book\n\n- carefully buys both sides\n\n- handles failure scenarios if the market moves\n\nKey design decision: shares-first model. \n\nAll position sizes are calculated in shares, not USD.\nUSD is only a derived value.\n\nThe algorithm:\n> scans markets via API\n\n> calculates edge using VWAP\n\n> evaluates executability\n\n> executes trades using FOK / IOC / TTL\n\n> handles failure and edge cases\n\n> operates in three modes: paper, shadow, live\n\nArchitecture:\n\nMarket layer order books and fees -> Strategy layer: VWAP and edge calculation\n\nExecution layer -> Recovery layer: hedge and stop-loss ->\n\nSafety & ops: kill switch, rate limits -> Storage \n\nI tested the bot in shadow mode for two days and it managed to turn $100 into $119. \n\nArbitrage is a purely mathematical problem and it can be solved.\n\nI’ll keep working on it and share more results later.","created_at":"Fri Jan 16 13:29:22 +0000 2026","like_count":211,"retweet_count":11,"reply_count":34,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:02.469Z"},{"tweet_id":"2061883600208035923","author":"embrron","author_name":"MO","text":"Prediction markets are no longer one mechanism, they’re becoming a design space.\n\nover the next few weeks, I'll break down 7 prediction market primitives, one by one:\n1. Binary Markets\n2. Event Contracts\n3. Scalar Markets\n4. Decision Markets\n5. Multiverse Markets\n6. Information Markets\n7. Continuous Markets\n\nEach one exists because a different type of belief needs a different market structure.\n\nBeliefs have different shapes, Markets should too!","created_at":"Tue Jun 02 18:52:12 +0000 2026","like_count":210,"retweet_count":24,"reply_count":25,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network","eventbuoy-com","fishboneny-com","instasoiree-com"],"editorial_note":"Market data point for goodalgo network: sizing or supply chain insight.","signal_type":"market","month_tag":"2026-06","ingested_at":"2026-07-01T01:51:45.563Z"},{"tweet_id":"2008923927154966785","author":"ankitkr0","author_name":"Ankit","text":"@Polymarket 👉 https://t.co/jA0jMNavOA https://t.co/WPWCOuJiUR","created_at":"Wed Jan 07 15:29:22 +0000 2026","like_count":202,"retweet_count":14,"reply_count":15,"resolved_url":"https://polymarketimes.com/","resolved_type":"external","venture_tags":["goodalgo-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:13.502Z"},{"tweet_id":"2056855425446994349","author":"papa_couch","author_name":"Couch","text":"A few days ago, a surprisingly deep paper on Polymarket market microstructure was published.\n\nIn it, Philipp D. Dubach highlights one very interesting idea: “Reconstructing true market state from realtime feeds is significantly harder than it looks.”\n\nThere is far more infrastructure hidden behind a normal market feed than most people probably realize.\n\nFeed synchronization. Order book reconstruction. Timestamp alignment. Stream reconciliation.\n\nAt some point, all of this starts resembling distributed systems engineering much more than trading itself.\n\n(https://t.co/WUCStGx9YW)\n\nrecommend reading it 👍","created_at":"Tue May 19 21:52:02 +0000 2026","like_count":195,"retweet_count":13,"reply_count":16,"resolved_url":"https://arxiv.org/pdf/2604.24366","resolved_type":"arxiv","venture_tags":["goodalgo-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:12.978Z"},{"tweet_id":"2056988557869543932","author":"stacy_muur","author_name":"Stacy Muur","text":"If you ignore studying AI Agents in 2026, you’re voluntarily choosing to play Dark Souls on permadeath mode.\n\nHermes + Polymarket agent setup, TL;DR ↓ https://t.co/oGc4zxkiyG","created_at":"Wed May 20 06:41:03 +0000 2026","like_count":178,"retweet_count":52,"reply_count":32,"resolved_url":"https://twitter.com/stacy_muur/status/2056988557869543932/photo/1","resolved_type":"media","venture_tags":["goodalgo-network","collectivewin-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:15.010Z"},{"tweet_id":"2056666511905861653","author":"Param_eth","author_name":"Param","text":"POLYMARKET INSIDER TRACKER: \n\nI built an insider detection tool for @Polymarket.\n\nIt maps every wallet betting on a market, \n\nflags coordinated clusters and shows you real onchain positions in one click.\n\nLaunching: https://t.co/XQ5Z7akOUy\n\nPick any market and:\n\n> See every whale, insider and sybil ring on the map\n\n> Click a bubble \n- Polymarket profile\n- positions \n- trades\n\n> Identify coordinated entries before the price moves.\n\nWhat it can do:\n\n> Visualize 200+ real onchain wallets per market in a live force-directed bubble map\n\n> Click any bubble and get cost basis, P&L, win rate, trade history, link to their Polymarket profile\n\n> Live whale-feed ticker showing every recent BUY / SELL on the market\n\nExample flow:\n\nYou're scrolling Polymarket. \n\nA market is trading at 14¢.\n\nYou open PolyMaps.\n\nThere's a tight cluster of 7 wallets, all glowing orange.\n\nYou click one: \"Bought $14K @ 13¢, 2h ago.\"\n\nClick another. \nSame outcome. \nSame time. \nSame price.\n\nYou're watching a coordinated entry in real time.\n\n20 minutes later, the market is at 38¢.\n\nBuilding in public.","created_at":"Tue May 19 09:21:22 +0000 2026","like_count":174,"retweet_count":11,"reply_count":46,"resolved_url":"https://polymapss.netlify.app/","resolved_type":"external","venture_tags":["goodalgo-network","onesqft-org"],"editorial_note":"Tool relevant to goodalgo network.","signal_type":"tool","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:12.845Z"},{"tweet_id":"2060431173625540631","author":"sxtvik","author_name":"satvik","text":"Some observations from referring 63 founders to @alliance, maybe helpful for others:\n\n1. Too many people building prediction markets still, what you think is a novel company is a weekend feature for incumbents who've raised a billion dollars and already have distribution.\n2. Too many perp dexes and leveraged trading products still, their \"novelty\" is usually stacking leverage on already leveraged assets aka cascading catastrophe for users. If you burn the user once, they won't return.\n3. Lot of agentic use cases, the low hanging fruit (agentic commerce, agentic coordination/unification) is less exciting personally. But a few novel applications across healthcare, science, gaming stood out to me.\n4. Solana and Hyperliquid reign supreme, Base is a close 3rd. No Monad, MegaETH, Ethereum, etc. This is maybe an Alliance alignment issue or a larger preference trend for builders.\n5. What many builders believe is unique and new is most likely already being done by another person in my DMs. The immediate opportunities are very obvious and $500K might not be enough to take on Stripe and Ramp, find new avenues where you have an unfair advantage and asymmetric opportunity.\n6. Not a lot of \"cypherpunk/privacy\" builders, I think there's still massive opportunities in resilience, networking, shielding, identity for both crypto and AI use cases that I would've loved to see more of. \n7. Manners. A please, thank you, and professionalism in cold messages go a long way.","created_at":"Fri May 29 18:40:47 +0000 2026","like_count":173,"retweet_count":9,"reply_count":33,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network","oneof1-network","velab-org","onesqft-org","groww-ca","myblackbean-com"],"editorial_note":"Market signal for goodalgo network.","signal_type":"trend","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:03.530Z"},{"tweet_id":"2039727392915349902","author":"joshalbrecht","author_name":"Josh Albrecht","text":"mngr: programmatically manage 100s of claude code sessions in parallel 🤖\n\nopen source today.\n\nlets you do things like:\n— for each open GitHub issue, create a PR\n— for each flaky test in the past week, fix it\n— for each rule in style guide, scan codebase & fix all instances\n\nruns any agent: @claudeai, codex, @opencode, etc.\n\nruns on any compute: locally, @modal, @Docker, or anything you can ssh into.","created_at":"Thu Apr 02 15:31:21 +0000 2026","like_count":171,"retweet_count":37,"reply_count":28,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network","velab-org","velab-stack"],"editorial_note":"Tool relevant to goodalgo network.","signal_type":"tool","month_tag":"2026-04","ingested_at":"2026-07-01T04:05:08.273Z"},{"tweet_id":"2027740878945611986","author":"alex_verem","author_name":"Alex Veremeyenko","text":"The word \"algorithm\" is literally one guy's name.\n\nMuhammad al-Khwārizmī, a Persian mathematician from 780 CE, wrote a book so influential that when it was translated to Latin, his name became the word \"Algoritmi.\"\n\n1,200 years later, that same concept powers every AI tool you use.\n\nHere's why this matters for your business right now 👇","created_at":"Sat Feb 28 13:41:13 +0000 2026","like_count":138,"retweet_count":31,"reply_count":13,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Tool relevant to goodalgo network.","signal_type":"tool","month_tag":"2026-02","ingested_at":"2026-07-01T04:05:05.612Z"},{"tweet_id":"2006769653193044186","author":"aryanXmahajan","author_name":"Aryan Mahajan","text":"spend 5 minutes daily creating content that books 10+ calls weekly\n\nthe secret is context-engineered AI that knows:\n- your business positioning\n- your ICP psychology\n- your brand voice\n- platform-specific patterns\n\nnot chatgpt generic garbage\n\nthe problem with most AI content:\n\nyou prompt for 30 minutes\nget back wikipedia slop\nedit for another hour making it human\nstill sounds like AI\ngets 8 likes\n\nwhy? because AI doesn't know your context\n\nthe solution:\n\nAI is input → output\nbetter context = better content\n\nwhat your AI needs to know:\n\nlayer 1 - business intelligence\nICP psychology (actual pain points not demographics)\nbusiness context (positioning, advantages)\npersonal profile (your story)\nproduct strategy (what you sell, why it matters)\nbrand voice (how you communicate)\n\nlayer 2 - platform patterns\nbest performing posts (your actual winners)\nplatform formatting (linkedin ≠ twitter)\nconversion patterns (what makes YOUR audience act)\n\nlayer 3 - identity programming\nnot \"you are a copywriter\"\nbut \"you're a growth marketer who discovered emotional triggers drive 10x conversions\"\n\nlive example:\n\ni ask my AI: \"create linkedin + twitter lead magnet for ad creative system\"\n\nmy AI:\nactivates brand voice profile\nloads ICP psychology\nreferences platform examples\ngenerates 2 perfect posts in 30 seconds\n\none for linkedin, one for twitter\ndifferent platforms, different tones\nboth sound exactly like me\n\nresults:\n5 minutes daily creating 10 linkedin posts + 20-30 tweets\nall in my voice\nall platform-optimized\nall converting at scale\n\ndeployed this for clients:\nrudy (50K coaching offer, scaled to 6 figures)\nsharon hedge (2K likes per post)\nlinah ai (0 to 11K followers in 60 days)\n\nyour AI stops sounding like AI when you give it proper context","created_at":"Thu Jan 01 16:49:03 +0000 2026","like_count":124,"retweet_count":10,"reply_count":5,"resolved_url":null,"resolved_type":null,"venture_tags":["freeintelligence-ai","goodalgo-network","oneof1-network"],"editorial_note":"Tool relevant to freeintelligence ai.","signal_type":"tool","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:09.679Z"},{"tweet_id":"2056168763439903058","author":"GingyTrades","author_name":"GingyTrades","text":"Gaming will make a huge comeback in the next years due to the amount of volume/liquidity in prediction markets.\n\nEsports markets on Polymarket are going to be huge.","created_at":"Mon May 18 00:23:29 +0000 2026","like_count":99,"retweet_count":1,"reply_count":36,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:05.090Z"},{"tweet_id":"2059485840867303711","author":"masonnystrom","author_name":"Mason Nystrom","text":"Great essay. My takeaways\n\n1) Esports is an underserved prediction market vertical. If you're building this my DMs are open. \n\n2) Weather bettors really like the weather, but retention was lower (strange?), indicating solving something as part of that market structure or building a better weather product (e.g. derivative, better data feed) could really increase weather betting retention. \n\n3) Sports users mostly stick to themselves, showcasing the need for a dedicated market for sports predictions. \n\n4) Listings is another way to say \"asset differentiation\" which is core to any marketplace. The best marketplaces provide differentiated supply of tradeable assets, but the key to find ways to build propriety into those assets (e.g. via unique data feeds, licensing, user data, regulatory compliance, local targeting, etc.)","created_at":"Wed May 27 04:04:22 +0000 2026","like_count":78,"retweet_count":0,"reply_count":16,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network","onesqft-org"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:15.493Z"},{"tweet_id":"2056116659857813680","author":"Baheet_","author_name":"Baheet","text":"CLOBS are failing prediction markets\n\non polymarket and kalshi, the long tail market doesn't exist because the market makers can't/won't provide liquidity for them\n\nwhich is why polymarket and kalshi both concentrate activity in a handful of flagship categories; \n\nmost of their thousands of listed markets stay dormant or low-volume.","created_at":"Sun May 17 20:56:27 +0000 2026","like_count":68,"retweet_count":4,"reply_count":18,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:08.136Z"},{"tweet_id":"2059397285856125413","author":"ericliujt","author_name":"Eric Liu","text":"Parlays on prediction markets sound simple on the frontend. But on the seller side, they create a bunch of hard microstructure problems: collateral, pricing, hedging, risk management etc.\n\nThis article covers one of the first problems we’re tackling at Totalis: reducing MM collateral requirements without making the system under-collateralized.","created_at":"Tue May 26 22:12:29 +0000 2026","like_count":64,"retweet_count":0,"reply_count":5,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:13.089Z"},{"tweet_id":"2062945392573006017","author":"thenarrator","author_name":"good","text":"new generation of sports prediction markets isn't a marketing reframe, it's a completely different infrastructure underneath\n\npeer-to-peer order books, on-chain execution, micro markets and a bunch more\n\n@Novig: $4b annualized\n@predofficial: sub-200ms on base\n@Underdog: pivoted out of fantasy and current unicorn status\n\nthe audience that cares about pricing has somewhere else to go now","created_at":"Fri Jun 05 17:11:23 +0000 2026","like_count":63,"retweet_count":3,"reply_count":14,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data point for goodalgo network: sizing or supply chain insight.","signal_type":"market","month_tag":"2026-06","ingested_at":"2026-07-01T01:51:48.744Z"},{"tweet_id":"2063831347513135474","author":"thenarrator","author_name":"good","text":"for years prediction markets have been asking which mechanism wins\n\nlmsr or clob\namm or parimutuel\nbonding curves or order books\n\nthe more interesting answer is increasingly: all of them\n\nthe next primitive isn't a new mechanism, but it's composition\n\neach primitive doing the one thing it's best at\n\nprediction markets are starting to look less like products and more like market operating systems","created_at":"Mon Jun 08 03:51:52 +0000 2026","like_count":59,"retweet_count":6,"reply_count":14,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data point for goodalgo network: sizing or supply chain insight.","signal_type":"market","month_tag":"2026-06","ingested_at":"2026-07-01T01:51:47.988Z"},{"tweet_id":"2056096149585416429","author":"thenarrator","author_name":"good","text":"we're in the first chapter of prediction markets: the infancy phase\n\nthe real evolution is prediction markets becoming the risk engine underneath finance (mostly how i see it)\n\none of the problems in defi lending is that everything is overcollateralized (you deposit $150 to borrow $100). it works but it's capital inefficient and it locks out anyone who doesn't already have more money than they need to borrow\n\na wallet with hundreds of resolved predictions at 78% accuracy has proven judgment under uncertainty, which is a honest risk signal\n\nthe protocol assigns trust tiers based on accuracy where higher accuracy means lower collateral requirements (your skill literally reduces your cost of capital) \n\ncombine that with live prediction markets monitoring event risk on your collateral in real time and you have a lending system where trust is earned through demonstrated ability\n\nthis can be one way where defi eventually competes with tradfi","created_at":"Sun May 17 19:34:57 +0000 2026","like_count":52,"retweet_count":3,"reply_count":16,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network","eventbuoy-com","fishboneny-com","instasoiree-com"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:08.120Z"},{"tweet_id":"2064064781342917029","author":"ninedol","author_name":"Ninedol","text":"This 17-minute lecture will help you understand how information spreads among people even before professional traders on Polymarket start to take it into account\n\nIf you find out about something from the headlines, you’re probably already too late.\n\nThe speaker clearly explains why relationships, trust and communication often give an edge long before it becomes publicly apparent.\n\n> valuable information spreads through networks, not through news headlines\n> trust determines who gets the information first\n> understanding motivation helps explain people’s actions\n\nMost traders focus solely on charts and figures, but the best forecasters understand the people behind the information, which is why they often spot changes before the crowd.\n\nWatch the video → then read the article below.\n\nYou will stop viewing the markets as a collection of bets and start to understand the people behind the prices.","created_at":"Mon Jun 08 19:19:26 +0000 2026","like_count":44,"retweet_count":2,"reply_count":12,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Educational resource for goodalgo network team and stakeholders.","signal_type":"education","month_tag":"2026-06","ingested_at":"2026-07-01T01:51:47.700Z"},{"tweet_id":"2066242825562513877","author":"embrron","author_name":"MO","text":"We have 90+ concepts in prediction markets, all getting leveraged by builders to build something new.\n\nParlays are one of my top 10.\n\nMost people think of them as a degen lottery ticket but that's wrong.\n\nA parlay is a bet on correlation: do these move together.\n\nWhy it's cool? a sportsbook prices each leg alone, so does a binary market. neither prices how they move together.\n\nThat gap is the correlation, the part they delete.\n\nBut finally, we have exchanges that actually let you trade it.","created_at":"Sun Jun 14 19:34:13 +0000 2026","like_count":35,"retweet_count":1,"reply_count":10,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data point for goodalgo network: sizing or supply chain insight.","signal_type":"market","month_tag":"2026-06","ingested_at":"2026-07-01T01:51:47.159Z"},{"tweet_id":"2056432599271141551","author":"ZHeerwagen","author_name":"CryptoZach.eth","text":"Interesting to see the heat coming from @mattkalish against Kalshi, and PMs generally. \n\nOverall: I think his take is mostly warranted / accurate, prediction markets are early, both as apps and as a category. \n\nEspecially in the case of sports books as a competitive product, predictions offer only marginally better fees. After accounting for bonuses and other promotions, the fees are likely worse for most.\n\nWhere he's spot on, PMs are better than sportsbooks for:\n1) Professional gamblers \n2) Professional market makers \n3) Employees / investors in exchanges or ppl making deriv products\n\nThat's exactly the point. \n\nPrediction markets turn 'gambling' into real financial infrastructure that can be leveraged by institutions and market makers. \n\nThe UX will improve, and the tech is here to stay.","created_at":"Mon May 18 17:51:52 +0000 2026","like_count":30,"retweet_count":3,"reply_count":10,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:05.156Z"},{"tweet_id":"2063967279927242806","author":"Baheet_","author_name":"Baheet","text":"I believe this article can act as a North Star for builders and contributors in PMs\n\nespecially if you’re looking to build novel prediction markets products \n\nwithout having to directly compete with polymarket and kalshi \n\nthis is solid work @netrovertHQ","created_at":"Mon Jun 08 12:52:00 +0000 2026","like_count":28,"retweet_count":2,"reply_count":4,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data point for goodalgo network: sizing or supply chain insight.","signal_type":"market","month_tag":"2026-06","ingested_at":"2026-07-01T01:51:48.063Z"},{"tweet_id":"2062379221570163093","author":"thenarrator","author_name":"good","text":"the next breakthrough in prediction markets is not choosing the right mechanism. it is combining them across a market’s lifecycle\n\neach phase uses the mechanism best suited for that stage","created_at":"Thu Jun 04 03:41:38 +0000 2026","like_count":26,"retweet_count":0,"reply_count":7,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data point for goodalgo network: sizing or supply chain insight.","signal_type":"market","month_tag":"2026-06","ingested_at":"2026-07-01T01:51:48.944Z"},{"tweet_id":"2056396151100768541","author":"0xForecaster","author_name":"Forecaster","text":"most people on polymarket are betting on outcomes\n\nthe sharpest traders are betting on market inefficiencies\n\nbig difference\n\nthe 4 edges i keep seeing go underused:\n\n1. information speed  \n2. probability mispricing  \n3. market making  / liquidity provision\n4. trading against emotional retail flow\n\nmost users are just placing bets \n\nthe sharper players are treating these markets like microstructure games","created_at":"Mon May 18 15:27:03 +0000 2026","like_count":19,"retweet_count":3,"reply_count":6,"resolved_url":null,"resolved_type":null,"venture_tags":["anygame-dev","goodalgo-network"],"editorial_note":"Market data for anygame dev.","signal_type":"market","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:05.106Z"},{"tweet_id":"2013239120391262621","author":"quantscience_","author_name":"Quant Science","text":"That's a wrap! Over the next 24 days, I'm sharing my top 24 algorithmic trading concepts to help you get started.\n\nIf you enjoyed this thread:\n\n1. Follow me @quantscience_ for more of these\n2. RT the tweet below to share this thread with your audience","created_at":"Mon Jan 19 13:16:25 +0000 2026","like_count":17,"retweet_count":2,"reply_count":0,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Intelligence signal for VE Lab portfolio.","signal_type":"general","month_tag":"2026-01","ingested_at":"2026-07-01T04:05:04.856Z"},{"tweet_id":"2062187605354029280","author":"Baheet_","author_name":"Baheet","text":"how to exploit price shocks in the 2026 world cup markets on Polymarket\n\nI will have to give this another read\n\nbut i can say the viability of the strategies discussed here depends on how liquid the markets are \n\nbut this is good work from @RohOnChain \n\nhighly recommended","created_at":"Wed Jun 03 15:00:13 +0000 2026","like_count":13,"retweet_count":0,"reply_count":2,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data point for goodalgo network: sizing or supply chain insight.","signal_type":"market","month_tag":"2026-06","ingested_at":"2026-07-01T01:51:49.011Z"},{"tweet_id":"2052016325845778903","author":"0xForecaster","author_name":"Forecaster","text":"the real moat in prediction markets may not be liquidity\n\nit may be the ability to identify calibrated people before the market realizes they’re calibrated\n\nbecause once someone is publicly “sharp”\n\n> their edge compresses fast\n> their positions get copied\n> their signal gets priced in\n> their information advantage decays\n\nwhich means reputation alone isnt  the moat\n\nreputation is lagging\n\nthe deeper edge is:\nwho can evaluate signal before it becomes obvious\n\nalmost like talent scouting for forecasters\n\nand underneath that, there’s an even bigger layer:\n\nmost strong forecasters arent just “smart”\n\nthey’re plugged into better \n\n> information networks\n> domain experts\n> private communities\n> early data\n> people close to the source\n\nso maybe the next frontier isnt just prediction markets\n\nit’s systems that surface credible networks and reward real calibration before the crowd catches on\n\nthe irony is the system that does this well\n\nprobably cant be public\n\nthe moment it is, the edge is gone","created_at":"Wed May 06 13:23:11 +0000 2026","like_count":9,"retweet_count":0,"reply_count":3,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Market data for goodalgo network.","signal_type":"market","month_tag":"2026-05","ingested_at":"2026-07-01T04:05:14.823Z"},{"tweet_id":"2071434117456027959","author":"not_ellington","author_name":"","text":"Probably 10x better than any of the eduslopppp bullshit you'll find in the 15 min threads with 2k bookmarks that have been put out in the past year truth be told. The best way to learn will always be to just sit down and read and reread and reread again\n\nhttps://t.co/Rz14zg9OdL","created_at":"","like_count":0,"retweet_count":0,"reply_count":0,"resolved_url":null,"resolved_type":null,"venture_tags":["goodalgo-network"],"editorial_note":"Educational resource for goodalgo network team and stakeholders.","signal_type":"education","month_tag":"2026-06","ingested_at":"2026-07-02T01:42:19.275Z"}]}