Загрузка видео...

Не удалось загрузить видео

На главную

01 — One query, one research flow. This personal DIY video explores how Cambrian Network and TrueNorth could complement each other, moving from live market evidence to deeper analysis. 02 — Cambrian / Data Live prices, interactive K-lines, OHLCV, trading activity, liquidity, holder insights, security metrics and risk signals,...

chen1904o's profile picture

Mingrise｜八方來財版

1,881 subscribers

10,216 просмотров • 1 месяц назад •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Prediction markets are one of crypto’s most interesting sectors right now, and I like how Fortune is approaching them. Fortune Agent is what stood out to me most. It’s more than a chatbot summarizing headlines. Its multi-agent system scans live news, sentiment and possible arbitrage opportunities, then validates potential trades based on the user’s chosen amount and risk level. What I like is how it brings research and execution together. Instead of jumping between news feeds, market data and trading platforms, users can find opportunities and act on them from one place while keeping control of their risk. Fortune also isn’t building another isolated prediction market. Its aggregator now brings Polymarket liquidity alongside Predictfun, letting users browse more markets and compare liquidity, volume and probabilities through one interface. The updated flow also allows users to select an outcome, preview their position before trading and track open or settled positions in one portfolio. Following its completed Pre-A round, Fortune is heading toward its TGE coming soon. Users can earn F-Points beforehand through prediction trading, daily activities and Council participation. With its AI Agent, growing liquidity and rewards for active users, Fortune is looking strong heading into TGE!
1:00

Prediction markets are one of crypto’s most interesting sectors right now, and I like how Fortune is approaching them. Fortune Agent is what stood out to me most. It’s more than a chatbot summarizing headlines. Its multi-agent system scans live news, sentiment and possible arbitrage opportunities, then validates potential trades based on the user’s chosen amount and risk level. What I like is how it brings research and execution together. Instead of jumping between news feeds, market data and trading platforms, users can find opportunities and act on them from one place while keeping control of their risk. Fortune also isn’t building another isolated prediction market. Its aggregator now brings Polymarket liquidity alongside Predictfun, letting users browse more markets and compare liquidity, volume and probabilities through one interface. The updated flow also allows users to select an outcome, preview their position before trading and track open or settled positions in one portfolio. Following its completed Pre-A round, Fortune is heading toward its TGE coming soon. Users can earn F-Points beforehand through prediction trading, daily activities and Council participation. With its AI Agent, growing liquidity and rewards for active users, Fortune is looking strong heading into TGE!

Caleb

23,206 просмотров • 18 дней назад

Hive Intelligence Launches Specialized Crypto Agents Hive Intelligence has released a suite of 17 specialized crypto agents that extend Claude Code's capabilities for professional crypto development and analysis. Extending Claude Code for Crypto Work Claude Code, Anthropic's command-line coding tool, now has access to specialized crypto intelligence through Hive's agent framework. These 17 agents work alongside SuperClaude's 14 base development agents, bringing the total available agent count to 31. The key difference: instead of generic AI responses to crypto queries, developers now have access to specialized agents trained for specific blockchain domains, from smart contract auditing to MEV research to DeFi strategy optimization. How the Agents Work After installation, the agents operate automatically based on query context. When you ask Claude Code to perform crypto-related tasks, the appropriate specialist agent is invoked: - "Audit this smart contract" → Crypto Security Researcher - "Find yield farming opportunities on Ethereum" → Crypto DeFi Strategist - "Analyze this wallet's transaction history" → Crypto Wallet Detective - "Identify arbitrage opportunities across DEXs" → Crypto DEX Arbitrageur No manual agent selection required. The system recognizes the task and routes it to the appropriate specialist. The 17 Specialized Agents Market & Trading Intelligence (4 agents) Crypto Quant: Mathematical models, algorithmic trading strategies, statistical arbitrage, and quantitative risk modeling. Crypto Market Researcher: Fundamental analysis, market trends, institutional adoption tracking, and regulatory landscape monitoring. Crypto Derivatives Trader: Futures and perpetuals analysis, options strategies, leverage management, and derivatives market intelligence. Crypto DEX Arbitrageur: Cross-exchange arbitrage identification, MEV strategy development, and automated profit extraction techniques. DeFi & Liquidity (4 agents) Crypto DeFi Strategist: Yield farming optimization, protocol analysis, liquidity provision strategies, and DeFi portfolio management. Crypto Liquidity Manager: Pool optimization, impermanent loss calculation and mitigation, market making strategies, and capital efficiency analysis. Crypto Governance Analyst: DAO structure evaluation, governance token analysis, proposal assessment, and voting mechanism research. Crypto Bridge Analyst: Cross-chain bridge security assessment, protocol comparison, interoperability solutions, and bridge risk evaluation. Security & Risk (3 agents) Crypto Security Researcher: Smart contract auditing, vulnerability detection, honeypot identification, and exploit pattern recognition. Crypto Security Engineer: Secure contract development practices, defensive programming patterns, and security implementation guidance. Crypto Risk Manager: Portfolio risk assessment, compliance monitoring, exposure analysis, and risk mitigation strategy development. On-Chain Analysis (3 agents) Crypto Wallet Detective: Blockchain forensics, wallet behavior analysis, transaction tracing, and entity identification across chains. Crypto On-chain Analyst: Transaction pattern analysis, wallet clustering, flow tracking, and on-chain metrics interpretation. Crypto MEV Researcher: MEV opportunity detection, flashloan arbitrage analysis, sandwich attack identification, and MEV protection strategies. Specialized Intelligence (3 agents) Crypto NFT Specialist: Collection valuation, rarity analysis, marketplace trends, and NFT ecosystem intelligence. Crypto Stablecoin Analyst: Peg stability monitoring, collateral analysis, depegging risk assessment, and stablecoin mechanism evaluation. Crypto Social Sentiment: Social media sentiment tracking, influencer monitoring, trending topic identification, and community analysis. Data Coverage: - 60+ blockchain networks - 2,000+ DeFi protocols - Real-time DEX data - CEX trading metrics - Social sentiment feeds - NFT marketplace data Compatibility: Works seamlessly with SuperClaude's existing agent framework. No configuration conflicts or manual routing needed. Practical Applications Smart Contract Development Security agents can audit contracts during development, identifying reentrancy risks, access control issues, and common vulnerabilities before deployment. DeFi Research Strategy agents query real-time pool data across networks, calculate yield-adjusted returns, and assess risks like impermanent loss or smart contract exposure. Trading Analysis Market agents access derivatives data, funding rates, liquidation levels, and order book depth across exchanges for informed trading decisions. Forensic Investigation On-chain agents trace fund flows, identify connected addresses, and analyze transaction patterns for security research or compliance work. Portfolio Management Risk agents evaluate protocol exposure, assess tail risks, and monitor positions across multiple chains and protocols. Why Specialized Agents Matter Generic AI models lack the domain-specific knowledge required for professional crypto work. A general-purpose AI might provide surface-level analysis of a smart contract, but a specialized security agent understands Solidity patterns, common exploits, and auditing methodologies. The agent framework solves this by routing tasks to specialists with deep domain knowledge: - A derivatives question goes to an agent trained on perpetuals, funding rates, and options greeks - A DeFi query reaches an agent that understands liquidity mathematics and protocol mechanics - A security audit is handled by an agent familiar with vulnerability patterns and exploit techniques This specialization produces more accurate, actionable insights than single-model approaches. Getting Started The agents are available now through npm. Requirements: - Node.js 16+ - Claude Code installed - No additional dependencies After installation, simply use Claude Code normally. When you ask crypto-related questions or request blockchain analysis, the appropriate agent is automatically invoked. The system handles routing, data retrieval, and response generation. Documentation covers individual agent capabilities, example queries, and integration patterns for different workflows. What This Enables With 17 specialized crypto agents, Claude Code becomes a comprehensive blockchain development and analysis environment: - Developers can audit contracts, optimize gas usage, and implement security patterns - Researchers can analyze protocols, compare yields, and assess risks - Traders can evaluate markets, identify opportunities, and manage positions - Security professionals can investigate exploits, trace funds, and assess vulnerabilities The agents provide access to blockchain data and specialized analysis that previously required multiple tools, APIs, and manual research. ghive.
0:56

Hive Intelligence Launches Specialized Crypto Agents Hive Intelligence has released a suite of 17 specialized crypto agents that extend Claude Code's capabilities for professional crypto development and analysis. Extending Claude Code for Crypto Work Claude Code, Anthropic's command-line coding tool, now has access to specialized crypto intelligence through Hive's agent framework. These 17 agents work alongside SuperClaude's 14 base development agents, bringing the total available agent count to 31. The key difference: instead of generic AI responses to crypto queries, developers now have access to specialized agents trained for specific blockchain domains, from smart contract auditing to MEV research to DeFi strategy optimization. How the Agents Work After installation, the agents operate automatically based on query context. When you ask Claude Code to perform crypto-related tasks, the appropriate specialist agent is invoked: - "Audit this smart contract" → Crypto Security Researcher - "Find yield farming opportunities on Ethereum" → Crypto DeFi Strategist - "Analyze this wallet's transaction history" → Crypto Wallet Detective - "Identify arbitrage opportunities across DEXs" → Crypto DEX Arbitrageur No manual agent selection required. The system recognizes the task and routes it to the appropriate specialist. The 17 Specialized Agents Market & Trading Intelligence (4 agents) Crypto Quant: Mathematical models, algorithmic trading strategies, statistical arbitrage, and quantitative risk modeling. Crypto Market Researcher: Fundamental analysis, market trends, institutional adoption tracking, and regulatory landscape monitoring. Crypto Derivatives Trader: Futures and perpetuals analysis, options strategies, leverage management, and derivatives market intelligence. Crypto DEX Arbitrageur: Cross-exchange arbitrage identification, MEV strategy development, and automated profit extraction techniques. DeFi & Liquidity (4 agents) Crypto DeFi Strategist: Yield farming optimization, protocol analysis, liquidity provision strategies, and DeFi portfolio management. Crypto Liquidity Manager: Pool optimization, impermanent loss calculation and mitigation, market making strategies, and capital efficiency analysis. Crypto Governance Analyst: DAO structure evaluation, governance token analysis, proposal assessment, and voting mechanism research. Crypto Bridge Analyst: Cross-chain bridge security assessment, protocol comparison, interoperability solutions, and bridge risk evaluation. Security & Risk (3 agents) Crypto Security Researcher: Smart contract auditing, vulnerability detection, honeypot identification, and exploit pattern recognition. Crypto Security Engineer: Secure contract development practices, defensive programming patterns, and security implementation guidance. Crypto Risk Manager: Portfolio risk assessment, compliance monitoring, exposure analysis, and risk mitigation strategy development. On-Chain Analysis (3 agents) Crypto Wallet Detective: Blockchain forensics, wallet behavior analysis, transaction tracing, and entity identification across chains. Crypto On-chain Analyst: Transaction pattern analysis, wallet clustering, flow tracking, and on-chain metrics interpretation. Crypto MEV Researcher: MEV opportunity detection, flashloan arbitrage analysis, sandwich attack identification, and MEV protection strategies. Specialized Intelligence (3 agents) Crypto NFT Specialist: Collection valuation, rarity analysis, marketplace trends, and NFT ecosystem intelligence. Crypto Stablecoin Analyst: Peg stability monitoring, collateral analysis, depegging risk assessment, and stablecoin mechanism evaluation. Crypto Social Sentiment: Social media sentiment tracking, influencer monitoring, trending topic identification, and community analysis. Data Coverage: - 60+ blockchain networks - 2,000+ DeFi protocols - Real-time DEX data - CEX trading metrics - Social sentiment feeds - NFT marketplace data Compatibility: Works seamlessly with SuperClaude's existing agent framework. No configuration conflicts or manual routing needed. Practical Applications Smart Contract Development Security agents can audit contracts during development, identifying reentrancy risks, access control issues, and common vulnerabilities before deployment. DeFi Research Strategy agents query real-time pool data across networks, calculate yield-adjusted returns, and assess risks like impermanent loss or smart contract exposure. Trading Analysis Market agents access derivatives data, funding rates, liquidation levels, and order book depth across exchanges for informed trading decisions. Forensic Investigation On-chain agents trace fund flows, identify connected addresses, and analyze transaction patterns for security research or compliance work. Portfolio Management Risk agents evaluate protocol exposure, assess tail risks, and monitor positions across multiple chains and protocols. Why Specialized Agents Matter Generic AI models lack the domain-specific knowledge required for professional crypto work. A general-purpose AI might provide surface-level analysis of a smart contract, but a specialized security agent understands Solidity patterns, common exploits, and auditing methodologies. The agent framework solves this by routing tasks to specialists with deep domain knowledge: - A derivatives question goes to an agent trained on perpetuals, funding rates, and options greeks - A DeFi query reaches an agent that understands liquidity mathematics and protocol mechanics - A security audit is handled by an agent familiar with vulnerability patterns and exploit techniques This specialization produces more accurate, actionable insights than single-model approaches. Getting Started The agents are available now through npm. Requirements: - Node.js 16+ - Claude Code installed - No additional dependencies After installation, simply use Claude Code normally. When you ask crypto-related questions or request blockchain analysis, the appropriate agent is automatically invoked. The system handles routing, data retrieval, and response generation. Documentation covers individual agent capabilities, example queries, and integration patterns for different workflows. What This Enables With 17 specialized crypto agents, Claude Code becomes a comprehensive blockchain development and analysis environment: - Developers can audit contracts, optimize gas usage, and implement security patterns - Researchers can analyze protocols, compare yields, and assess risks - Traders can evaluate markets, identify opportunities, and manage positions - Security professionals can investigate exploits, trace funds, and assess vulnerabilities The agents provide access to blockchain data and specialized analysis that previously required multiple tools, APIs, and manual research. ghive.

Hive Intelligence

80,942 просмотров • 10 месяцев назад

PhD Students – How to easily understand a complex research topic? Meet Ponder – a tool for understanding complex research. 𝐇𝐨𝐰 𝐏𝐨𝐧𝐝𝐞𝐫 𝐰𝐨𝐫𝐤𝐬? 1. Go to and log in 2. Enter your research topic or research question 3. Ponder will start building a knowledge map 4. This knowledge map breaks down complex ideas into structured cards 𝐖𝐡𝐚𝐭 𝐜𝐚𝐧 𝐲𝐨𝐮 𝐝𝐨 𝐰𝐢𝐭𝐡 𝐭𝐡𝐞𝐬𝐞 𝐜𝐚𝐫𝐝𝐬? → You can add your own thoughts, questions, and insights. → Ask follow-up questions and deepen your exploration. → You can color the cards for better understanding → You can drag & organize them freely across the infinite canvas. 𝐇𝐨𝐰 𝐭𝐨 𝐚𝐝𝐝 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐩𝐚𝐩𝐞𝐫𝐬 𝐭𝐨 𝐭𝐡𝐞 𝐜𝐚𝐫𝐝𝐬? — You can search for relevant papers with built-in discovery. — Ponder will identify all relevant papers — You can then add or upload research papers — You can also attach papers to specific cards. 𝐀𝐟𝐭𝐞𝐫 𝐲𝐨𝐮𝐫 𝐩𝐨𝐧𝐝𝐞𝐫𝐢𝐧𝐠 𝐢𝐬 𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞𝐝: ➟ You can change the view to document, browser, or full screen. ➟ You can also download your knowledge map as a PDF ➟ You can ask further questions and refine with Ponder’s Agent. 𝐖𝐡𝐚𝐭 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐭𝐡𝐢𝐬 𝐰𝐚𝐲 𝐢𝐬 𝟏𝟎𝐱 𝐛𝐞𝐭𝐭𝐞𝐫? ↳ It brings discovery and analysis of research into one workspace ↳ It makes ideas branch and evolve naturally, just like your brain ↳ It helps you to easily identify research gaps ↳ It connects knowledge from all sources such as papers and web ↳ It enables you to export knowledge as maps, reports, or data. ↳ Designed for PhD students & researchers, who think deeply. Try Ponder here: Anything you'd like to add?
2:30

PhD Students – How to easily understand a complex research topic? Meet Ponder – a tool for understanding complex research. 𝐇𝐨𝐰 𝐏𝐨𝐧𝐝𝐞𝐫 𝐰𝐨𝐫𝐤𝐬? 1. Go to and log in 2. Enter your research topic or research question 3. Ponder will start building a knowledge map 4. This knowledge map breaks down complex ideas into structured cards 𝐖𝐡𝐚𝐭 𝐜𝐚𝐧 𝐲𝐨𝐮 𝐝𝐨 𝐰𝐢𝐭𝐡 𝐭𝐡𝐞𝐬𝐞 𝐜𝐚𝐫𝐝𝐬? → You can add your own thoughts, questions, and insights. → Ask follow-up questions and deepen your exploration. → You can color the cards for better understanding → You can drag & organize them freely across the infinite canvas. 𝐇𝐨𝐰 𝐭𝐨 𝐚𝐝𝐝 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐩𝐚𝐩𝐞𝐫𝐬 𝐭𝐨 𝐭𝐡𝐞 𝐜𝐚𝐫𝐝𝐬? — You can search for relevant papers with built-in discovery. — Ponder will identify all relevant papers — You can then add or upload research papers — You can also attach papers to specific cards. 𝐀𝐟𝐭𝐞𝐫 𝐲𝐨𝐮𝐫 𝐩𝐨𝐧𝐝𝐞𝐫𝐢𝐧𝐠 𝐢𝐬 𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞𝐝: ➟ You can change the view to document, browser, or full screen. ➟ You can also download your knowledge map as a PDF ➟ You can ask further questions and refine with Ponder’s Agent. 𝐖𝐡𝐚𝐭 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐭𝐡𝐢𝐬 𝐰𝐚𝐲 𝐢𝐬 𝟏𝟎𝐱 𝐛𝐞𝐭𝐭𝐞𝐫? ↳ It brings discovery and analysis of research into one workspace ↳ It makes ideas branch and evolve naturally, just like your brain ↳ It helps you to easily identify research gaps ↳ It connects knowledge from all sources such as papers and web ↳ It enables you to export knowledge as maps, reports, or data. ↳ Designed for PhD students & researchers, who think deeply. Try Ponder here: Anything you'd like to add?

Faheem Ullah

12,212 просмотров • 1 год назад

One tab. The whole market. That’s Eon. How many browser tabs do you have open right now just to keep up with the market? One for prices, one for news, one for charts, a whale tracker you check sometimes, that economic calendar you keep forgetting about... 😵‍💫 Eon brings all of it into one place. And it adds something none of those tabs have: an AI that actually reads the data for you and tells you what it means. Let’s take a quick look at what's inside 👀 Type something like "Is Bitcoin bullish or bearish right now?" and Eon answers properly - market phase, price action, trend, momentum, the full picture. You don't have to decode the charts yourself. The Explore section (our favorite part) 🎯 - Technical Analysis - pick a coin and an indicator like RSI, MACD or moving averages, and the AI reads the chart and tells you what it's saying - Fundamental Analysis - supply, top holder concentration, on-chain activity, active addresses - Whale Tracking - watch the big money move in real time, with live alerts the moment a whale sends funds to an exchange - Token Unlocks - see exactly when locked tokens are about to hit the market, before it catches you off guard - Event & Economic Calendars - airdrops, mainnet launches, Fed rate decisions, all on one timeline - Live News Feed - the whole market's headlines in one scroll Your home dashboard? Market cap, Bitcoin price, the Fear & Greed Index and the latest market updates, all there the second you log in 🏡 And the best bit? On every page there's a little box that says "ask about this analysis." Any time you're not sure what something means, you just ask, and you get a straight answer 💪 This is what crypto research looks like when it's finally in one place. Come see for yourself: 🙌
1:57

One tab. The whole market. That’s Eon. How many browser tabs do you have open right now just to keep up with the market? One for prices, one for news, one for charts, a whale tracker you check sometimes, that economic calendar you keep forgetting about... 😵‍💫 Eon brings all of it into one place. And it adds something none of those tabs have: an AI that actually reads the data for you and tells you what it means. Let’s take a quick look at what's inside 👀 Type something like "Is Bitcoin bullish or bearish right now?" and Eon answers properly - market phase, price action, trend, momentum, the full picture. You don't have to decode the charts yourself. The Explore section (our favorite part) 🎯 - Technical Analysis - pick a coin and an indicator like RSI, MACD or moving averages, and the AI reads the chart and tells you what it's saying - Fundamental Analysis - supply, top holder concentration, on-chain activity, active addresses - Whale Tracking - watch the big money move in real time, with live alerts the moment a whale sends funds to an exchange - Token Unlocks - see exactly when locked tokens are about to hit the market, before it catches you off guard - Event & Economic Calendars - airdrops, mainnet launches, Fed rate decisions, all on one timeline - Live News Feed - the whole market's headlines in one scroll Your home dashboard? Market cap, Bitcoin price, the Fear & Greed Index and the latest market updates, all there the second you log in 🏡 And the best bit? On every page there's a little box that says "ask about this analysis." Any time you're not sure what something means, you just ask, and you get a straight answer 💪 This is what crypto research looks like when it's finally in one place. Come see for yourself: 🙌

Ozak AI

17,333 просмотров • 3 месяцев назад

PREDICTION MARKET RESEARCH JUST GOT KILLED BY ONE .MD FILE. The .md file in the video plugs any AI agent into 1,800 live data sources -> Polymarket orderbooks, satellite imagery, vessel tracking, NOAA weather, SEC filings, sports lines, and the top 100 KOL wallets. It's pref.trade. No APIs, no scraping, no signup and no card. An agent with this installed doesn't ask "What's the price". It pulls the orderbook depth on Polymarket, cross-references vessel positions in the Strait of Hormuz, scans the latest SEC filings on the names mentioned, and watches what the top 100 KOL wallets did in the last 4 hours. Before it makes a single call. The numbers are insane: > $0 in API fees. > $0 in data subscriptions. > 670+ capabilities behind a single endpoint. Every datapoint with full provenance back to the source. The mechanism is wild too: It's called Preference. An MCP server that gives any AI agent structured access to prediction markets -> Polymarket, Kalshi, Hyperliquid, dFlow AND the real-world signals that price them. Your agent asks one question, gets the full picture before it acts. It goes way past Polymarket: Smart-money mirroring on the top 100 wallets in real time. Cross-venue arb scanners and event-driven agents that watch tanker traffic in the Strait of Hormuz and trade oil-linked markets. Backtesting pipelines over historical data plus the world signals that moved each market. The model was never the bottleneck. The data was. One agent, one .md file and Live world data on tap. -> Retail still has 12 CoinGecko tabs open. Agents already have the orderbook. Full info and guide at Don't forget to save.
0:34

PREDICTION MARKET RESEARCH JUST GOT KILLED BY ONE .MD FILE. The .md file in the video plugs any AI agent into 1,800 live data sources -> Polymarket orderbooks, satellite imagery, vessel tracking, NOAA weather, SEC filings, sports lines, and the top 100 KOL wallets. It's pref.trade. No APIs, no scraping, no signup and no card. An agent with this installed doesn't ask "What's the price". It pulls the orderbook depth on Polymarket, cross-references vessel positions in the Strait of Hormuz, scans the latest SEC filings on the names mentioned, and watches what the top 100 KOL wallets did in the last 4 hours. Before it makes a single call. The numbers are insane: > $0 in API fees. > $0 in data subscriptions. > 670+ capabilities behind a single endpoint. Every datapoint with full provenance back to the source. The mechanism is wild too: It's called Preference. An MCP server that gives any AI agent structured access to prediction markets -> Polymarket, Kalshi, Hyperliquid, dFlow AND the real-world signals that price them. Your agent asks one question, gets the full picture before it acts. It goes way past Polymarket: Smart-money mirroring on the top 100 wallets in real time. Cross-venue arb scanners and event-driven agents that watch tanker traffic in the Strait of Hormuz and trade oil-linked markets. Backtesting pipelines over historical data plus the world signals that moved each market. The model was never the bottleneck. The data was. One agent, one .md file and Live world data on tap. -> Retail still has 12 CoinGecko tabs open. Agents already have the orderbook. Full info and guide at Don't forget to save.

slash1s

61,850 просмотров • 3 месяцев назад

What It's Like Building a Proprietary Power Trading Firm with Cory Paddock Cory Paddock (Cory Paddock) has been trading the physical power grid since the early 2000s. He built his own firm from scratch in 2014 — trading his own capital — and has navigated every major paradigm shift in U.S. energy markets since coal dominated the grid. "It's the perfect amount of darkness. The information is public — but it's in the dark." We cover: - How Cory built a point of view on paradigm shifts before the market caught up - Why power trading sits at the intersection of economics & physics — and why that matters for edge - Why backtesting more than a few years of power data is basically useless — the grid isn't the same grid - LMP & locational marginal pricing: how physical grid constraints turn into alpha if you know where to look - The 5–10 trades that make your year — and why forcing setups in the lean periods kills you - How GBE stripped pay uncertainty out of trader comp so people can just focus on trading well - What it actually feels like watching your own money swing in real-time — and when it stops feeling that way Thanks so much Cory for coming on Odds on Open! Timestamps: 00:00 Intro 01:09 Starting GBE and finding trading edge 01:38 Overview of electricity markets and pricing 02:05 Power trading structure and deregulated markets 04:11 Research pipeline for market data analysis 04:56 Domain knowledge and renewable energy trading 06:39 LLMs and AI tools for quants 07:49 Grid data and intraday market signals 09:25 Finding alpha in electricity markets 10:13 Paradigm shifts and regime change insights 13:19 Coal to gas, wind, and solar trends 14:39 Data centers, EVs, and load growth 16:47 Recruiting talent in energy trading firms 17:38 Gen Z quants and algorithmic trading skills 21:55 Outliers, agency, and Gen Z traders 24:11 Culture and innovation in quant finance 27:29 Trading personal capital and risk management 28:06 PJM West Hub and market dynamics 32:19 Five-minute tick data and volatility 34:49 High-conviction trades and alpha generation 35:35 Incentive alignment and trader performance 36:42 Pay structure and removing stress capital 39:22 Motivation and purpose in trading careers 40:00 Passing knowledge to the next generation 42:04 Host reflections on electricity trading 42:14 Closing thoughts and sign-off
42:18

What It's Like Building a Proprietary Power Trading Firm with Cory Paddock Cory Paddock (Cory Paddock) has been trading the physical power grid since the early 2000s. He built his own firm from scratch in 2014 — trading his own capital — and has navigated every major paradigm shift in U.S. energy markets since coal dominated the grid. "It's the perfect amount of darkness. The information is public — but it's in the dark." We cover: - How Cory built a point of view on paradigm shifts before the market caught up - Why power trading sits at the intersection of economics & physics — and why that matters for edge - Why backtesting more than a few years of power data is basically useless — the grid isn't the same grid - LMP & locational marginal pricing: how physical grid constraints turn into alpha if you know where to look - The 5–10 trades that make your year — and why forcing setups in the lean periods kills you - How GBE stripped pay uncertainty out of trader comp so people can just focus on trading well - What it actually feels like watching your own money swing in real-time — and when it stops feeling that way Thanks so much Cory for coming on Odds on Open! Timestamps: 00:00 Intro 01:09 Starting GBE and finding trading edge 01:38 Overview of electricity markets and pricing 02:05 Power trading structure and deregulated markets 04:11 Research pipeline for market data analysis 04:56 Domain knowledge and renewable energy trading 06:39 LLMs and AI tools for quants 07:49 Grid data and intraday market signals 09:25 Finding alpha in electricity markets 10:13 Paradigm shifts and regime change insights 13:19 Coal to gas, wind, and solar trends 14:39 Data centers, EVs, and load growth 16:47 Recruiting talent in energy trading firms 17:38 Gen Z quants and algorithmic trading skills 21:55 Outliers, agency, and Gen Z traders 24:11 Culture and innovation in quant finance 27:29 Trading personal capital and risk management 28:06 PJM West Hub and market dynamics 32:19 Five-minute tick data and volatility 34:49 High-conviction trades and alpha generation 35:35 Incentive alignment and trader performance 36:42 Pay structure and removing stress capital 39:22 Motivation and purpose in trading careers 40:00 Passing knowledge to the next generation 42:04 Host reflections on electricity trading 42:14 Closing thoughts and sign-off

Ethan Kho

17,408 просмотров • 7 месяцев назад

🚀 Three Next-Gen AI & Web3 Projects Are Launching on Mindo AI A new chapter for community-powered intelligence, prediction markets, and open AI infrastructure The AI + Web3 landscape is entering a decisive phase — one where real usage, real revenue, and real ownership matter more than hype. Today, MindoAI is proud to welcome three groundbreaking projects that represent this shift clearly and powerfully: Perceptron Network Space DeepNode AI Each project tackles a different bottleneck in the AI economy — data, forecasting, and infrastructure — but they all share the same vision: decentralization, community ownership, and sustainable value creation. Let’s take a deeper look 👇 🧠 Perceptron Network The world’s first community-powered AI data engine Perceptron Network is redefining how AI data is sourced, validated, and delivered. Instead of relying on expensive, closed, and slow legacy data providers, Perceptron unlocks community-powered data pipelines that are: Faster Cheaper Revenue-generating from day one This isn’t experimental AI infrastructure — Perceptron already serves real clients with real revenue, proving that decentralized data engines can outperform traditional incumbents. Why Perceptron matters: AI models are only as good as their data Centralized data monopolies slow innovation Communities can produce higher-quality data at scale By aligning contributors, validators, and clients through incentives, Perceptron turns unused human and network potential into a living data engine for AI. Launching on Mindo AI gives Perceptron access to a broader AI-native community — accelerating adoption, partnerships, and ecosystem growth. 🌌 intodotspace The first 10× leveraged prediction market on Solana intodotspace is pushing the boundaries of on-chain prediction markets. Built by the $1.5B UFO team, this platform introduces: 10× leveraged predictions Ultra-fast execution on Solana Deep liquidity and composable market design The market’s confidence is already clear — the project completed a record-breaking raise that was oversubscribed by 1,360%. What makes intodotspace different: Leverage amplifies conviction, not noise On-chain transparency replaces opaque odds Markets become real-time intelligence engines Prediction markets are often called “truth machines.” intodotspace upgrades them into high-signal, high-efficiency forecasting layers — useful for traders, protocols, DAOs, and even AI systems that need probabilistic insights. Launching on positions intodotspace at the intersection of AI-driven decision-making and on-chain market intelligence. 🌐 DeepNode AI Infrastructure for open intelligence DeepNode AI is tackling one of the biggest problems in modern AI: centralized ownership. Today, AI is dominated by a handful of corporations. DeepNode flips that model by building open intelligence infrastructure where: Anyone can deploy AI models Builders earn directly from usage Intelligence is co-owned, not extracted Backed by leading validators, miners, and ecosystem builders, DeepNode transforms AI from a closed monopoly into a shared utility. DeepNode’s core philosophy: “Own what you build — or someone else will.” This is more than infrastructure. It’s an economic redesign of AI itself: Builders keep ownership Contributors share upside Networks replace platforms Launching on connects DeepNode to creators, researchers, and communities who believe intelligence should belong to everyone — not just Big Tech. 🤝 Why This Matters for With the launch of Perceptron Network, intodotspace, and DeepNode AI, #MindoAI is rapidly becoming: A hub for AI-native Web3 innovation A launchpad for real, revenue-backed projects A meeting point for data, markets, and intelligence infrastructure These three projects don’t compete — they complement each other: Perceptron supplies data intodotspace produces market intelligence DeepNode powers open AI execution Together, they form the backbone of a decentralized intelligence economy. 🔥 The future of AI is open, composable, and community-owned — and it’s launching now on Which of these projects are you most excited about? And how do you see decentralized intelligence reshaping the next AI cycle? 👇 Share your thoughts and join the conversation.
0:38

🚀 Three Next-Gen AI & Web3 Projects Are Launching on Mindo AI A new chapter for community-powered intelligence, prediction markets, and open AI infrastructure The AI + Web3 landscape is entering a decisive phase — one where real usage, real revenue, and real ownership matter more than hype. Today, MindoAI is proud to welcome three groundbreaking projects that represent this shift clearly and powerfully: Perceptron Network Space DeepNode AI Each project tackles a different bottleneck in the AI economy — data, forecasting, and infrastructure — but they all share the same vision: decentralization, community ownership, and sustainable value creation. Let’s take a deeper look 👇 🧠 Perceptron Network The world’s first community-powered AI data engine Perceptron Network is redefining how AI data is sourced, validated, and delivered. Instead of relying on expensive, closed, and slow legacy data providers, Perceptron unlocks community-powered data pipelines that are: Faster Cheaper Revenue-generating from day one This isn’t experimental AI infrastructure — Perceptron already serves real clients with real revenue, proving that decentralized data engines can outperform traditional incumbents. Why Perceptron matters: AI models are only as good as their data Centralized data monopolies slow innovation Communities can produce higher-quality data at scale By aligning contributors, validators, and clients through incentives, Perceptron turns unused human and network potential into a living data engine for AI. Launching on Mindo AI gives Perceptron access to a broader AI-native community — accelerating adoption, partnerships, and ecosystem growth. 🌌 intodotspace The first 10× leveraged prediction market on Solana intodotspace is pushing the boundaries of on-chain prediction markets. Built by the $1.5B UFO team, this platform introduces: 10× leveraged predictions Ultra-fast execution on Solana Deep liquidity and composable market design The market’s confidence is already clear — the project completed a record-breaking raise that was oversubscribed by 1,360%. What makes intodotspace different: Leverage amplifies conviction, not noise On-chain transparency replaces opaque odds Markets become real-time intelligence engines Prediction markets are often called “truth machines.” intodotspace upgrades them into high-signal, high-efficiency forecasting layers — useful for traders, protocols, DAOs, and even AI systems that need probabilistic insights. Launching on positions intodotspace at the intersection of AI-driven decision-making and on-chain market intelligence. 🌐 DeepNode AI Infrastructure for open intelligence DeepNode AI is tackling one of the biggest problems in modern AI: centralized ownership. Today, AI is dominated by a handful of corporations. DeepNode flips that model by building open intelligence infrastructure where: Anyone can deploy AI models Builders earn directly from usage Intelligence is co-owned, not extracted Backed by leading validators, miners, and ecosystem builders, DeepNode transforms AI from a closed monopoly into a shared utility. DeepNode’s core philosophy: “Own what you build — or someone else will.” This is more than infrastructure. It’s an economic redesign of AI itself: Builders keep ownership Contributors share upside Networks replace platforms Launching on connects DeepNode to creators, researchers, and communities who believe intelligence should belong to everyone — not just Big Tech. 🤝 Why This Matters for With the launch of Perceptron Network, intodotspace, and DeepNode AI, #MindoAI is rapidly becoming: A hub for AI-native Web3 innovation A launchpad for real, revenue-backed projects A meeting point for data, markets, and intelligence infrastructure These three projects don’t compete — they complement each other: Perceptron supplies data intodotspace produces market intelligence DeepNode powers open AI execution Together, they form the backbone of a decentralized intelligence economy. 🔥 The future of AI is open, composable, and community-owned — and it’s launching now on Which of these projects are you most excited about? And how do you see decentralized intelligence reshaping the next AI cycle? 👇 Share your thoughts and join the conversation.

Hồng Ngọc | Ruby💎

12,837 просмотров • 7 месяцев назад

Yesterday, I told you about a wall I'd been hitting for years. Today I get to break through it — with two announcements. 👇 𝟭. CreativAI is out of stealth — the SQL layer for Physical and Visual AI; also enabling visual intelligence to be verifiable, reliable, and cost-effective. 𝟮. We're launching a product that works today. Not a waitlist. Not a vision deck. Something you can try right now 👇 Whether you're an individual exploring AI, a developer building the next generation of applications, or an enterprise unlocking the value of visual data, CreativAI is ready for you. Deploy in the cloud, on-premises, or integrate through our APIs—whichever fits your workflow. Grateful to our CCO Waleed, our advisors Rob Ferguson and Abdul Jarrar, and to Google for Startups, AWS Startups, Microsoft for Startups, and NVIDIA for Startups Inception for the support. I've spent my career at the foundations of vision-language AI — research at KAUST, Stanford, Meta FAIR, and Adobe. I contributed to some of the building blocks the field now takes for granted: a linear version of CLIP (ICCV13; and the first vision LLMs — VisualGPT (CVPR22), MiniGPT-4(Arxiv'23, ICLR24). Somewhere along the way, the hardest problem in visual AI moved. Every kind of data got its breakthrough. Documents got search. Tabular data got SQL. Code got GitHub. Each one gave messy data a structure — something you could query, verify, and act on. Visual data never got that SQL like accessibility; the largest data type we produce — over 80% of internet traffic, a billion cameras and climbing. And there's a deeper limit. The models got remarkably good, but the events that matter most in your operation barely exist in pretraining data. A general model may have never seen them — so it can't recognize them in your world. That's what we built at Creativ AI. Point it at anything with a lens — cameras, robots, live streams, or years of archives. Our Data Plating technology turns raw pixels into structure the instant something happens: entities, events, behaviors. Not captions. Not metadata. The video itself, as rows and columns. Live streams as they happen, archives you've had for years —all of it becomes a knowledge base you can query. In plain language for your team. Through APIs for your agents. On-device for your robots, so they can close the loop and act inside your workflows. Every row points back to the moment it came from — so every result is traceable, verifiable, and safe to build on. One structured picture. One source of truth. Everyone reading from the same record. And this is where the pretraining gap closes: you teach it your domain — your events, your entities, the rare cases that matter. CreativAI learns what a general model never could, so the long tail of your world becomes queryable data like everything else
3:07

Yesterday, I told you about a wall I'd been hitting for years. Today I get to break through it — with two announcements. 👇 𝟭. CreativAI is out of stealth — the SQL layer for Physical and Visual AI; also enabling visual intelligence to be verifiable, reliable, and cost-effective. 𝟮. We're launching a product that works today. Not a waitlist. Not a vision deck. Something you can try right now 👇 Whether you're an individual exploring AI, a developer building the next generation of applications, or an enterprise unlocking the value of visual data, CreativAI is ready for you. Deploy in the cloud, on-premises, or integrate through our APIs—whichever fits your workflow. Grateful to our CCO Waleed, our advisors Rob Ferguson and Abdul Jarrar, and to Google for Startups, AWS Startups, Microsoft for Startups, and NVIDIA for Startups Inception for the support. I've spent my career at the foundations of vision-language AI — research at KAUST, Stanford, Meta FAIR, and Adobe. I contributed to some of the building blocks the field now takes for granted: a linear version of CLIP (ICCV13; and the first vision LLMs — VisualGPT (CVPR22), MiniGPT-4(Arxiv'23, ICLR24). Somewhere along the way, the hardest problem in visual AI moved. Every kind of data got its breakthrough. Documents got search. Tabular data got SQL. Code got GitHub. Each one gave messy data a structure — something you could query, verify, and act on. Visual data never got that SQL like accessibility; the largest data type we produce — over 80% of internet traffic, a billion cameras and climbing. And there's a deeper limit. The models got remarkably good, but the events that matter most in your operation barely exist in pretraining data. A general model may have never seen them — so it can't recognize them in your world. That's what we built at Creativ AI. Point it at anything with a lens — cameras, robots, live streams, or years of archives. Our Data Plating technology turns raw pixels into structure the instant something happens: entities, events, behaviors. Not captions. Not metadata. The video itself, as rows and columns. Live streams as they happen, archives you've had for years —all of it becomes a knowledge base you can query. In plain language for your team. Through APIs for your agents. On-device for your robots, so they can close the loop and act inside your workflows. Every row points back to the moment it came from — so every result is traceable, verifiable, and safe to build on. One structured picture. One source of truth. Everyone reading from the same record. And this is where the pretraining gap closes: you teach it your domain — your events, your entities, the rare cases that matter. CreativAI learns what a general model never could, so the long tail of your world becomes queryable data like everything else

Mohamed Elhoseiny

39,450 просмотров • 1 месяц назад

CLAUDE "SKILLS" BUILT ME AN AI AGENT ARMY in 33 minutes Claude Skills fix one of the biggest problems in AI.... context rot. when you overload a model with long prompts, scattered files, and inconsistent instructions, it BREAKS. Claude Skills solve that by packaging everything an AI needs into one structured workflow. each Claude Skill includes: 1. instructions that define the role and process 2. reference materials that capture brand voice, examples, and style 3. code scripts that handle data and make outputs deterministic together, they act like a trained employee...reliable, consistent, and specialized. instead of dumping chaos into a chatbot, you’re building a clear operating system for how work gets done. in this The Startup Ideas Podcast (SIP) 🧃 episode, we built an entire team of AI employees inside Claude using Claude Skills. each had a specific job and worked in sync: – one generated UTM links and tracked campaign performance automatically – one ran A/B test idea generation using real website data and the ICE framework – one analyzed marketing reports, pulling actual numbers from CSVs and surfacing insights – one turned viral tweets into newsletters that matched my tone and writing style perfectly we then layered in sub-agents basically smaller Claude instances that split large tasks into specialized roles and passed results back. the result is a new kind of reliability. you can automate marketing, content creation, analytics, and reporting without losing accuracy, consistency, or creativity. Claude Skills turn messy, repeatable work into clean, reusable systems that anyone can deploy. in this episode, we walk through the full build writing the instructions, linking sub-agents, connecting data, and watching them collaborate in real time. thanks to amirmxt for dropping this sauce. most people charge thousands to teach this kind of AI systems design. this one’s free. watch the full masterclass on The Startup Ideas Podcast (SIP) 🧃 below on X or YouTube ( . claude skills isn't perfect but it's a step in the right direction pretty cool many will bookmark this but never try it but the key is getting your hands dirty learn and lightbulb moments will hit IM ROOTING FOR YOU
33:05

CLAUDE "SKILLS" BUILT ME AN AI AGENT ARMY in 33 minutes Claude Skills fix one of the biggest problems in AI.... context rot. when you overload a model with long prompts, scattered files, and inconsistent instructions, it BREAKS. Claude Skills solve that by packaging everything an AI needs into one structured workflow. each Claude Skill includes: 1. instructions that define the role and process 2. reference materials that capture brand voice, examples, and style 3. code scripts that handle data and make outputs deterministic together, they act like a trained employee...reliable, consistent, and specialized. instead of dumping chaos into a chatbot, you’re building a clear operating system for how work gets done. in this The Startup Ideas Podcast (SIP) 🧃 episode, we built an entire team of AI employees inside Claude using Claude Skills. each had a specific job and worked in sync: – one generated UTM links and tracked campaign performance automatically – one ran A/B test idea generation using real website data and the ICE framework – one analyzed marketing reports, pulling actual numbers from CSVs and surfacing insights – one turned viral tweets into newsletters that matched my tone and writing style perfectly we then layered in sub-agents basically smaller Claude instances that split large tasks into specialized roles and passed results back. the result is a new kind of reliability. you can automate marketing, content creation, analytics, and reporting without losing accuracy, consistency, or creativity. Claude Skills turn messy, repeatable work into clean, reusable systems that anyone can deploy. in this episode, we walk through the full build writing the instructions, linking sub-agents, connecting data, and watching them collaborate in real time. thanks to amirmxt for dropping this sauce. most people charge thousands to teach this kind of AI systems design. this one’s free. watch the full masterclass on The Startup Ideas Podcast (SIP) 🧃 below on X or YouTube ( . claude skills isn't perfect but it's a step in the right direction pretty cool many will bookmark this but never try it but the key is getting your hands dirty learn and lightbulb moments will hit IM ROOTING FOR YOU

GREG ISENBERG

189,753 просмотров • 10 месяцев назад

OpenClaw setup made me $23,472 Literally overnight my $100 turned into $2,411 Average bot win rate 71% Copytrade: Here is the full strategy: The system builds automated workflows for trading by turning domain expertise into structured skills that activate automatically when specific market conditions appear Skill architecture Each skill is a modular package that includes instruction scripts and reference data This allows the system to apply specialized workflows without needing manual input for every trade Progressive context loading Skills use a three layer structure Only minimal metadata loads at first Full instructions historical data and supporting resources load only when required This reduces resource usage while keeping advanced trading capability Trigger detection Skills activate automatically when market conditions match predefined triggers such as volatility levels orderflow behavior or news sentiment This ensures the right workflow is used at the right time without manual action Workflow execution Once activated each skill runs a predefined multi step process including Real time price tracking and order book analysis Factor generation and backtesting Signal aggregation from machine learning models news sentiment and orderflow Risk assessment and capital allocation Trade execution with retries and position splitting Consistency and reliability All workflows are embedded directly into the system which ensures consistent execution instead of random decision making Every factor signal and risk rule is applied in a structured way Testing and iteration Skills are continuously improved using historical backtesting simulated trading and live performance tracking to maintain reliability in real market conditions Automation edge Instead of creating new strategies every time the system repeatedly uses optimized workflows This reduces complexity increases consistency and scales performance across thousands of trades Performance snapshot Started one month ago with $500 Current daily profit $2,300 per day Morning profit today $71,452 The system runs fully autonomously constantly scanning markets generating signals auditing trades managing risk and executing orders to maximize compounding returns
0:14

OpenClaw setup made me $23,472 Literally overnight my $100 turned into $2,411 Average bot win rate 71% Copytrade: Here is the full strategy: The system builds automated workflows for trading by turning domain expertise into structured skills that activate automatically when specific market conditions appear Skill architecture Each skill is a modular package that includes instruction scripts and reference data This allows the system to apply specialized workflows without needing manual input for every trade Progressive context loading Skills use a three layer structure Only minimal metadata loads at first Full instructions historical data and supporting resources load only when required This reduces resource usage while keeping advanced trading capability Trigger detection Skills activate automatically when market conditions match predefined triggers such as volatility levels orderflow behavior or news sentiment This ensures the right workflow is used at the right time without manual action Workflow execution Once activated each skill runs a predefined multi step process including Real time price tracking and order book analysis Factor generation and backtesting Signal aggregation from machine learning models news sentiment and orderflow Risk assessment and capital allocation Trade execution with retries and position splitting Consistency and reliability All workflows are embedded directly into the system which ensures consistent execution instead of random decision making Every factor signal and risk rule is applied in a structured way Testing and iteration Skills are continuously improved using historical backtesting simulated trading and live performance tracking to maintain reliability in real market conditions Automation edge Instead of creating new strategies every time the system repeatedly uses optimized workflows This reduces complexity increases consistency and scales performance across thousands of trades Performance snapshot Started one month ago with $500 Current daily profit $2,300 per day Morning profit today $71,452 The system runs fully autonomously constantly scanning markets generating signals auditing trades managing risk and executing orders to maximize compounding returns

winkle.

44,158 просмотров • 5 месяцев назад

Sundial has raised $23M to build the analytics platform for the AI era! Our work is personal to me (though many have asked: Why? Aren't you into intuition and taste and experience which is ultimately unmeasurable?) But hear me out: I love building, and I have a deep respect for it. Making something people love is one of the hardest and most humbling endeavors. The art comes down to making high-quality decisions, which comes from an obsession with the cliff’s edge between customer understanding and product capability. You need to know what’s working and what isn’t. That’s why data matters. Data is *information* about how reality works. At Sundial, we live by the mantra: diagnose with data; treat with design. What does masterful decision-making look like? It comes down to 3 things: 1. extreme alignment 2. shared curiosity to unpeel deeper and deeper layers of truth 3. urgent execution The very fact is that good intuition and taste comes from data internalized across many, many reps. Yes, reality is infinitely more complex than what can be measured. But measuring gives us a better grasp of reality. Alas, using data well is like learning a new language. It requires years of skill and context building. It's easy to misuse, whether misguidedly or intentionally. I know this all too well. Mastery requires everything from how to break down an ambiguous question, to fluently reading triangle charts and dense tables, to remembering the specific name of a specific column using a specific dialect of SQL. Too many people, like me, regularly feel frustrated by a) how long it takes to get answers b) how to draw the right interpretations c) how much noise I have to wade through to find actually actionable insights. Instead of greater confidence and quality, we get conflicting signals, cherry-picked facts, and analysis paralysis. Sundial is our attempt to solve those problems. We’re bottling up opinionated intelligence to guide decision-makers towards faster and more confident decisions. We envision a world where *everyone* can be their own expert analyst. Sundial uses AI and expert analytical techniques to make insights accessible to every decision-maker. Exemplary analysis takes the listener through a story. Data should speak the language of business, not the other way around. Sundial is also smart in the ways you’d expect of an AI-native tool. It’s not just about looking up data (“What’s India ARR last month?”), which has become table stakes; rather, Sundial can also tackle deep, complex analysis (”Why did ARR decline? What are my levers?”). In a crowded landscape of fragmented data tools—dashboards, notebooks, ETL systems—Sundial brings it all together into one intuitive platform. We believe this era of AI will see teams doing far more with less, and moving faster than ever before. Our mission is to build the data brain for the next generation of AI-powered companies. We're thrilled to be backed by dj patil at GPV—the first U.S. Chief Data Scientist and coiner of the term "data scientist”, alongside industry luminaries like Amjad Masad, tobi lutke, Fidji Simo, alex schultz 🏳️‍🌈, Shishir, Ruchi Sanghvi, Avichal Garg - Electric ϟ Capital, Drew Houston, Howie Liu and firms including Sequoia Capital, Tribe Capital, Sunflower Capital, Unusual Ventures. The best part of building Sundial is the people we get to work with. Funding announcements are nice and all, but what really fuels us is the feedback and growth trajectory of our customers. There’s nothing better than working on interesting problems with people you like. Onward! (P.S. We’re hiring for AI engineers, data engineers, and data scientists in the Bay Area -- DM me if you resonate with our mission, love dissecting big problems down into smaller ones, and appreciate the consistent practice of craft.)
0:20

Sundial has raised $23M to build the analytics platform for the AI era! Our work is personal to me (though many have asked: Why? Aren't you into intuition and taste and experience which is ultimately unmeasurable?) But hear me out: I love building, and I have a deep respect for it. Making something people love is one of the hardest and most humbling endeavors. The art comes down to making high-quality decisions, which comes from an obsession with the cliff’s edge between customer understanding and product capability. You need to know what’s working and what isn’t. That’s why data matters. Data is *information* about how reality works. At Sundial, we live by the mantra: diagnose with data; treat with design. What does masterful decision-making look like? It comes down to 3 things: 1. extreme alignment 2. shared curiosity to unpeel deeper and deeper layers of truth 3. urgent execution The very fact is that good intuition and taste comes from data internalized across many, many reps. Yes, reality is infinitely more complex than what can be measured. But measuring gives us a better grasp of reality. Alas, using data well is like learning a new language. It requires years of skill and context building. It's easy to misuse, whether misguidedly or intentionally. I know this all too well. Mastery requires everything from how to break down an ambiguous question, to fluently reading triangle charts and dense tables, to remembering the specific name of a specific column using a specific dialect of SQL. Too many people, like me, regularly feel frustrated by a) how long it takes to get answers b) how to draw the right interpretations c) how much noise I have to wade through to find actually actionable insights. Instead of greater confidence and quality, we get conflicting signals, cherry-picked facts, and analysis paralysis. Sundial is our attempt to solve those problems. We’re bottling up opinionated intelligence to guide decision-makers towards faster and more confident decisions. We envision a world where *everyone* can be their own expert analyst. Sundial uses AI and expert analytical techniques to make insights accessible to every decision-maker. Exemplary analysis takes the listener through a story. Data should speak the language of business, not the other way around. Sundial is also smart in the ways you’d expect of an AI-native tool. It’s not just about looking up data (“What’s India ARR last month?”), which has become table stakes; rather, Sundial can also tackle deep, complex analysis (”Why did ARR decline? What are my levers?”). In a crowded landscape of fragmented data tools—dashboards, notebooks, ETL systems—Sundial brings it all together into one intuitive platform. We believe this era of AI will see teams doing far more with less, and moving faster than ever before. Our mission is to build the data brain for the next generation of AI-powered companies. We're thrilled to be backed by dj patil at GPV—the first U.S. Chief Data Scientist and coiner of the term "data scientist”, alongside industry luminaries like Amjad Masad, tobi lutke, Fidji Simo, alex schultz 🏳️‍🌈, Shishir, Ruchi Sanghvi, Avichal Garg - Electric ϟ Capital, Drew Houston, Howie Liu and firms including Sequoia Capital, Tribe Capital, Sunflower Capital, Unusual Ventures. The best part of building Sundial is the people we get to work with. Funding announcements are nice and all, but what really fuels us is the feedback and growth trajectory of our customers. There’s nothing better than working on interesting problems with people you like. Onward! (P.S. We’re hiring for AI engineers, data engineers, and data scientists in the Bay Area -- DM me if you resonate with our mission, love dissecting big problems down into smaller ones, and appreciate the consistent practice of craft.)

Julie Zhuo

129,299 просмотров • 1 год назад

after reviewing 97 wave 3 submissions, these are my personal favorite demos. this is not a ranking, just the projects that impressed me the most because of their technical quality, execution, and attention to detail. every team that shipped deserves respect, building is never easy. 1. BasisDesk – A delta neutral basis trading platform that earns funding rates while reducing price risk. - what impressed me: every financial calculation uses fixed point arithmetic instead of floating point, making it one of the most accurate implementations I reviewed. - best for: traders looking for funding-rate opportunities with lower market risk. 2. SoNarr – turns crypto narratives into real onchain trades using SoSoValue data and SoDEX. - what impressed me: It showed three confirmed mainnet orders with careful checks before execution. - best for: analysts and index creators who want to automate narrative-based investing. 3. Helix – A news-to-signal platform that analyzes headlines and generates trading signals. - what impressed me: It includes a correlation heatmap to prove which signals actually worked instead of just making claims. - best for: traders who want transparent and evidence-based signals. 4. Conviction Matrix – scores crypto sectors using ETF flows, VC activity, and treasury data. - what impressed me: uses proper statistical methods like Wilson confidence intervals and verifies predictions over time. - best for: anyone who values measurable and data-driven signals. 5. Sonar – An AI hedge fund assistant that turns ETF flow data into trading ideas. - what impressed me: the builder openly fixed 34 issues found during an audit instead of hiding them. - best for: small funds and solo traders who value transparency. 6. SoSoMind – A complete AI trading terminal with research, execution, and portfolio tools. - what impressed me: It never shows fake data. If information isn't available, it simply says "unavailable." - best for: active onchain traders who want everything in one place. 7. MARA – An ai macro trading agent that records its reasoning onchain. - what impressed me: strong historical validation with a very rigorous performance evaluation. - best for: traders who want transparent and verifiable AI decisions. 8. SoSo Analyst – A protocol that lets analysts build an onchain reputation through verified predictions. - what impressed me: It showed one of the strongest end-to-end execution examples I reviewed. - best for: researchers and users who want to follow analysts with proven records. 9. Mosaic – builds crypto index portfolios from simple natural-language investment ideas. - what impressed me: the team found a major execution bug, fixed it, and added tests to prevent it from happening again. - best for: Investors who want easy thematic investing. 10. Prism – A quantitative index builder using a deterministic five-factor model. -what impressed me: AI is only used to understand the investment idea. Portfolio construction stays fully deterministic and reproducible. - best for: Index creators and quantitative researchers. These were my personal favorites after reviewing 97 submissions on SoSoValue there were many great projects that didn't make this list, and every builder deserves credit for shipping something. I'm excited to see which of these projects continue to grow after the buildathon. which demos impressed you the most? 👇
2:19

after reviewing 97 wave 3 submissions, these are my personal favorite demos. this is not a ranking, just the projects that impressed me the most because of their technical quality, execution, and attention to detail. every team that shipped deserves respect, building is never easy. 1. BasisDesk – A delta neutral basis trading platform that earns funding rates while reducing price risk. - what impressed me: every financial calculation uses fixed point arithmetic instead of floating point, making it one of the most accurate implementations I reviewed. - best for: traders looking for funding-rate opportunities with lower market risk. 2. SoNarr – turns crypto narratives into real onchain trades using SoSoValue data and SoDEX. - what impressed me: It showed three confirmed mainnet orders with careful checks before execution. - best for: analysts and index creators who want to automate narrative-based investing. 3. Helix – A news-to-signal platform that analyzes headlines and generates trading signals. - what impressed me: It includes a correlation heatmap to prove which signals actually worked instead of just making claims. - best for: traders who want transparent and evidence-based signals. 4. Conviction Matrix – scores crypto sectors using ETF flows, VC activity, and treasury data. - what impressed me: uses proper statistical methods like Wilson confidence intervals and verifies predictions over time. - best for: anyone who values measurable and data-driven signals. 5. Sonar – An AI hedge fund assistant that turns ETF flow data into trading ideas. - what impressed me: the builder openly fixed 34 issues found during an audit instead of hiding them. - best for: small funds and solo traders who value transparency. 6. SoSoMind – A complete AI trading terminal with research, execution, and portfolio tools. - what impressed me: It never shows fake data. If information isn't available, it simply says "unavailable." - best for: active onchain traders who want everything in one place. 7. MARA – An ai macro trading agent that records its reasoning onchain. - what impressed me: strong historical validation with a very rigorous performance evaluation. - best for: traders who want transparent and verifiable AI decisions. 8. SoSo Analyst – A protocol that lets analysts build an onchain reputation through verified predictions. - what impressed me: It showed one of the strongest end-to-end execution examples I reviewed. - best for: researchers and users who want to follow analysts with proven records. 9. Mosaic – builds crypto index portfolios from simple natural-language investment ideas. - what impressed me: the team found a major execution bug, fixed it, and added tests to prevent it from happening again. - best for: Investors who want easy thematic investing. 10. Prism – A quantitative index builder using a deterministic five-factor model. -what impressed me: AI is only used to understand the investment idea. Portfolio construction stays fully deterministic and reproducible. - best for: Index creators and quantitative researchers. These were my personal favorites after reviewing 97 submissions on SoSoValue there were many great projects that didn't make this list, and every builder deserves credit for shipping something. I'm excited to see which of these projects continue to grow after the buildathon. which demos impressed you the most? 👇

DAVIS (❖,❖)

42,756 просмотров • 1 месяц назад

We’re thrilled to share that Outset has raised $17M in Series A funding, led by 8VC to help companies better understand their customers. When michael hess and I founded Outset, we set out to solve a critical problem: truly understanding your customer is painfully slow, expensive, and at times, impossible. It shouldn’t be. We believed AI could change this by focusing on the human side of AI. So we built the world’s first AI-interviewer. An AI agent that asked questions, listened, and learned from real humans. By removing the barriers of traditional research and allowing companies to have deeper conversations with more customers more quickly, we could help teams infuse their products with genuine human understanding at a speed and scale previously impossible. So what was the moment we knew we were onto something? When WeightWatchers ran that first pilot back in early 2023. Participants shared incredible amounts of depth, all with the world’s first AI-interviewer. We got a call the next day from their head of research: "You built a thing. We want that thing. How do I pay you for it?" That validation has turned into explosive growth. We've doubled our revenue in just the last 4 months alone, with >50 enterprise customers like Nestlé, Microsoft, and WeightWatchers trusting us to unlock deeper customer insights. All of this built on the backs of a truly special early team with 0 employee turnover. This funding round was led by 8VC, with participation from an incredible group, including: Future Back Ventures by Bain & Company, Y Combinator / Garry Tan, Adverb Ventures /April Underwood / Jessica Verrilli ), Alt Capital / Jack Altman , Rebel Fund, Genius Ventures, Ritual Capital, and many more. So what's next? We're scaling our engineering and go-to-market teams to build the world's most powerful agentic customer research platform. All focused on one mission: helping companies better understand humans. To our customers, investors, and team - thank you for believing in this vision. Now check out the video to see Outset in action, testing the video itself with real people!
2:12

We’re thrilled to share that Outset has raised $17M in Series A funding, led by 8VC to help companies better understand their customers. When michael hess and I founded Outset, we set out to solve a critical problem: truly understanding your customer is painfully slow, expensive, and at times, impossible. It shouldn’t be. We believed AI could change this by focusing on the human side of AI. So we built the world’s first AI-interviewer. An AI agent that asked questions, listened, and learned from real humans. By removing the barriers of traditional research and allowing companies to have deeper conversations with more customers more quickly, we could help teams infuse their products with genuine human understanding at a speed and scale previously impossible. So what was the moment we knew we were onto something? When WeightWatchers ran that first pilot back in early 2023. Participants shared incredible amounts of depth, all with the world’s first AI-interviewer. We got a call the next day from their head of research: "You built a thing. We want that thing. How do I pay you for it?" That validation has turned into explosive growth. We've doubled our revenue in just the last 4 months alone, with >50 enterprise customers like Nestlé, Microsoft, and WeightWatchers trusting us to unlock deeper customer insights. All of this built on the backs of a truly special early team with 0 employee turnover. This funding round was led by 8VC, with participation from an incredible group, including: Future Back Ventures by Bain & Company, Y Combinator / Garry Tan, Adverb Ventures /April Underwood / Jessica Verrilli ), Alt Capital / Jack Altman , Rebel Fund, Genius Ventures, Ritual Capital, and many more. So what's next? We're scaling our engineering and go-to-market teams to build the world's most powerful agentic customer research platform. All focused on one mission: helping companies better understand humans. To our customers, investors, and team - thank you for believing in this vision. Now check out the video to see Outset in action, testing the video itself with real people!

Aaron Cannon

34,386 просмотров • 1 год назад

What a year. 🚀 2025 was the year ChainOpera AI turned vision into real momentum: building a community-co-created, community-co-owned AI agent network and pushing the boundaries of what decentralized, collaborative intelligence can look like. 🚀 Biggest highlights from 2025 ✅- AI Terminal officially launched: We unveiled the ChainOpera AI Terminal as a unified gateway to decentralized AI, making it possible for anyone to interact with powerful, decentralized LLMs without technical friction. Positioned as the “browser for the DeAI era,” the AI Terminal marked a major step toward making decentralized intelligence accessible, usable, and mainstream. ✅- AI Terminal adoption at massive scale: Momentum followed quickly. The AI Terminal surpassed 2M registered users and consistently ranked top 3 among all apps on the BNB AI DappBay, validating strong product–market fit and real, sustained usage at scale. ✅- Announcing Coco: the world’s first community-owned Super Agent: We introduced Coco, the intelligence layer that sits between users and the agent network. Coco dynamically routes each request to the most efficient, community-built agent—optimizing for quality and speed while rewarding the creators behind the best-performing agents. This was a defining moment in realizing a truly community-owned intelligence layer. ✅- From agents to a living agent network: With the launch of the Agent Social Network and Super Agent architecture, ChainOpera AI moved beyond isolated agents toward a collaborative system where humans and specialized agents coordinate, share context, and solve complex, multi-step tasks together. ✅- $COAI breakout year: The listing of $COAI across major exchanges shocked the market, and throughout the year COAI consistently remained among the top AI-native crypto tokens by visibility, activity, and community engagement – reflecting growing confidence in the long-term vision of collaborative intelligence. ✅- Global presence: ChainOpera AI around-the-world tour: ChainOpera AI went global in 2025, sponsoring and participating in major AI and Web3 events across North America, Europe, and Asia, including ETHDenver, Consensus Toronto, Token2049 Singapore, ETHCC, SBC, and Devcon. These global touchpoints helped us engage directly with developers, builders, investors, and partners worldwide, accelerating adoption and positioning ChainOpera AI at the center of the emerging AIxBlockchain movement. ✅- Community momentum at scale: Community remained the heart of ChainOpera AI’s growth. We successfully completed three seasons of structured community engagement, executed a widely participated community airdrop, and ran multiple ecosystem-shaping campaigns to incentivize builders, creators, and early adopters. These efforts strengthened alignment between users, developers, and the protocol, laying the foundation for a durable, community-owned AI ecosystem. ✅- “AI for Markets” taking shape: We laid critical groundwork for AI-native market intelligence, including the launch of PrediMarket Agent and multiple trading and analysis agents—early building blocks toward an AI-driven ecosystem for crypto and DeFi markets. ✅- Building in public, with the community: Across product launches, research milestones, ecosystem discussions, and global events, we continued to build openly to bring developers, users, and partners directly into the evolution of ChainOpera AI. This year also marked the launch of the ChainOpera AI Foundation website, formally kicking off a bold Ecosystem Fund designed to empower builders, incubate high-impact projects, and accelerate the growth of a truly community-owned, collaborative AI ecosystem. To every builder, user, and supporter who helped make this year possible: THANK YOU! 🧭 What we’re excited about in the coming year 🔹- A Stronger, Denser Agent Economy (everyday adoption + cross-chain reach): In 2026, we are scaling the Agent Economy from growth to daily usage, with more agents, richer workflows, deeper multi-agent collaboration, and higher-impact use cases that users rely on every day. In parallel, we are expanding the agent network beyond a single ecosystem with cross-chain execution and interoperability, allowing agents to access the best liquidity, data, and opportunities wherever they exist. 🔹- AI Market Infrastructure Evolution: Building on PrediMarket Agent and our growing suite of trading and market-intelligence agents, we are advancing toward a mature AI market infrastructure, where agents continuously monitor, reason, simulate, optimize, and act across crypto, DeFi, and beyond. The goal is to make complex markets more accessible, more transparent, and more intelligence-driven, turning research, decision-making, and execution into a fast and reliable loop for everyday users. 🔹- Ecosystem Acceleration through the Foundation: With the ChainOpera AI Foundation and our Ecosystem Fund and Co-Creation Grants, we are doubling down on empowering independent builders to expand the protocol, the agent network, and the underlying infrastructure, so the community can co-create, co-own, and scale the ecosystem together. 🔹- Business Expansion and Market Penetration: In 2026, we will focus on expanding ChainOpera’s reach through strategic partnerships, product-led growth, and new paths to monetization, bringing AI agents to a broader global user base and driving sustained adoption, engagement, and revenue, while staying aligned with community ownership and an open ecosystem. 2025 was the proof. 2026 is where it compounds. 🔥 Co-Create. Co-Own. COAI.
0:22

What a year. 🚀 2025 was the year ChainOpera AI turned vision into real momentum: building a community-co-created, community-co-owned AI agent network and pushing the boundaries of what decentralized, collaborative intelligence can look like. 🚀 Biggest highlights from 2025 ✅- AI Terminal officially launched: We unveiled the ChainOpera AI Terminal as a unified gateway to decentralized AI, making it possible for anyone to interact with powerful, decentralized LLMs without technical friction. Positioned as the “browser for the DeAI era,” the AI Terminal marked a major step toward making decentralized intelligence accessible, usable, and mainstream. ✅- AI Terminal adoption at massive scale: Momentum followed quickly. The AI Terminal surpassed 2M registered users and consistently ranked top 3 among all apps on the BNB AI DappBay, validating strong product–market fit and real, sustained usage at scale. ✅- Announcing Coco: the world’s first community-owned Super Agent: We introduced Coco, the intelligence layer that sits between users and the agent network. Coco dynamically routes each request to the most efficient, community-built agent—optimizing for quality and speed while rewarding the creators behind the best-performing agents. This was a defining moment in realizing a truly community-owned intelligence layer. ✅- From agents to a living agent network: With the launch of the Agent Social Network and Super Agent architecture, ChainOpera AI moved beyond isolated agents toward a collaborative system where humans and specialized agents coordinate, share context, and solve complex, multi-step tasks together. ✅- $COAI breakout year: The listing of $COAI across major exchanges shocked the market, and throughout the year COAI consistently remained among the top AI-native crypto tokens by visibility, activity, and community engagement – reflecting growing confidence in the long-term vision of collaborative intelligence. ✅- Global presence: ChainOpera AI around-the-world tour: ChainOpera AI went global in 2025, sponsoring and participating in major AI and Web3 events across North America, Europe, and Asia, including ETHDenver, Consensus Toronto, Token2049 Singapore, ETHCC, SBC, and Devcon. These global touchpoints helped us engage directly with developers, builders, investors, and partners worldwide, accelerating adoption and positioning ChainOpera AI at the center of the emerging AIxBlockchain movement. ✅- Community momentum at scale: Community remained the heart of ChainOpera AI’s growth. We successfully completed three seasons of structured community engagement, executed a widely participated community airdrop, and ran multiple ecosystem-shaping campaigns to incentivize builders, creators, and early adopters. These efforts strengthened alignment between users, developers, and the protocol, laying the foundation for a durable, community-owned AI ecosystem. ✅- “AI for Markets” taking shape: We laid critical groundwork for AI-native market intelligence, including the launch of PrediMarket Agent and multiple trading and analysis agents—early building blocks toward an AI-driven ecosystem for crypto and DeFi markets. ✅- Building in public, with the community: Across product launches, research milestones, ecosystem discussions, and global events, we continued to build openly to bring developers, users, and partners directly into the evolution of ChainOpera AI. This year also marked the launch of the ChainOpera AI Foundation website, formally kicking off a bold Ecosystem Fund designed to empower builders, incubate high-impact projects, and accelerate the growth of a truly community-owned, collaborative AI ecosystem. To every builder, user, and supporter who helped make this year possible: THANK YOU! 🧭 What we’re excited about in the coming year 🔹- A Stronger, Denser Agent Economy (everyday adoption + cross-chain reach): In 2026, we are scaling the Agent Economy from growth to daily usage, with more agents, richer workflows, deeper multi-agent collaboration, and higher-impact use cases that users rely on every day. In parallel, we are expanding the agent network beyond a single ecosystem with cross-chain execution and interoperability, allowing agents to access the best liquidity, data, and opportunities wherever they exist. 🔹- AI Market Infrastructure Evolution: Building on PrediMarket Agent and our growing suite of trading and market-intelligence agents, we are advancing toward a mature AI market infrastructure, where agents continuously monitor, reason, simulate, optimize, and act across crypto, DeFi, and beyond. The goal is to make complex markets more accessible, more transparent, and more intelligence-driven, turning research, decision-making, and execution into a fast and reliable loop for everyday users. 🔹- Ecosystem Acceleration through the Foundation: With the ChainOpera AI Foundation and our Ecosystem Fund and Co-Creation Grants, we are doubling down on empowering independent builders to expand the protocol, the agent network, and the underlying infrastructure, so the community can co-create, co-own, and scale the ecosystem together. 🔹- Business Expansion and Market Penetration: In 2026, we will focus on expanding ChainOpera’s reach through strategic partnerships, product-led growth, and new paths to monetization, bringing AI agents to a broader global user base and driving sustained adoption, engagement, and revenue, while staying aligned with community ownership and an open ecosystem. 2025 was the proof. 2026 is where it compounds. 🔥 Co-Create. Co-Own. COAI.

ChainOpera AI

17,113 просмотров • 8 месяцев назад

Announcing the DVM Terminal Presale! 01/ We are excited to formally announce the next step in our journey: our AI and Signal based trading Terminal. See ALL details on our website, including product, tech, deposit address, and tech documentation: Deposit Address (SOL only): 4pyVRFX56MdqtREcxWnf6XuEGfRNCQaKm1LA4xmHeccv By contributing, you agree to our Terms & Privacy Policy – full docs on site. 02/ We are building ‘DVM Terminal’, a signal and AI powered trading platform for the Solana trenches (initially). The first multi-agent AI trading terminal designed as an institutional-grade dashboard – turning market noise into actionable alpha with agent summaries, live signals, rigid filters, and a full multi-agent system. 03/ The problem. Trench hunting is far too inefficient with real data and insights lacking. - Dashboards are noisy (not even sortable), - No AI agents (in an AI world) - No narratives (a critical component to a thesis), - VERY limited signals (only DB/DS), - No advanced trading (no TP, SL, or VWAP), - No portfolio alert/management system post-trade etc. - The list goes on… Products from major competitors are all just homogeneous, even down to the 3-frame design. We have to piece everything together like broken lego blocks, building a weak matrix from existing platforms, X, FNFs, telegram and discord for little to no alpha. 04/ The solution & moat. We rebuild this from the ground up, leveraging signals and AI. - Clean institutional-like dashboards (we can sort and navigate thru a proper terminal, like Bloomberg or Messari) - AI agents (thank goodness for intelligence, distilling all the important info upfront across 2k+ tokens/day) - A Narrative engine (no need to ask “what is this token about?”; additionally, our engine can identify the newest metas like AI, ICM, Cards, etc.) - 100s of value-add Signals overlaid live on charts (momentum, smart money, sentiment, event data; all of it; tell us what’s happening in real-time) - Advanced trading system (finally, SL, TP, VWAP etc.) - Live portfolio monitoring (AI will give us pertinent live info on our holdings, so we can go live life and not look at screens all day) - All in one place. At a higher-level, our advantage will be managing the massive on/off-chain data pipeline being processed by thousands or millions of context-aware AI agents that recognize patterns, filter noise and deliver only the most actionable insights to a trader with which it can execute a trade effectively. 05/ The opportunity. The Industry leader on Solana makes $600m+ in fees annually, with total industry near $1b on Solana alone, according to Adam. Yet, the entire industry gives us total burnout, fragmented data, either little info or info overload, no real signals, no narratives, no personalized AI-driven strategies, and zero incentives (like buybacks or a flywheel). We’ll flip the script, designing a high-powered scalable signal and AI driven intelligence platform with a flywheel (50-100% fee buy-back & burn). Simply put, we want to be tops. 06/ Development. Our product is MVP. We are building this to scale beyond Solana, into multi-chain. V1 is expected in 4-6 weeks. Our approach to building is an open feedback loop with community members, building to the demands of our users. 07/ Pre-sale terms & Valuation. We are offering 50% public sale, with min $100, no max. Ending valuation is susceptible to change based on amount raised, but will be fixed at 2x raise - i.e. $1m raised=$2m val, $50m raised=$100m val. We are seeking to raise $25m on a $50m valuation, which represents 1% of Solana bot market-share. At TGE event, expect ~65% of our tokens to be floating (or outstanding), with 25% in treasury and 10% of the team allocation locked. Tokens are expected to be distributed just ahead of v1 rollout. Again, find more details on our webpage. 08/ Tailwinds. AI input costs are declining 90%/yr also, so the operational model could become very accretive over time, as we scale our tech to other chains. Solana outputs the most tokens (~35k per day), so we start here, where the challenge is the greatest. 09/ Advisors. Big thanks to our advisors, who’ve been part of this community since inception. Austin Barack, JK 🛡️, cryptic, Tachi, , ZoeyLoo and Chetan Badhe. 10/ The end. Thank you for your consideration; and make sure the SOL address posted here is the same as on our website.
0:52

Announcing the DVM Terminal Presale! 01/ We are excited to formally announce the next step in our journey: our AI and Signal based trading Terminal. See ALL details on our website, including product, tech, deposit address, and tech documentation: Deposit Address (SOL only): 4pyVRFX56MdqtREcxWnf6XuEGfRNCQaKm1LA4xmHeccv By contributing, you agree to our Terms & Privacy Policy – full docs on site. 02/ We are building ‘DVM Terminal’, a signal and AI powered trading platform for the Solana trenches (initially). The first multi-agent AI trading terminal designed as an institutional-grade dashboard – turning market noise into actionable alpha with agent summaries, live signals, rigid filters, and a full multi-agent system. 03/ The problem. Trench hunting is far too inefficient with real data and insights lacking. - Dashboards are noisy (not even sortable), - No AI agents (in an AI world) - No narratives (a critical component to a thesis), - VERY limited signals (only DB/DS), - No advanced trading (no TP, SL, or VWAP), - No portfolio alert/management system post-trade etc. - The list goes on… Products from major competitors are all just homogeneous, even down to the 3-frame design. We have to piece everything together like broken lego blocks, building a weak matrix from existing platforms, X, FNFs, telegram and discord for little to no alpha. 04/ The solution & moat. We rebuild this from the ground up, leveraging signals and AI. - Clean institutional-like dashboards (we can sort and navigate thru a proper terminal, like Bloomberg or Messari) - AI agents (thank goodness for intelligence, distilling all the important info upfront across 2k+ tokens/day) - A Narrative engine (no need to ask “what is this token about?”; additionally, our engine can identify the newest metas like AI, ICM, Cards, etc.) - 100s of value-add Signals overlaid live on charts (momentum, smart money, sentiment, event data; all of it; tell us what’s happening in real-time) - Advanced trading system (finally, SL, TP, VWAP etc.) - Live portfolio monitoring (AI will give us pertinent live info on our holdings, so we can go live life and not look at screens all day) - All in one place. At a higher-level, our advantage will be managing the massive on/off-chain data pipeline being processed by thousands or millions of context-aware AI agents that recognize patterns, filter noise and deliver only the most actionable insights to a trader with which it can execute a trade effectively. 05/ The opportunity. The Industry leader on Solana makes $600m+ in fees annually, with total industry near $1b on Solana alone, according to Adam. Yet, the entire industry gives us total burnout, fragmented data, either little info or info overload, no real signals, no narratives, no personalized AI-driven strategies, and zero incentives (like buybacks or a flywheel). We’ll flip the script, designing a high-powered scalable signal and AI driven intelligence platform with a flywheel (50-100% fee buy-back & burn). Simply put, we want to be tops. 06/ Development. Our product is MVP. We are building this to scale beyond Solana, into multi-chain. V1 is expected in 4-6 weeks. Our approach to building is an open feedback loop with community members, building to the demands of our users. 07/ Pre-sale terms & Valuation. We are offering 50% public sale, with min $100, no max. Ending valuation is susceptible to change based on amount raised, but will be fixed at 2x raise - i.e. $1m raised=$2m val, $50m raised=$100m val. We are seeking to raise $25m on a $50m valuation, which represents 1% of Solana bot market-share. At TGE event, expect ~65% of our tokens to be floating (or outstanding), with 25% in treasury and 10% of the team allocation locked. Tokens are expected to be distributed just ahead of v1 rollout. Again, find more details on our webpage. 08/ Tailwinds. AI input costs are declining 90%/yr also, so the operational model could become very accretive over time, as we scale our tech to other chains. Solana outputs the most tokens (~35k per day), so we start here, where the challenge is the greatest. 09/ Advisors. Big thanks to our advisors, who’ve been part of this community since inception. Austin Barack, JK 🛡️, cryptic, Tachi, , ZoeyLoo and Chetan Badhe. 10/ The end. Thank you for your consideration; and make sure the SOL address posted here is the same as on our website.

Deep Value Memetics

23,075 просмотров • 10 месяцев назад

/HEYAURA_INITIALIZING ████████████ 100% heyAura beta is now live! Welcome the first public version of the AI assistant that makes crypto easy. heyAura gives users a better way to work with their wallet. Even in this early version, it can analyze a portfolio, compare positions, surface yield opportunities, stress-test exposure, and prepare transactions for swaps, bridges, and trades. It is built to cut down the amount of research, interpretation, and manual execution that still slows down too much of the Web3 experience. heyAura is still a beta of a broader direction we have been building toward. More will follow around prompting, automation, deeper research, and the wider assistant experience. That progress matters only if control stays with the user. heyAura is built to support user-approved actions, not to make decisions on the user’s behalf. Early access to the beta starts through staking 300 $ADX and unlocks unlimited access to heyAura. We are opening this version gradually so the product can be shaped through real usage and direct feedback. heyAura is here today thanks to the right infrastructure and strong collaborations behind it. ambire.eth is the official wallet partner for heyAura's launch. This partnership brought our product closer to the wallet layer, where context, permissions, and user-approved actions actually matter. Billions Network supports the identity layer behind where the product is going, as heyAura moves toward agentic workflows, identity and trust. LI.FI brings routing for swaps and bridges into the execution flow. That gives heyAura a stronger way to support cross-chain actions and multi-step transaction paths. Barter strengthens the quote and routing layer behind transaction quality, allowing heyAura to compare routes more effectively. vaults.fyi powers the yield layer. One API gives heyAura live APY data and ready-to-sign transactions across 90+ protocols on 23+ chains, so Aura can execute yield opportunities without integrating each protocol itself. SKALE supports the chain layer behind faster and lower-friction interactions. That becomes more useful as heyAura grows more interactive. PayAI Network | x402 Facilitator is heyAura’s facilitator for payment verification and settlement. We also want to thank the numerous communities that have supported us up to this point. Your improved Web3 experience lies ahead. Stake $ADX and try heyAura now.
0:53

/HEYAURA_INITIALIZING ████████████ 100% heyAura beta is now live! Welcome the first public version of the AI assistant that makes crypto easy. heyAura gives users a better way to work with their wallet. Even in this early version, it can analyze a portfolio, compare positions, surface yield opportunities, stress-test exposure, and prepare transactions for swaps, bridges, and trades. It is built to cut down the amount of research, interpretation, and manual execution that still slows down too much of the Web3 experience. heyAura is still a beta of a broader direction we have been building toward. More will follow around prompting, automation, deeper research, and the wider assistant experience. That progress matters only if control stays with the user. heyAura is built to support user-approved actions, not to make decisions on the user’s behalf. Early access to the beta starts through staking 300 $ADX and unlocks unlimited access to heyAura. We are opening this version gradually so the product can be shaped through real usage and direct feedback. heyAura is here today thanks to the right infrastructure and strong collaborations behind it. ambire.eth is the official wallet partner for heyAura's launch. This partnership brought our product closer to the wallet layer, where context, permissions, and user-approved actions actually matter. Billions Network supports the identity layer behind where the product is going, as heyAura moves toward agentic workflows, identity and trust. LI.FI brings routing for swaps and bridges into the execution flow. That gives heyAura a stronger way to support cross-chain actions and multi-step transaction paths. Barter strengthens the quote and routing layer behind transaction quality, allowing heyAura to compare routes more effectively. vaults.fyi powers the yield layer. One API gives heyAura live APY data and ready-to-sign transactions across 90+ protocols on 23+ chains, so Aura can execute yield opportunities without integrating each protocol itself. SKALE supports the chain layer behind faster and lower-friction interactions. That becomes more useful as heyAura grows more interactive. PayAI Network | x402 Facilitator is heyAura’s facilitator for payment verification and settlement. We also want to thank the numerous communities that have supported us up to this point. Your improved Web3 experience lies ahead. Stake $ADX and try heyAura now.

heyAura

129,068 просмотров • 3 месяцев назад

🚨 I think I just found one of the smartest AI Agents for real-world investing. No prompt engineering. No complicated workflows. Just pick an expert and start chatting. I tested it on one of the hottest AI semiconductor stocks right now: Micron ($MU). Here’s all I did: → Opened EasyClaw → Added the Stock Master Agent → Installed the Serenity skill → Typed ONE sentence: “Use Serenity’s framework to research $MU and give me an investment recommendation.” A few minutes later, I had a research report that looked like something from a professional analyst. It automatically covered: ✅ Market outlook ✅ Supply chain trends ✅ Fundamental analysis ✅ Technical analysis ✅ Valuation ✅ Risk assessment ✅ Clear investment recommendation The result? Surprisingly… it said DON’T chase $MU at current prices. Why? • AI-driven HBM demand is still exploding 📈 • Micron’s fundamentals remain incredibly strong 📈 • Memory market sentiment is bullish 📈 But… The stock has run much faster than the business has improved. Its recommendations were refreshingly practical: 📌 Already holding? → Consider scaling out gradually and protect gains with trailing stops. 📌 Waiting to buy? → Stay patient. Let the market come to you. 📌 Risk-averse investor? → Skip the volatility until a better setup appears. What impressed me most wasn’t the conclusion… It was how the AI reached it. It highlighted the 3 metrics that actually matter going forward: 1️⃣ DRAM & HBM pricing trends 2️⃣ HBM4 production ramp for next-gen AI chips 3️⃣ CapEx plans from major memory manufacturers That’s the kind of analysis that separates signal from noise. The entire workflow felt like watching a veteran analyst think in real time: Hot trend → Data → Industry insights → Risk analysis → Decision. No prompts. No setup. No building AI agents from scratch. Just choose an expert. Ask your question. Get a structured investment report in minutes. If you’re into AI, semiconductors, or US stocks, this is absolutely worth trying. Learn More Here :- #AIAgent #StockMarket #Micron #MU #Investing #Semiconductors #HBM #Claude #EasyClaw #AIInvesting
0:31

🚨 I think I just found one of the smartest AI Agents for real-world investing. No prompt engineering. No complicated workflows. Just pick an expert and start chatting. I tested it on one of the hottest AI semiconductor stocks right now: Micron ($MU). Here’s all I did: → Opened EasyClaw → Added the Stock Master Agent → Installed the Serenity skill → Typed ONE sentence: “Use Serenity’s framework to research $MU and give me an investment recommendation.” A few minutes later, I had a research report that looked like something from a professional analyst. It automatically covered: ✅ Market outlook ✅ Supply chain trends ✅ Fundamental analysis ✅ Technical analysis ✅ Valuation ✅ Risk assessment ✅ Clear investment recommendation The result? Surprisingly… it said DON’T chase $MU at current prices. Why? • AI-driven HBM demand is still exploding 📈 • Micron’s fundamentals remain incredibly strong 📈 • Memory market sentiment is bullish 📈 But… The stock has run much faster than the business has improved. Its recommendations were refreshingly practical: 📌 Already holding? → Consider scaling out gradually and protect gains with trailing stops. 📌 Waiting to buy? → Stay patient. Let the market come to you. 📌 Risk-averse investor? → Skip the volatility until a better setup appears. What impressed me most wasn’t the conclusion… It was how the AI reached it. It highlighted the 3 metrics that actually matter going forward: 1️⃣ DRAM & HBM pricing trends 2️⃣ HBM4 production ramp for next-gen AI chips 3️⃣ CapEx plans from major memory manufacturers That’s the kind of analysis that separates signal from noise. The entire workflow felt like watching a veteran analyst think in real time: Hot trend → Data → Industry insights → Risk analysis → Decision. No prompts. No setup. No building AI agents from scratch. Just choose an expert. Ask your question. Get a structured investment report in minutes. If you’re into AI, semiconductors, or US stocks, this is absolutely worth trying. Learn More Here :- #AIAgent #StockMarket #Micron #MU #Investing #Semiconductors #HBM #Claude #EasyClaw #AIInvesting

Marry Evan

17,629 просмотров • 2 месяцев назад

The last 20 Moni Wizards NFTs. WL Application is live. The Wizards collection is the highest access to everything Moni. Apply to get whitelisted: 20 seats left. After these, primary closes for good and the only way in is the secondary market. Funds from this sale go straight back into the build: more research, more Smarts coverage, more API surface, more community infrastructure. What’s inside? Full Moni platform access. The off-chain side of our stack and how you find alpha before it's alpha. Discover tracks where smart money is already looking: VCs, founders, alpha hunters, and influencers, in real time. You see the projects they're moving toward one to three weeks before they trend on the main timeline. Behind it: 15,000 hand-curated Smarts and millions of smart mentions collected over five years. Wizards get every filter, every list, every signal we expose internally. Daily and weekly Alpha Reports. Written by the Moni Research team, not aggregated from elsewhere. Our analysts hand-pick the best of what the engine surfaces each day and each week, then write up what the Smarts are watching, why it matters, and where the narrative is forming. Reports usually land in the Wizards Discord before any public version exists. Moni Social API. New for Wizards. The same API we give access to launchpads, exchanges, VCs, and analytical platforms. 30+ data types, 100,000+ tracked events per day, 5,000+ projects under coverage, Smart Mindshare endpoints, real-time and historical social signals. Think of it as the social intelligence layer you'd otherwise have to build yourself. Wizards get a data they can plug into their own tools, alert systems, or agents. Deep Research. One project at a time, long form, the same work we run inside Moni Research. Each one takes the team about a week. Thesis, ecosystem map, mechanism, risks, Smart positioning, what to watch for. Structured the way an analyst would actually use it, not a Twitter thread version of it. Private Wizards-only chats and community. The room where the 180 holders and the private Moni community already share early calls, deal flow, research drafts, and "look at this" moments before anything goes public. Most of the real work happens here, not in the Twitter version of Moni. Alpha bots and curated Smarts lists. The bots that track Smart movements in real time. The Twitter lists we don't share publicly because they are the actual edge. Wizards get both. Early access to every new Moni product. Whatever ships next, Wizards see it first. Sometimes the prototype, sometimes weeks before public release. The feedback loop runs straight back into the team. Partnership raffles and early-stage deal flow. Pre-seed and seed allocations from partner projects. Raffles, intros, primary access to things that come through the table and never leave it. Custom hand-drawn PFP. Designed by our artist around your call. Yours forever. How to buy. Fill the form. The team reads every answer. If your fit makes sense for what this circle is, we'll come back to you with everything you need to complete the purchase. Moni Wizards Opensea Page:
0:45

The last 20 Moni Wizards NFTs. WL Application is live. The Wizards collection is the highest access to everything Moni. Apply to get whitelisted: 20 seats left. After these, primary closes for good and the only way in is the secondary market. Funds from this sale go straight back into the build: more research, more Smarts coverage, more API surface, more community infrastructure. What’s inside? Full Moni platform access. The off-chain side of our stack and how you find alpha before it's alpha. Discover tracks where smart money is already looking: VCs, founders, alpha hunters, and influencers, in real time. You see the projects they're moving toward one to three weeks before they trend on the main timeline. Behind it: 15,000 hand-curated Smarts and millions of smart mentions collected over five years. Wizards get every filter, every list, every signal we expose internally. Daily and weekly Alpha Reports. Written by the Moni Research team, not aggregated from elsewhere. Our analysts hand-pick the best of what the engine surfaces each day and each week, then write up what the Smarts are watching, why it matters, and where the narrative is forming. Reports usually land in the Wizards Discord before any public version exists. Moni Social API. New for Wizards. The same API we give access to launchpads, exchanges, VCs, and analytical platforms. 30+ data types, 100,000+ tracked events per day, 5,000+ projects under coverage, Smart Mindshare endpoints, real-time and historical social signals. Think of it as the social intelligence layer you'd otherwise have to build yourself. Wizards get a data they can plug into their own tools, alert systems, or agents. Deep Research. One project at a time, long form, the same work we run inside Moni Research. Each one takes the team about a week. Thesis, ecosystem map, mechanism, risks, Smart positioning, what to watch for. Structured the way an analyst would actually use it, not a Twitter thread version of it. Private Wizards-only chats and community. The room where the 180 holders and the private Moni community already share early calls, deal flow, research drafts, and "look at this" moments before anything goes public. Most of the real work happens here, not in the Twitter version of Moni. Alpha bots and curated Smarts lists. The bots that track Smart movements in real time. The Twitter lists we don't share publicly because they are the actual edge. Wizards get both. Early access to every new Moni product. Whatever ships next, Wizards see it first. Sometimes the prototype, sometimes weeks before public release. The feedback loop runs straight back into the team. Partnership raffles and early-stage deal flow. Pre-seed and seed allocations from partner projects. Raffles, intros, primary access to things that come through the table and never leave it. Custom hand-drawn PFP. Designed by our artist around your call. Yours forever. How to buy. Fill the form. The team reads every answer. If your fit makes sense for what this circle is, we'll come back to you with everything you need to complete the purchase. Moni Wizards Opensea Page:

Moni 🧙‍♂️

50,196 просмотров • 3 месяцев назад

| $SGT Latest Update is LIVE! At we're dedicated to building an all-in-one DeFi ecosystem that covers everything from the hottest crypto trends and breaking news to top performers and in-depth analysis of call groups and influencer signals. Our latest update is designed to enhance your user experience, making it easier to navigate through our utilities and access critical insights. Here’s What’s New: 🔍 Search Bar: for tokens mentioned on our platform by name or contract hash, streamlining your access to key data. 📊 Token Profile Pages: with essential metrics such as Market Cap, Volume, Price, and Performance Charts. A detailed table at the bottom shows which influencers mentioned the token and how it performed afterward. 📈 Top 5 Visited Tokens: Check out the most viewed tokens on our platform. This new table highlights the tokens generating the most user interest, helping you stay ahead of the trends. 💻 Telegram App & Bots: With our focus on Telegram, we've added dedicated pages for our app and bots, making it easier to explore their features and utilities as we continue to expand our offerings. ⚡️ UI & Speed Enhancements: The platform has been optimized for a faster, smoother experience, with an improved user interface for better navigation. 📺 Watch the full tutorial: Join our community for more news and updates! 🌐 Visit us at :
3:51

| $SGT Latest Update is LIVE! At we're dedicated to building an all-in-one DeFi ecosystem that covers everything from the hottest crypto trends and breaking news to top performers and in-depth analysis of call groups and influencer signals. Our latest update is designed to enhance your user experience, making it easier to navigate through our utilities and access critical insights. Here’s What’s New: 🔍 Search Bar: for tokens mentioned on our platform by name or contract hash, streamlining your access to key data. 📊 Token Profile Pages: with essential metrics such as Market Cap, Volume, Price, and Performance Charts. A detailed table at the bottom shows which influencers mentioned the token and how it performed afterward. 📈 Top 5 Visited Tokens: Check out the most viewed tokens on our platform. This new table highlights the tokens generating the most user interest, helping you stay ahead of the trends. 💻 Telegram App & Bots: With our focus on Telegram, we've added dedicated pages for our app and bots, making it easier to explore their features and utilities as we continue to expand our offerings. ⚡️ UI & Speed Enhancements: The platform has been optimized for a faster, smoother experience, with an improved user interface for better navigation. 📺 Watch the full tutorial: Join our community for more news and updates! 🌐 Visit us at :

ShillGuard $SGT

16,239 просмотров • 1 год назад