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Builder credibility is still mostly self-reported. A resume, portfolio, or post can say what someone shipped, but a grant committee, DAO, or hiring manager still has to investigate the GitHub trail. Admon turns a builder's public GitHub activity into a verifiable record bound to their wallet on Monad. Connect...

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Mojeeb | Arcapush.com

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12,514 просмотров • 2 месяцев назад •via X (Twitter)

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Recap Quiz for Episode #1 with Monad We talked about why Monad was created and who created it, exploring Monad from the basics. Monad was founded by three founders to build a fast L1 capable of real-time trading. Instead of taking the easy route with rollups or shortcuts, they refined their own technology over a long period to launch their mainnet. Additionally, they pursue competition to help the ecosystem grow in natural and leverage their strong industry network to support project funding, using it to benefit ecosystem partners. 📂 And now for the quiz: On July 12th, the 7th Monad OOOOO Hackathon will be held in Korea. What is the name of this hackathon? Thx sungmo & Monad

Wecryptotogether (Theo/acc)

20,319 просмотров • 1 год назад

Hacktron founder s1r1us argues OpenAI is running a “Manhattan Project” on Slack and GitHub, giving it the same basic attack surface as any startup: "Every repository is running on github .com/openai. It's the same thing that Hacktron uses or any other company uses." "We have friends at OpenAI who are much more capable than what we could do. But what I can say is, why is it running on Slack? Why are you running this Manhattan Project from Slack? Why are you hosting your repositories on github? That looks silly to me." "Your attack surface becomes Slack. You can hack a Slack employee and go through that and get into OpenAI. You can hack GitHub, go through that and get into OpenAI." "My claim is it shouldn't be running on B2B SaaS if you are building Manhattan Projects. That's all I'm saying. I can think of numerous ways on how to get into that." Hacktron AI Harsh Jaiswal
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Hacktron founder s1r1us argues OpenAI is running a “Manhattan Project” on Slack and GitHub, giving it the same basic attack surface as any startup: "Every repository is running on github .com/openai. It's the same thing that Hacktron uses or any other company uses." "We have friends at OpenAI who are much more capable than what we could do. But what I can say is, why is it running on Slack? Why are you running this Manhattan Project from Slack? Why are you hosting your repositories on github? That looks silly to me." "Your attack surface becomes Slack. You can hack a Slack employee and go through that and get into OpenAI. You can hack GitHub, go through that and get into OpenAI." "My claim is it shouldn't be running on B2B SaaS if you are building Manhattan Projects. That's all I'm saying. I can think of numerous ways on how to get into that." Hacktron AI Harsh Jaiswal

MTS

158,535 просмотров • 2 дней назад

Everyone trading memecoins needs this tool right now i made over $7k in 3 days trading shitcoins with it WARDEN - the terminal that reads the token and the github standing behind it > snipers already know lp lock, mint, and holder concentration. that's the cheap way not to catch a classic rug. they almost never check whether the repo is actually real an account could sit dead for years and wake up on ticker day. forks could land in a burst that's the whole trick. it runs on your machine. it never touches a key until you pass --live what it does with a launch before you've even opened the chart: - reads it off the chain: curve, lp, mint/blacklist, how much the deployer bought for themselves, how the holders sit. if it couldn't fetch holders it writes null, not "zero concentration" - fingerprints the github: account age vs the first living repo, a fork burst in a tight window, ticker in the readme. a raw 0x in protocol docs is a weak signal. TICKER is not - it will not invent a green light out of a hole. if github is silent, or github itself locked the list, it says so. missing is not a pass pons v2 and four-meme on the read side. every rule that decides a buy sits in the repo in plain text. link in the first reply tell me which check you'd drop first. i want to argue about it
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Everyone trading memecoins needs this tool right now i made over $7k in 3 days trading shitcoins with it WARDEN - the terminal that reads the token and the github standing behind it > snipers already know lp lock, mint, and holder concentration. that's the cheap way not to catch a classic rug. they almost never check whether the repo is actually real an account could sit dead for years and wake up on ticker day. forks could land in a burst that's the whole trick. it runs on your machine. it never touches a key until you pass --live what it does with a launch before you've even opened the chart: - reads it off the chain: curve, lp, mint/blacklist, how much the deployer bought for themselves, how the holders sit. if it couldn't fetch holders it writes null, not "zero concentration" - fingerprints the github: account age vs the first living repo, a fork burst in a tight window, ticker in the readme. a raw 0x in protocol docs is a weak signal. TICKER is not - it will not invent a green light out of a hole. if github is silent, or github itself locked the list, it says so. missing is not a pass pons v2 and four-meme on the read side. every rule that decides a buy sits in the repo in plain text. link in the first reply tell me which check you'd drop first. i want to argue about it

Archive

17,168 просмотров • 14 дней назад

✨Public Sale – Exo Incubators! A Blink Planet x ExoSpirits Spin-off Collection! Site: 😺1111 Incubators granting access to: • A platform to redeem physical items! • 1 ExoSpirits airdrop on Monad! 🚨The ExoSpirits total supply will be 6666, with: 🧢1111 reserved for Exo Incubators holders • 5555 available for minting on Monad Mainnet! 🌍Exo Incubators is a collection created to solidify the partnership between ExoSpirits and BlinkPlanet and to kickstart the global distribution and branding of the ExoSpirits universe! 🔥PUMP IT! 🔥 ➡️RT + LIKE + Drop your EVM Wallet (10 wallets will be selected to receive 10 USDT)
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✨Public Sale – Exo Incubators! A Blink Planet x ExoSpirits Spin-off Collection! Site: 😺1111 Incubators granting access to: • A platform to redeem physical items! • 1 ExoSpirits airdrop on Monad! 🚨The ExoSpirits total supply will be 6666, with: 🧢1111 reserved for Exo Incubators holders • 5555 available for minting on Monad Mainnet! 🌍Exo Incubators is a collection created to solidify the partnership between ExoSpirits and BlinkPlanet and to kickstart the global distribution and branding of the ExoSpirits universe! 🔥PUMP IT! 🔥 ➡️RT + LIKE + Drop your EVM Wallet (10 wallets will be selected to receive 10 USDT)

ExoSpirits

10,995 просмотров • 1 год назад

Anthropic engineer (ex-Google): "I spent 14 years at Google and built 24 reusable skills for agents that I can use with any AI model So I stopped prompting my agents from scratch. The repo has already reached ~100K stars on GitHub" In a 40-min masterclass, Addy Osmani showed exactly how he uses his skills (~100K stars on GitHub) for his 24/7 multi-agent system His workflow and this workshop will replace 15 hours of other paid videos on agent engineering Watch it today, copy the GitHub repo - then read below how to use these skills for graphs ↓
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Anthropic engineer (ex-Google): "I spent 14 years at Google and built 24 reusable skills for agents that I can use with any AI model So I stopped prompting my agents from scratch. The repo has already reached ~100K stars on GitHub" In a 40-min masterclass, Addy Osmani showed exactly how he uses his skills (~100K stars on GitHub) for his 24/7 multi-agent system His workflow and this workshop will replace 15 hours of other paid videos on agent engineering Watch it today, copy the GitHub repo - then read below how to use these skills for graphs ↓

codila

185,058 просмотров • 7 дней назад

5 free GitHub bots for trading on Polymarket… 5 different strategies for 5 different trading situations. Each of these tools comes with a detailed step by step setup and usage guide in English: 1. This bot can automatically manage your limit orders to maximize liquidity rewards (useful for liquidity providers on Polymarket). GitHub: 2. The bot, which analyzes the real behavior of any Polymarket trader, finds repeated patterns in his trades, explains which strategies he uses and how you can actually adapt them to your own trading. GitHub: 3. A bot with 118+ ready to use strategies and tools for prediction markets, including Smart Money, Binance-Polymarket latency, Mean Reversion and more… The most interesting one is Polymarket - Kalshi Cross Arbitrage - it finds differences in prices between platforms and can manage trades automatically. GitHub: 4. A Chinese weather bot that analyzes multiple sources in real time, like forecasts, public airport data and aviation observations (METAR + SPECI) and then generates a detailed weather report for a specific city and day. GitHub: 5. This is a bot-toolkit that includes copy trading, arbitrage, market making, spread farming, whale alerts, sports trading and more… GitHub: Almost every tool here has a DRY RUN mode, so you can test them on real markets, but with fake funds.
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5 free GitHub bots for trading on Polymarket… 5 different strategies for 5 different trading situations. Each of these tools comes with a detailed step by step setup and usage guide in English: 1. This bot can automatically manage your limit orders to maximize liquidity rewards (useful for liquidity providers on Polymarket). GitHub: 2. The bot, which analyzes the real behavior of any Polymarket trader, finds repeated patterns in his trades, explains which strategies he uses and how you can actually adapt them to your own trading. GitHub: 3. A bot with 118+ ready to use strategies and tools for prediction markets, including Smart Money, Binance-Polymarket latency, Mean Reversion and more… The most interesting one is Polymarket - Kalshi Cross Arbitrage - it finds differences in prices between platforms and can manage trades automatically. GitHub: 4. A Chinese weather bot that analyzes multiple sources in real time, like forecasts, public airport data and aviation observations (METAR + SPECI) and then generates a detailed weather report for a specific city and day. GitHub: 5. This is a bot-toolkit that includes copy trading, arbitrage, market making, spread farming, whale alerts, sports trading and more… GitHub: Almost every tool here has a DRY RUN mode, so you can test them on real markets, but with fake funds.

Recogard

14,162 просмотров • 3 месяцев назад

NØNOS Microkernel, track the release commits Live. We’ve begun pushing commits to the public GitHub, marking the release of the NØNOS microkernel. This is the beginning. Piece by piece, the vision becomes reality. Built with patience, purpose and love for what we’re creating. Every day is a lesson, a chance to refine, to grow and to push the boundaries of what’s possible. Building isn’t easy, but it’s awesome if done with purpose, ours is: transparent, verifiable and shared with the world. We hope this journey inspires collaboration. Every contribution, review and following tests brings us closer to a computing foundation owned by everyone, by the people. This release marks the beginning of the next phase: OS components, tests, closer to the real systems, closer to real freedom.
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NØNOS Microkernel, track the release commits Live. We’ve begun pushing commits to the public GitHub, marking the release of the NØNOS microkernel. This is the beginning. Piece by piece, the vision becomes reality. Built with patience, purpose and love for what we’re creating. Every day is a lesson, a chance to refine, to grow and to push the boundaries of what’s possible. Building isn’t easy, but it’s awesome if done with purpose, ours is: transparent, verifiable and shared with the world. We hope this journey inspires collaboration. Every contribution, review and following tests brings us closer to a computing foundation owned by everyone, by the people. This release marks the beginning of the next phase: OS components, tests, closer to the real systems, closer to real freedom.

NØNOS

42,095 просмотров • 11 месяцев назад

My last open-source skill, /no-ai-slop, clearly hit a nerve with 4K GitHub stars. Today, I’m introducing /human-review, another free AI skill I think you’ll love. Let’s face it - giving feedback to AI in chat is painful. Asking it to “update the 3rd paragraph” or “update image size to X” is annoying when I just want to edit the text myself or give feedback to AI directly on the page. /human-review opens HTML and Markdown files in a visual editor that lets you: → Edit and format text directly → Resize images → Leave comments for AI like a Google Doc I've been using it to edit PRDs, landing pages, product copy, and much more. The whole review loop runs locally, so your data is safe and nothing is uploaded to the cloud. 📌 Get /human-review for free on GitHub: If you find it useful, please ⭐ the repo so more people can find it. 📌 Read my full post here for more on how I use /human-review:
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My last open-source skill, /no-ai-slop, clearly hit a nerve with 4K GitHub stars. Today, I’m introducing /human-review, another free AI skill I think you’ll love. Let’s face it - giving feedback to AI in chat is painful. Asking it to “update the 3rd paragraph” or “update image size to X” is annoying when I just want to edit the text myself or give feedback to AI directly on the page. /human-review opens HTML and Markdown files in a visual editor that lets you: → Edit and format text directly → Resize images → Leave comments for AI like a Google Doc I've been using it to edit PRDs, landing pages, product copy, and much more. The whole review loop runs locally, so your data is safe and nothing is uploaded to the cloud. 📌 Get /human-review for free on GitHub: If you find it useful, please ⭐ the repo so more people can find it. 📌 Read my full post here for more on how I use /human-review:

Peter Yang

316,335 просмотров • 1 месяц назад

I built an entire RAG application without writing any code. This is one of the easiest ways to start building AI applications. I used Langflow. It's open-source. It's a visual interface for building and deploying AI applications. I built a couple of workflows to show you how it works, and I'm impressed! Check the video I recorded. I built two workflows: 1. The first one loads data into a vector store database (Astra DB). 2. The second asks questions from that data using OpenAI's models. Langchain does the heavy lifting behind the scenes, but having a visual interface makes this 10 times easier. Here is Langflow's GitHub repository: In the video, I used their pre-release version. The development experience for building AI applications is improving tremendously! What a time to be a builder!
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I built an entire RAG application without writing any code. This is one of the easiest ways to start building AI applications. I used Langflow. It's open-source. It's a visual interface for building and deploying AI applications. I built a couple of workflows to show you how it works, and I'm impressed! Check the video I recorded. I built two workflows: 1. The first one loads data into a vector store database (Astra DB). 2. The second asks questions from that data using OpenAI's models. Langchain does the heavy lifting behind the scenes, but having a visual interface makes this 10 times easier. Here is Langflow's GitHub repository: In the video, I used their pre-release version. The development experience for building AI applications is improving tremendously! What a time to be a builder!

Santiago

263,136 просмотров • 2 лет назад

GitHub stars are a vanity metric. I wanted to know who's actually building — so I built Sentrion: a Bloomberg Terminal for software builders. Here's how it works; It ingests GitHub's full public activity firehose — 2.2M builders, 62,000+ notable repos — and scores everyone on real momentum + influence, refreshed daily. No manual lists. Then the part I'm proud of: an AI reads each top builder's actual work — repos, languages, trajectory — and grades them on a fixed rubric. Every score ships with the reasoning. No black box. Anti-BS built in: 0 stars + 0 followers + 1 repo can't rank high. A famous-but-quiet maintainer can't rank low. Bots get flagged and graded ~18. The real ones rise to 96. It also writes a daily intelligence brief — what's breaking out, what's quietly important, and what's star-farmed garbage. The AI calls it out. Soon..
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GitHub stars are a vanity metric. I wanted to know who's actually building — so I built Sentrion: a Bloomberg Terminal for software builders. Here's how it works; It ingests GitHub's full public activity firehose — 2.2M builders, 62,000+ notable repos — and scores everyone on real momentum + influence, refreshed daily. No manual lists. Then the part I'm proud of: an AI reads each top builder's actual work — repos, languages, trajectory — and grades them on a fixed rubric. Every score ships with the reasoning. No black box. Anti-BS built in: 0 stars + 0 followers + 1 repo can't rank high. A famous-but-quiet maintainer can't rank low. Bots get flagged and graded ~18. The real ones rise to 96. It also writes a daily intelligence brief — what's breaking out, what's quietly important, and what's star-farmed garbage. The AI calls it out. Soon..

cetto

28,341 просмотров • 3 месяцев назад

Introducing Dune: a context-aware keypad for Mac that adapts to what you’re doing. Dune reads which app is in the foreground and automatically changes what its three keys do based on what you’re working on. One tap to join meetings without searching for links. Approve and merge PRs on GitHub. Approve or reject on Claude. Or trigger your own Agentic workflows. All from a single key press. Choose what Dune does from a set of pre-built workflow triggers or build your own. We are shipping a limited batch of Dune and would love to see what you build with it.
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Introducing Dune: a context-aware keypad for Mac that adapts to what you’re doing. Dune reads which app is in the foreground and automatically changes what its three keys do based on what you’re working on. One tap to join meetings without searching for links. Approve and merge PRs on GitHub. Approve or reject on Claude. Or trigger your own Agentic workflows. All from a single key press. Choose what Dune does from a set of pre-built workflow triggers or build your own. We are shipping a limited batch of Dune and would love to see what you build with it.

Apoorv Shankar

304,962 просмотров • 5 месяцев назад

🚀 GeoLibre just passed 5,000 stars on GitHub, in only two months! GeoLibre went public on May 27, and the community has already pushed it past 5,100 stars and 500+ forks. Thank you to everyone who starred, forked, filed issues, opened pull requests, and shared the project. For those just discovering it: GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. Key features of GeoLibre: - Runs anywhere: the same app ships as a native desktop app, a browser web app, a native Android app, and a Jupyter widget. - Local and private by default: load and analyze GeoJSON, GeoParquet, GeoPackage, Shapefile, COG, LiDAR, 3D Tiles, and more, right in the browser. - Powered by open source: built on MapLibre GL JS, DuckDB-WASM Spatial, Tauri, React, and TypeScript. - Spatial SQL in the browser: query your data with DuckDB Spatial, PostGIS via PGlite, and Apache Sedona. - Extensible: a growing plugin system for cloud data, federal web services, and custom tools. - Supports 12 planetary basemaps: Earth, Mars, the Moon, Mercury, Venus, and more. Two months in, we have already shipped 25 releases, the latest being v2.4.0. There is a lot more to come, and the best way to shape it is to jump in. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: If GeoLibre is useful to you, a star on GitHub and a share here go a long way. Thank you for an incredible first two months. #geospatial #opensource #MapLibre #GeoLibre
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🚀 GeoLibre just passed 5,000 stars on GitHub, in only two months! GeoLibre went public on May 27, and the community has already pushed it past 5,100 stars and 500+ forks. Thank you to everyone who starred, forked, filed issues, opened pull requests, and shared the project. For those just discovering it: GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. Key features of GeoLibre: - Runs anywhere: the same app ships as a native desktop app, a browser web app, a native Android app, and a Jupyter widget. - Local and private by default: load and analyze GeoJSON, GeoParquet, GeoPackage, Shapefile, COG, LiDAR, 3D Tiles, and more, right in the browser. - Powered by open source: built on MapLibre GL JS, DuckDB-WASM Spatial, Tauri, React, and TypeScript. - Spatial SQL in the browser: query your data with DuckDB Spatial, PostGIS via PGlite, and Apache Sedona. - Extensible: a growing plugin system for cloud data, federal web services, and custom tools. - Supports 12 planetary basemaps: Earth, Mars, the Moon, Mercury, Venus, and more. Two months in, we have already shipped 25 releases, the latest being v2.4.0. There is a lot more to come, and the best way to shape it is to jump in. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: If GeoLibre is useful to you, a star on GitHub and a share here go a long way. Thank you for an incredible first two months. #geospatial #opensource #MapLibre #GeoLibre

Qiusheng Wu

94,705 просмотров • 1 месяц назад

Here is an open-source tool to generate a complete dataset. 1. Describe the data you want 2. An orchestrator agent searches the web 3. Sub-agents run in parallel to fetch the data 4. You get a structured dataset you can download For example, you can run Bigset with the query "all leica lenses being sold on amazon", or "leica stores in kyoto with their opening hours and ratings". Bigset uses TinyFish's free Search and Fetch APIs in the background. You can configure it to refresh the data on a schedule. You can self-host it with your own keys. Here is the GitHub repository: You can get free TinyFish API keys here: Thanks to the TinyFish team for partnering with me on this post.
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Here is an open-source tool to generate a complete dataset. 1. Describe the data you want 2. An orchestrator agent searches the web 3. Sub-agents run in parallel to fetch the data 4. You get a structured dataset you can download For example, you can run Bigset with the query "all leica lenses being sold on amazon", or "leica stores in kyoto with their opening hours and ratings". Bigset uses TinyFish's free Search and Fetch APIs in the background. You can configure it to refresh the data on a schedule. You can self-host it with your own keys. Here is the GitHub repository: You can get free TinyFish API keys here: Thanks to the TinyFish team for partnering with me on this post.

Santiago

20,877 просмотров • 3 месяцев назад

I USED GPT-6 ASTRA TO TURN 1 FLY INTO A 7-PART ROCKET FACTORY the goal was simple: 1 fly studies every part, fits it, verifies it, then keeps building until the rocket is complete. part → study → neural state → fit gate → assembly → verify I called it buildfly. Astra helped me turn the idea into a working bay with 7 rocket parts, 3 live systems, a build log, neural activity map, and tolerance checks. the weird part is that the rocket is not even the main experiment. the real system is the neural loop deciding what happens next without skipping verification. I put the full build into a public GitHub repo so anyone can run it, break it, or make it even stranger. repo in the comments. bookmark this.
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I USED GPT-6 ASTRA TO TURN 1 FLY INTO A 7-PART ROCKET FACTORY the goal was simple: 1 fly studies every part, fits it, verifies it, then keeps building until the rocket is complete. part → study → neural state → fit gate → assembly → verify I called it buildfly. Astra helped me turn the idea into a working bay with 7 rocket parts, 3 live systems, a build log, neural activity map, and tolerance checks. the weird part is that the rocket is not even the main experiment. the real system is the neural loop deciding what happens next without skipping verification. I put the full build into a public GitHub repo so anyone can run it, break it, or make it even stranger. repo in the comments. bookmark this.

Gipp 🦅

49,931 просмотров • 8 дней назад

I pointed Grok Bot at one article about overnight bots and gave it $200 plus a kill line: earn or the process dies Grok Bot read it, pulled 7 public GitHub repos, wired them into a pipeline, and got one sentence from me: earn or the process dies. $200 in the wallet. nobody tops it up the pipeline did not pick tickers off the timeline. It opened Fomo, I register (as grok bot said) - scanned the tape, and locked on Aurelius0121 $4.85M on the book. +$1.19M in 24h. 3.2k trades. 1d 18h average hold. biggest prints still public: +$2.38M, AMC +$1.16M, +$785k from there it ran without me every few seconds it: > reads his last fills, not a call > checks size against the leftover wallet > copies the same side smaller > skips anything already cooked > holds toward his 42-hour clock > writes the fill or passes if the wallet hits $0 the box dies with it 47 fills later the small account was +$870. his book is still $4.85M. the bot inherited the hold, not the bankroll Grok is one layer. The repos, the Fomo desk and the kill switch sit around it. a normal chat goes quiet when the tab closes. this one still had a job
0:21

I pointed Grok Bot at one article about overnight bots and gave it $200 plus a kill line: earn or the process dies Grok Bot read it, pulled 7 public GitHub repos, wired them into a pipeline, and got one sentence from me: earn or the process dies. $200 in the wallet. nobody tops it up the pipeline did not pick tickers off the timeline. It opened Fomo, I register (as grok bot said) - scanned the tape, and locked on Aurelius0121 $4.85M on the book. +$1.19M in 24h. 3.2k trades. 1d 18h average hold. biggest prints still public: +$2.38M, AMC +$1.16M, +$785k from there it ran without me every few seconds it: > reads his last fills, not a call > checks size against the leftover wallet > copies the same side smaller > skips anything already cooked > holds toward his 42-hour clock > writes the fill or passes if the wallet hits $0 the box dies with it 47 fills later the small account was +$870. his book is still $4.85M. the bot inherited the hold, not the bankroll Grok is one layer. The repos, the Fomo desk and the kill switch sit around it. a normal chat goes quiet when the tab closes. this one still had a job

morph

11,520 просмотров • 13 дней назад

i gave grok bot three repos from github and one job: make money on Polymarket. first day it made $3300. honestly, i didn't think free github bots could earn anything the first one was built for the Colosseum hackathon. it looks at what a Polymarket event is priced at everywhere else: fed rate futures, 538, Silver Bulletin, bookmaker odds. when there's a gap, it gives a signal to enter. the second one watches 15m crypto markets and waits for a contract to drop 15% in 3 seconds. it buys the side that fell and picks up the other one while both together cost less than 95 cents. the third one answers the question worth asking before you follow anyone's wallet: how much of their strategy can you actually reproduce. it pulls a trader's entire history, runs it again and gives you a number - how much of their result shows up on your side, and how much stays on theirs. it's genuinely simple. grok sets up the environment itself, figures out the config, runs a few trades in dry run and moves to real trading
0:31

i gave grok bot three repos from github and one job: make money on Polymarket. first day it made $3300. honestly, i didn't think free github bots could earn anything the first one was built for the Colosseum hackathon. it looks at what a Polymarket event is priced at everywhere else: fed rate futures, 538, Silver Bulletin, bookmaker odds. when there's a gap, it gives a signal to enter. the second one watches 15m crypto markets and waits for a contract to drop 15% in 3 seconds. it buys the side that fell and picks up the other one while both together cost less than 95 cents. the third one answers the question worth asking before you follow anyone's wallet: how much of their strategy can you actually reproduce. it pulls a trader's entire history, runs it again and gives you a number - how much of their result shows up on your side, and how much stays on theirs. it's genuinely simple. grok sets up the environment itself, figures out the config, runs a few trades in dry run and moves to real trading

may.crypto {🦅}

56,122 просмотров • 24 дней назад

SOMEONE JUST CREATED AI TECHNOLOGY THAT MAKES WIFI SEE THROUGH WALLS. IT READS YOUR HEARTBEAT, BREATHING RATE, AND MOVEMENT ON THE OTHER SIDE. you don't need to be in the room, a camera, or anything except a WiFi signal and an AI that interprets what bounces back this is not a government prototype, this already exists and someone just published it on GitHub this is proof that with AI you can build almost anything you can imagine that's exactly why I put together a guide on Claude features most people don't know exist the article below shows exactly what that looks like in practice
1:09

SOMEONE JUST CREATED AI TECHNOLOGY THAT MAKES WIFI SEE THROUGH WALLS. IT READS YOUR HEARTBEAT, BREATHING RATE, AND MOVEMENT ON THE OTHER SIDE. you don't need to be in the room, a camera, or anything except a WiFi signal and an AI that interprets what bounces back this is not a government prototype, this already exists and someone just published it on GitHub this is proof that with AI you can build almost anything you can imagine that's exactly why I put together a guide on Claude features most people don't know exist the article below shows exactly what that looks like in practice

Anatoli Kopadze

20,812 просмотров • 3 месяцев назад

As we approach Monad mainnet, it’s worth understanding how Liquid Staking Protocols actually work, beyond just minting an LST. In this video, I'll walk you 🫵 through the architecture behind Kintsu, including: - How staking $MON into $sMON ("Staked MON") is like owning a share of a growing staking pool, unlocking massive amounts of otherwise idle composable liquidity from the base layer - How compounding happens automatically as validators earn rewards for processing transactions & securing the network - How unstaking sMON works with unbonding requests, batching and claiming back you MON - How the Kintsu Validator Registry evolves over time, not just from inflows/outflows, but through DAO-driven updates and algorithmic routing This is the foundation behind sMON, the most powerful DeFi money lego native to Monad. If you're planning to be active in Monad DeFi as a power user, buildoooor or validator on Monad, the mechanics matter. Education matters, especially in DeFi. Please feel free to ask away with any questions, that is what we're here for. 5 days till Mainnet. Get ready!
10:49

As we approach Monad mainnet, it’s worth understanding how Liquid Staking Protocols actually work, beyond just minting an LST. In this video, I'll walk you 🫵 through the architecture behind Kintsu, including: - How staking $MON into $sMON ("Staked MON") is like owning a share of a growing staking pool, unlocking massive amounts of otherwise idle composable liquidity from the base layer - How compounding happens automatically as validators earn rewards for processing transactions & securing the network - How unstaking sMON works with unbonding requests, batching and claiming back you MON - How the Kintsu Validator Registry evolves over time, not just from inflows/outflows, but through DAO-driven updates and algorithmic routing This is the foundation behind sMON, the most powerful DeFi money lego native to Monad. If you're planning to be active in Monad DeFi as a power user, buildoooor or validator on Monad, the mechanics matter. Education matters, especially in DeFi. Please feel free to ask away with any questions, that is what we're here for. 5 days till Mainnet. Get ready!

StovenLabs

27,539 просмотров • 10 месяцев назад

A lot of people ask why I use Rork but still use Cursor or Claude Code. Honestly, it’s simple, I don’t like relying on just one AI tool. Usually I start building the app with Rork, then connect it to GitHub and continue developing with Claude Code or Cursor. Some features just need deeper customization, and it’s much easier to handle those outside of Rork. PS: Rork sponsored me to build my app.
1:04

A lot of people ask why I use Rork but still use Cursor or Claude Code. Honestly, it’s simple, I don’t like relying on just one AI tool. Usually I start building the app with Rork, then connect it to GitHub and continue developing with Claude Code or Cursor. Some features just need deeper customization, and it’s much easier to handle those outside of Rork. PS: Rork sponsored me to build my app.

Alex Nguyen

16,430 просмотров • 6 месяцев назад

This is huge! This fixes the universal problem with conversational agents: hallucinations! Every company that builds customer-facing agents struggles to align them with business rules and make them consistent. If you solve this, you'll become a hero overnight. Check out Parlant, a free, open-source library taking off on GitHub. This is why it's big: 1. You have 10x more control over what your conversation agent says 2. You control how it conducts conversations 3. You control the service protocols and rules it follows 4. You control what it can and can't say Here is how Parlant's engine works behind the scenes as soon as your agent receives a question from a customer: 1. It loads the necessary domain terminology 2. It finds the relevant guidelines to answer the question 3. It invokes your tools to gather any relevant information 4. It implements self-critique to craft/evaluate its response iteratively All of this makes it very hard for an agent to hallucinate. Here is the GitHub repository: And here is a paper showing the prompt engineering method Parlant uses behind the scenes (4.8% more accurate than Chain of Thought!):
0:37

This is huge! This fixes the universal problem with conversational agents: hallucinations! Every company that builds customer-facing agents struggles to align them with business rules and make them consistent. If you solve this, you'll become a hero overnight. Check out Parlant, a free, open-source library taking off on GitHub. This is why it's big: 1. You have 10x more control over what your conversation agent says 2. You control how it conducts conversations 3. You control the service protocols and rules it follows 4. You control what it can and can't say Here is how Parlant's engine works behind the scenes as soon as your agent receives a question from a customer: 1. It loads the necessary domain terminology 2. It finds the relevant guidelines to answer the question 3. It invokes your tools to gather any relevant information 4. It implements self-critique to craft/evaluate its response iteratively All of this makes it very hard for an agent to hallucinate. Here is the GitHub repository: And here is a paper showing the prompt engineering method Parlant uses behind the scenes (4.8% more accurate than Chain of Thought!):

Santiago

93,080 просмотров • 1 год назад