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Sibyl Memory Plugin. closed beta is opening. one command, any harness. -95.1% on longmemeval. -file-based. -zero vectors. -hierarchical schema. early data is showing a 52% reduction in token usage. bounty board goes live tomorrow. come learn, earn & build.

SIBYL

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30,811 views • 2 months ago •via X (Twitter)

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Andrew Ng

89,779 views • 1 year ago

Once you learn these three things, you can build nearly anything yourself. Skills, chains, and plugins. Learn them once and you can automate a real part of your week yourself. Here's the system: A skill is a standard operating procedure. It's one long, reusable prompt that does one thing well, like writing a newsletter, setting up a PPC campaign, triaging your inbox, or drafting a note to the board. You write it once and reuse it forever. The trick is to feed it your real work. For my writing skill, I gave Claude posts I admire and my own exported analytics with the winners marked, so it could see the patterns. Show it what good looks like and it nails your voice. Skip that step and it guesses. A chain connects skills into an automation. One skill's output feeds the next, in order. A copywriting skill writes the messaging, then hands it to a PPC-setup skill that builds the campaign. That's an automation, and you built it without writing code. A plugin is the harness that holds it all. It bundles your skills and chains into one thing you share with your team. Instead of sending 15 separate prompts around, you send one plugin, and it knows when to use each skill on its own. Skill, chain, plugin. It's one step up the ladder, and once you're up there it's easy. Now the worked example. I call it the Daily Driver. It's five skills chained together: email triage, a writer, Slack triage, a thinking partner, and a setup skill that connects my tools and personalizes everything. I chained them into one morning brief and scheduled it to run at 9am and message me the list. Two things made the biggest difference. Give it memory. I made plain docs for About Me, my Brand Voice, and my working preferences. I had Claude interview me and saved each answer as a file. Now every output sounds like me and knows my projects and my team. Connect your tools. The plugin reads my inbox, Slack, and calendar through MCP connectors for Gmail, Slack, and Google Calendar. That's what turns "summarize my morning" into a real brief instead of an empty wish. This is the highest-ROI thing an operator can set up this week. I run my YouTube channel, podcast, community, and newsletter on plugins I built myself, all on the $100 Max plan with no engineer in sight. I made a full walkthrough that shows the whole build start to finish. Want the Daily Driver plugin to start from? Comment PLUGIN below and I'll send it to you. #AI #automation #ClaudeCode

JJ Englert

53,898 views • 1 month ago

HOW TO SELL "SECOND BRAIN AS A SERVICE" FOR $5K + (FULL COURSE) The model: build businesses a structured knowledge base out of plain markdown files, then charge to maintain it. No fancy database, Obsidian, or RAG. It becomes the foundation for every other AI project you sell them afterward. A $750 audit turns into a $3,500 build turns into a client who keeps paying you to add more. Adam Sandler came on the pod and walked through the entire playbook live. Here's what I learned: 1. Lead with the knowledge base, not the agent. Every prospect wants a CFO agent. Nobody has the context to make one work. Solve "where does the info live?" first and you've teed up every future build. 2. Sell it with AI out of the pitch. "I'll organize all your scattered company knowledge into one living asset." Their files are everywhere and they hate it. That closes on its own. 3. Zero technical friction. Just markdown files on their machine. No signup, no vault, no vectors. Technical drop-off kills AI deals. This deletes it. 4. Seven note types are your starting schema. Snapshot, people, rules, project history, decisions, open loops, links. Walk in with this and you already have a point of view. 5. Find the spine. The one thing everything ladders up to. Usually their annual goals. 6. Portability is the pitch. Fable got pulled and everyone panicked. A knowledge base outside Anthropic or OpenAI plugs into any model. Sells itself. 7. Token savings close the enterprise. One source means you stop re-pasting context every session. Real money, especially with pay-as-you-go API pricing. 8. The audit is the tripwire. Charge to map where their knowledge lives, then roll the fee into the build. Half the build is already done. 9. Two skills run it on autopilot. Ingest pulls from Gmail, calendar, and CRM. Curate does a weekly cleanup pass. That's the flywheel. 10. The knowledge base tells you what to sell next. Ask it for the top 3 AI opportunities. It finds the gap ("inbound takes 22 hours") and the next build sells itself. His 2 key takeaways: 1. Build one for yourself first. One source of truth, built once, every tool connected. Live the unlock and you'll sell it with conviction. 2. Don't let startups scare you off. Off-the-shelf can't learn how your client's business works. That domain knowledge is the moat you charge for. Adam is quietly building one of the best AI service offers out there and we had a blast going deep on it. Go follow Adam Sandler Full video below. (Also available on the Build With AI podcast wherever you get your pods)

HOW TO SELL "SECOND BRAIN AS A SERVICE" FOR $5K + (FULL COURSE) The model: build businesses a structured knowledge base out of plain markdown files, then charge to maintain it. No fancy database, Obsidian, or RAG. It becomes the foundation for every other AI project you sell them afterward. A $750 audit turns into a $3,500 build turns into a client who keeps paying you to add more. Adam Sandler came on the pod and walked through the entire playbook live. Here's what I learned: 1. Lead with the knowledge base, not the agent. Every prospect wants a CFO agent. Nobody has the context to make one work. Solve "where does the info live?" first and you've teed up every future build. 2. Sell it with AI out of the pitch. "I'll organize all your scattered company knowledge into one living asset." Their files are everywhere and they hate it. That closes on its own. 3. Zero technical friction. Just markdown files on their machine. No signup, no vault, no vectors. Technical drop-off kills AI deals. This deletes it. 4. Seven note types are your starting schema. Snapshot, people, rules, project history, decisions, open loops, links. Walk in with this and you already have a point of view. 5. Find the spine. The one thing everything ladders up to. Usually their annual goals. 6. Portability is the pitch. Fable got pulled and everyone panicked. A knowledge base outside Anthropic or OpenAI plugs into any model. Sells itself. 7. Token savings close the enterprise. One source means you stop re-pasting context every session. Real money, especially with pay-as-you-go API pricing. 8. The audit is the tripwire. Charge to map where their knowledge lives, then roll the fee into the build. Half the build is already done. 9. Two skills run it on autopilot. Ingest pulls from Gmail, calendar, and CRM. Curate does a weekly cleanup pass. That's the flywheel. 10. The knowledge base tells you what to sell next. Ask it for the top 3 AI opportunities. It finds the gap ("inbound takes 22 hours") and the next build sells itself. His 2 key takeaways: 1. Build one for yourself first. One source of truth, built once, every tool connected. Live the unlock and you'll sell it with conviction. 2. Don't let startups scare you off. Off-the-shelf can't learn how your client's business works. That domain knowledge is the moat you charge for. Adam is quietly building one of the best AI service offers out there and we had a blast going deep on it. Go follow Adam Sandler Full video below. (Also available on the Build With AI podcast wherever you get your pods)

Corey Ganim

105,458 views • 1 month ago

NXT Monthly Updates with Allie, Episode 03 ⁠— We launched pilot programs in Andhra Pradesh with spice exporters—one already closed $80K in new contracts using NXT; ⁠— We're expanding those pilots into new trade zones and prepping to onboard agri co-ops in Q2; ⁠— Early data shows a 65% cost reduction vs SWIFT, which is already a key selling point in margin-tight industries; ⁠— We’re deep in talks with NFDB-aligned institutions to plug into larger networks and smooth the regulatory path; ⁠— We’ve built local support for GST compliance, crypto tax handling, and KYC—so we can move fast without legal headaches; ⁠— Our loan issuance system is now live in test, with disbursements starting this month and new credit requests rolling in daily; ⁠— We’ve received over $28M in financing requests so far, and are onboarding new liquidity partners to help us scale faster; ⁠— Onboarding is now fully automated, and KYC approval time is down to under 12 hours; ⁠— We’ve started live testing of our on-chain contract lifecycle system—tokenizing deals, automating payments, and handling disputes in one workflow; ⁠— Monthly transaction volume is up 12% over the last 60 days, even as we transition into new markets; ⁠— Revenue stayed flat, which we expected during this expansion phase—but core activity and ecosystem usage are climbing steadily; ⁠— We’ve spun up local sales and support teams, with hiring ongoing across key Indian cities to drive faster adoption;

NXT Monthly Updates with Allie, Episode 03 ⁠— We launched pilot programs in Andhra Pradesh with spice exporters—one already closed $80K in new contracts using NXT; ⁠— We're expanding those pilots into new trade zones and prepping to onboard agri co-ops in Q2; ⁠— Early data shows a 65% cost reduction vs SWIFT, which is already a key selling point in margin-tight industries; ⁠— We’re deep in talks with NFDB-aligned institutions to plug into larger networks and smooth the regulatory path; ⁠— We’ve built local support for GST compliance, crypto tax handling, and KYC—so we can move fast without legal headaches; ⁠— Our loan issuance system is now live in test, with disbursements starting this month and new credit requests rolling in daily; ⁠— We’ve received over $28M in financing requests so far, and are onboarding new liquidity partners to help us scale faster; ⁠— Onboarding is now fully automated, and KYC approval time is down to under 12 hours; ⁠— We’ve started live testing of our on-chain contract lifecycle system—tokenizing deals, automating payments, and handling disputes in one workflow; ⁠— Monthly transaction volume is up 12% over the last 60 days, even as we transition into new markets; ⁠— Revenue stayed flat, which we expected during this expansion phase—but core activity and ecosystem usage are climbing steadily; ⁠— We’ve spun up local sales and support teams, with hiring ongoing across key Indian cities to drive faster adoption;

Ultron

30,026 views • 1 year ago

🚨‼️ They Have Been Dropping The Biggest Hints About One Of Ripple’s Biggest NDAs: Privacy, A New Multi-Trillion Dollar Technology Game-changing Red Pill from Ripple CEO Brad Garlinghouse: “The government owns your identity and Blockchain-based identity is the ONLY way to stop governments from controlling our personal documents.” Ripple President Monica Long: Decentralized identity on XRPL = your data as a portable, user-controlled token powered by zero-knowledge proofs. DNA Protocol executed the FIRST-EVER ZK-Proof Privacy Transaction LIVE on XRPL with their portable private digital token XDNA. And now Boundless has also landed on XRPL for zk-proofs. From ~5M XRP wallets today → billions of people + institutional credentials (KYC, licenses, certs) tomorrow. Epstein emails revealed that they dragged Ripple to the court with Lawsuit because they viewed Ripple as a “threat to their ecosystem” and Epstein wanted to gain physical control over ZCash keys. Epstein also invested in Coinbase and look how it is attacking Ripple over Clarity Act. The same Epstein Cabal that attacked Ripple is now pushing for Digital ID’s and XRPL might’ve cracked the code against it. Private Identity. Private Transactions. On The XRP Ledger. This could be the biggest breakthrough on XRPL👇

🚨‼️ They Have Been Dropping The Biggest Hints About One Of Ripple’s Biggest NDAs: Privacy, A New Multi-Trillion Dollar Technology Game-changing Red Pill from Ripple CEO Brad Garlinghouse: “The government owns your identity and Blockchain-based identity is the ONLY way to stop governments from controlling our personal documents.” Ripple President Monica Long: Decentralized identity on XRPL = your data as a portable, user-controlled token powered by zero-knowledge proofs. DNA Protocol executed the FIRST-EVER ZK-Proof Privacy Transaction LIVE on XRPL with their portable private digital token XDNA. And now Boundless has also landed on XRPL for zk-proofs. From ~5M XRP wallets today → billions of people + institutional credentials (KYC, licenses, certs) tomorrow. Epstein emails revealed that they dragged Ripple to the court with Lawsuit because they viewed Ripple as a “threat to their ecosystem” and Epstein wanted to gain physical control over ZCash keys. Epstein also invested in Coinbase and look how it is attacking Ripple over Clarity Act. The same Epstein Cabal that attacked Ripple is now pushing for Digital ID’s and XRPL might’ve cracked the code against it. Private Identity. Private Transactions. On The XRP Ledger. This could be the biggest breakthrough on XRPL👇

Stellar Rippler🚀

68,545 views • 2 months ago

2025.07.01 bi-weekly update here’s what we’ve built, shipped, and trained this past week: TRADING CAPABILITIES + agent-based txn execution engine now supports Meteora (DBC, DLMM, DYN, DAMM), Raydium (CLMM, AMM, CPMM), and Orca 🌊 (CLLM, VP, CPMM). we're now compatible with nearly every major liquidity layer on Solana. + DCA and limit orders now available to use through our agentic/natural language interface. + execution is faster, leaner, more reliable; optimized based on real closed beta usage. AGENT SWARM + A2A (agent-to-agent) finalized; based on Google's new open framework. it enables dynamic coordination between agents, deeper reasoning, better memory, and more human-like flow. + TraceGraph (diagram/chain-of-thought-like) UI is now deployed. users now see how Aya (and others) think and collaborate together. visualizes multi-agent logic paths. text UI also upgraded. sharper, smoother, faster. + Bravo (macro news oracle) live. it connects real-world macro events and news to Solana. powered by our in-house scrapers + NewsAPI, built from scratch. integrations with blocmates. coming soon. + Solvion, our Solana-native domain expert, is now active. trained on a custom-built, 70B parameter dataset of the full Solana ecosystem. auto-updated. devs, tokenomics, projects, whitepapers, technical information, know-hows... it knows everything. + Echo (our social media and sentiment analyst agent) getting integrated with Sentient natural language interface + Rivalz Network. + you can now start individual conversations with agents. e.g. ask Echo anything about social trends, or hit up Solvion for technicals. UX/UI + we’re now mobile responsive; fully optimized across devices. + deployed TraceGraph (diagram UI for agent cognition). + NLI improvements: sleeker prompt-response flow, improved text visualization, better latency, better rendering. + agents feel more alive, dynamic, and explainable PREDICTIONS weekly update from our head quant: + we now do weekly fine-tuning to adapt to market shifts. switched from F1-score optimization to pure precision; cutting noise, and maximizing conviction. we now discard the worst-performing model in the ensemble. only the top 2 vote. accuracy last 6 weeks = 82% directional. the ensemble logic is fully restructured. next: RNN + RL-based dynamic thresholding in progress (live this month). + partnered with Allora for the the SOL/USDT prediction stack, combining our hype score with their confidence-aware forecasting. + also cooking something with Sahara AI 🔆 (????)... OTHER + PnL cards integrated. track profit per trade, share it on X, get free XCC + Referral system is complete and rolling out to early users very soon (top referrers will dominate first layer of our multi-level tree and enjoy first-movers advantage). + working on a dynamic onboarding tutorial for first-time users. + backend latency improvements across endpoints. especially on token explorer + prediction refresh + docs are live ( TEAM + onboarded amy and Mike | heymike.sol 🎒🪽 — elite Solana engineers working on gRPCs, RPCs, instruction decoding, and data pipelines. their focus: making xFractal the only real-time NLP engine for Solana alpha extraction. + brought on ultra , Skely, HALKO and Gabriel Haines as strategic advisors and contributors, helping us scale narrative modeling, data ops, and GTM. QUICK STATS (REMINDER: this is a closed, invite-only beta — not optimized for adoption yet) + 400+ early beta testoors + 9,000+ natural language prompts + 500+ on-chain txs executed via our agent-based engine + we’re not scaling users yet, we’re optimizing agents, validating edge, and consolidating PMF. + open beta coming soon. engine’s warming up. let’s keep moving. (p.s. toly 🇺🇸 check this out)

2025.07.01 bi-weekly update here’s what we’ve built, shipped, and trained this past week: TRADING CAPABILITIES + agent-based txn execution engine now supports Meteora (DBC, DLMM, DYN, DAMM), Raydium (CLMM, AMM, CPMM), and Orca 🌊 (CLLM, VP, CPMM). we're now compatible with nearly every major liquidity layer on Solana. + DCA and limit orders now available to use through our agentic/natural language interface. + execution is faster, leaner, more reliable; optimized based on real closed beta usage. AGENT SWARM + A2A (agent-to-agent) finalized; based on Google's new open framework. it enables dynamic coordination between agents, deeper reasoning, better memory, and more human-like flow. + TraceGraph (diagram/chain-of-thought-like) UI is now deployed. users now see how Aya (and others) think and collaborate together. visualizes multi-agent logic paths. text UI also upgraded. sharper, smoother, faster. + Bravo (macro news oracle) live. it connects real-world macro events and news to Solana. powered by our in-house scrapers + NewsAPI, built from scratch. integrations with blocmates. coming soon. + Solvion, our Solana-native domain expert, is now active. trained on a custom-built, 70B parameter dataset of the full Solana ecosystem. auto-updated. devs, tokenomics, projects, whitepapers, technical information, know-hows... it knows everything. + Echo (our social media and sentiment analyst agent) getting integrated with Sentient natural language interface + Rivalz Network. + you can now start individual conversations with agents. e.g. ask Echo anything about social trends, or hit up Solvion for technicals. UX/UI + we’re now mobile responsive; fully optimized across devices. + deployed TraceGraph (diagram UI for agent cognition). + NLI improvements: sleeker prompt-response flow, improved text visualization, better latency, better rendering. + agents feel more alive, dynamic, and explainable PREDICTIONS weekly update from our head quant: + we now do weekly fine-tuning to adapt to market shifts. switched from F1-score optimization to pure precision; cutting noise, and maximizing conviction. we now discard the worst-performing model in the ensemble. only the top 2 vote. accuracy last 6 weeks = 82% directional. the ensemble logic is fully restructured. next: RNN + RL-based dynamic thresholding in progress (live this month). + partnered with Allora for the the SOL/USDT prediction stack, combining our hype score with their confidence-aware forecasting. + also cooking something with Sahara AI 🔆 (????)... OTHER + PnL cards integrated. track profit per trade, share it on X, get free XCC + Referral system is complete and rolling out to early users very soon (top referrers will dominate first layer of our multi-level tree and enjoy first-movers advantage). + working on a dynamic onboarding tutorial for first-time users. + backend latency improvements across endpoints. especially on token explorer + prediction refresh + docs are live ( TEAM + onboarded amy and Mike | heymike.sol 🎒🪽 — elite Solana engineers working on gRPCs, RPCs, instruction decoding, and data pipelines. their focus: making xFractal the only real-time NLP engine for Solana alpha extraction. + brought on ultra , Skely, HALKO and Gabriel Haines as strategic advisors and contributors, helping us scale narrative modeling, data ops, and GTM. QUICK STATS (REMINDER: this is a closed, invite-only beta — not optimized for adoption yet) + 400+ early beta testoors + 9,000+ natural language prompts + 500+ on-chain txs executed via our agent-based engine + we’re not scaling users yet, we’re optimizing agents, validating edge, and consolidating PMF. + open beta coming soon. engine’s warming up. let’s keep moving. (p.s. toly 🇺🇸 check this out)

xFractal

42,668 views • 1 year ago

how to use firecrawl to give your AI eyes and actually build startups that outperform 99% of apps: 1. your AI is smart but blind. it can't go to a website, read a page, or grab data on its own. firecrawl fixes that. you put in a URL. you get back clean markdown, structured JSON, screenshots. feed it to any model. 2. three lines of code. that's it. no proxies. no anti-bot detection. no custom scrapers that break when a site changes. one API call. clean data back in seconds. works on 98%+ of sites. 3. firecrawl has six core capabilities: scrape a single page. crawl an entire site. map all URLs on a domain. search google and return full content. an agent endpoint where you describe what you want and it goes and finds it. and a browser sandbox where AI controls a real browser like filling forms, clicking buttons, handles logins. 4. the agent endpoint is wild. you can say "find all of YC's winter 24 dev tool companies and their founders and emails" and get back structured data. or "compare pricing tiers across stripe, square, and paypal" and get a side-by-side table. 5. the browser sandbox lets your AI stay logged in across sessions, navigate pagination, watch live as it browses. this is computer use without building the infrastructure yourself. 6. think of it in layers. every builder needs: an agent harness (claude code, cursor, codex), a search layer (perplexity, exa), a web data layer (firecrawl), an ops brain (obsidian, notion), and an outbound stack. the web data layer is the one most people are sleeping on. 7. this is the AWS moment for web data. in 2006 building a web app meant buying servers and managing racks. AWS said one API call, use our servers. some of the biggest companies of the last decade were built on that. firecrawl is doing the same thing for web data in 2026. 8. the framework i'd use for coming up with startup ideas building with clean data: take a massive horizontal platform. rebuild it for one niche using firecrawl. the vertical version always wins because people want specific, not generic. price for outcome. 9. a year ago firecrawl posted a job listing that said "please only apply if you're an AI agent." content creator agents. customer support agents. junior dev agents. it looked weird. it was a signal for where this is all going. the people who understand how to get clean web data, wrap it around an LLM, and package it as a product are the the ones with a 12-month head start. i use Firecrawl with Idea Browser . once you see what's possible with structured web data, you can't unsee it. episode is live on The Startup Ideas Podcast (SIP) 🧃 (full breakdown there) i tried to explain this as clear as possible for even the non technical. send it to a builder friend. watch

how to use firecrawl to give your AI eyes and actually build startups that outperform 99% of apps: 1. your AI is smart but blind. it can't go to a website, read a page, or grab data on its own. firecrawl fixes that. you put in a URL. you get back clean markdown, structured JSON, screenshots. feed it to any model. 2. three lines of code. that's it. no proxies. no anti-bot detection. no custom scrapers that break when a site changes. one API call. clean data back in seconds. works on 98%+ of sites. 3. firecrawl has six core capabilities: scrape a single page. crawl an entire site. map all URLs on a domain. search google and return full content. an agent endpoint where you describe what you want and it goes and finds it. and a browser sandbox where AI controls a real browser like filling forms, clicking buttons, handles logins. 4. the agent endpoint is wild. you can say "find all of YC's winter 24 dev tool companies and their founders and emails" and get back structured data. or "compare pricing tiers across stripe, square, and paypal" and get a side-by-side table. 5. the browser sandbox lets your AI stay logged in across sessions, navigate pagination, watch live as it browses. this is computer use without building the infrastructure yourself. 6. think of it in layers. every builder needs: an agent harness (claude code, cursor, codex), a search layer (perplexity, exa), a web data layer (firecrawl), an ops brain (obsidian, notion), and an outbound stack. the web data layer is the one most people are sleeping on. 7. this is the AWS moment for web data. in 2006 building a web app meant buying servers and managing racks. AWS said one API call, use our servers. some of the biggest companies of the last decade were built on that. firecrawl is doing the same thing for web data in 2026. 8. the framework i'd use for coming up with startup ideas building with clean data: take a massive horizontal platform. rebuild it for one niche using firecrawl. the vertical version always wins because people want specific, not generic. price for outcome. 9. a year ago firecrawl posted a job listing that said "please only apply if you're an AI agent." content creator agents. customer support agents. junior dev agents. it looked weird. it was a signal for where this is all going. the people who understand how to get clean web data, wrap it around an LLM, and package it as a product are the the ones with a 12-month head start. i use Firecrawl with Idea Browser . once you see what's possible with structured web data, you can't unsee it. episode is live on The Startup Ideas Podcast (SIP) 🧃 (full breakdown there) i tried to explain this as clear as possible for even the non technical. send it to a builder friend. watch

GREG ISENBERG

134,714 views • 4 months ago

I built a Claude skill that turns Claude Code into your personal coding tutor. The core insight: Claude Opus 4.5 is already the best tutor in the world. Anthropic cooked with this model! It has incredible emotional intelligence and deep coding knowledge. What this skill does is just provide a harness—a way for Claude to agentically build the right context about YOU so it can personalize the tutoring experience in exactly the right way. Here's what makes it work: Learner profile from day one. The first time you use it, Claude interviews you. It asks about your programming background, your goal (where do you want this to take you?), and who you are as a person. This gets saved and informs every single tutorial it ever writes for you. From the very first interaction, everything is 100% personalized. Tutorials that use YOUR code. When you ask to learn something, Claude doesn't give you generic examples from some blog post. It finds examples in the actual codebase you're working in. This makes concepts stick in a way abstract examples never do. Quiz mode with spaced repetition. You can run "/quiz-me" and Claude will test you on concepts you've learned. It tracks your understanding score for each tutorial. Then it uses spaced repetition to prioritize the next quiz—concepts you're shaky on come back in 2 days, concepts you've mastered fade to 55+ day intervals. It literally builds retention into the learning process. One central knowledge base across all your projects. Whether you're joining a new company and want to understand their codebase, learning from an open source project, or leveling up on your own vibe-coded project—all your tutorials live in one place (~/coding-tutor-tutorials/). So your personal coding-tutor accompanies you across all your coding adventures. The whole thing is a feedback loop: learn → quiz → retain → learn more → quiz → retain. Your tutorials evolve, your knowledge compounds, and Claude gets better at teaching YOU specifically over time. To install it in Claude Code: • Run /plugin to open the plugin manager • Add marketplace nityeshaga/claude-code-essentials • Enable coding-tutor plugin Here's the Github: And here's 20-mins of me walking you through how to use this plugin and how it works 👇🏽 Let me know if you use it to teach yourself something cool!

Nityesh

64,540 views • 7 months ago

The time has come. Introducing Parallel an all-in-one copy trading platform for DeFi products that combines four years of our experience building on Solana and AI to create what we hope is a one-of-a-kind product for the Solana ecosystem. It’s our pleasure to announce that we’re now entering private beta for our first module built around Meteora DLMMs. You’ll be able to copy trade DLMM positions with fast execution and a ton of automated functions on top. Some key features: * Stop loss/take profit * Real-time PnL shown on the UI for your LP * Automatically claim fees when they reach X SOL or on a timer * Automatically swap all claimed fees into SOL * Become a power user and earn a % of fees from everyone copying your wallet * Generous referral comp And much more! Data feeds & AI: We understand what it takes for a copy trading platform to thrive, so we’ve been collecting real-time data from several contracts for both Meteora and the upcoming modules we’re releasing. As you can imagine, we’re handling tons of data, so with the help of AI, we’re not only analyzing potential up-and-coming wallets but also the top wallets on-chain that people don’t want you to know about. This applies to all aspects of DeFi—not just token trading. To access these data feeds, you’ll need $GP or our native Taiyo NFTs. More information will roll out as these feeds start to go live. Private Beta Access: We’re now collecting a list of the first 100 private beta testers, including LP army members, the Taiyo community, BOOGLES, and more. If you’re interested in getting early access, you can now submit your email at 👇 We recommend always creating a separate email for crypto purposes to keep your personal and online profiles separate. Excited to cook with you on our first non Launchpad related platform since Solport itself back in 2021. 🤝

The time has come. Introducing Parallel an all-in-one copy trading platform for DeFi products that combines four years of our experience building on Solana and AI to create what we hope is a one-of-a-kind product for the Solana ecosystem. It’s our pleasure to announce that we’re now entering private beta for our first module built around Meteora DLMMs. You’ll be able to copy trade DLMM positions with fast execution and a ton of automated functions on top. Some key features: * Stop loss/take profit * Real-time PnL shown on the UI for your LP * Automatically claim fees when they reach X SOL or on a timer * Automatically swap all claimed fees into SOL * Become a power user and earn a % of fees from everyone copying your wallet * Generous referral comp And much more! Data feeds & AI: We understand what it takes for a copy trading platform to thrive, so we’ve been collecting real-time data from several contracts for both Meteora and the upcoming modules we’re releasing. As you can imagine, we’re handling tons of data, so with the help of AI, we’re not only analyzing potential up-and-coming wallets but also the top wallets on-chain that people don’t want you to know about. This applies to all aspects of DeFi—not just token trading. To access these data feeds, you’ll need $GP or our native Taiyo NFTs. More information will roll out as these feeds start to go live. Private Beta Access: We’re now collecting a list of the first 100 private beta testers, including LP army members, the Taiyo community, BOOGLES, and more. If you’re interested in getting early access, you can now submit your email at 👇 We recommend always creating a separate email for crypto purposes to keep your personal and online profiles separate. Excited to cook with you on our first non Launchpad related platform since Solport itself back in 2021. 🤝

Tom

105,737 views • 1 year ago

I made a little cartoon animation to visualise Minswap V2 swaps using the library I have been building. Each delivery truck represents a block containing Minswap buy or sell swaps, with the size of the truck reflecting the amount of swap activity inside that block. The data comes from OgmiosDotnet.BlockchainEvents, a rule based transaction filtering and event emission engine I have been working on for Cardano. It processes live Cardano blocks through Ogmios, applies pluggable transaction rules, then emits a standardised event schema that downstream systems can consume. The broader idea is to make Cardano blockchain events much easier to integrate into existing enterprise architecture. Applications can define the transactions they care about, turn them into structured events, and feed those events directly into infrastructure across GCP, Azure, AWS and other systems. Minswap swaps are just one example of what can be extracted and visualised. There is still plenty I want to build, but I thought this was a cool basic way of showing what is happening inside each block in real time, whilst thinking outside of the box. Hope you like it :)

I made a little cartoon animation to visualise Minswap V2 swaps using the library I have been building. Each delivery truck represents a block containing Minswap buy or sell swaps, with the size of the truck reflecting the amount of swap activity inside that block. The data comes from OgmiosDotnet.BlockchainEvents, a rule based transaction filtering and event emission engine I have been working on for Cardano. It processes live Cardano blocks through Ogmios, applies pluggable transaction rules, then emits a standardised event schema that downstream systems can consume. The broader idea is to make Cardano blockchain events much easier to integrate into existing enterprise architecture. Applications can define the transactions they care about, turn them into structured events, and feed those events directly into infrastructure across GCP, Azure, AWS and other systems. Minswap swaps are just one example of what can be extracted and visualised. There is still plenty I want to build, but I thought this was a cool basic way of showing what is happening inside each block in real time, whilst thinking outside of the box. Hope you like it :)

Dave

32,051 views • 3 days ago