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💥 Introducing Echo, an AI powered support platform like Intercom, Crisp, or Zendesk. This isn't a sales pitch. It's a real app you'll build, step by step. 💬🚀 🚀 Next.js 15 + React 19 🎨 Tailwind v4 + shadcn UI 🧠 Agents for real-time AI chat 📣 AI tools...

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Code With Antonio

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37,695 Aufrufe • vor 1 Jahr •via X (Twitter)

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💥 Introducing Vibe, an AI powered app builder similar to Lovable, Replit and v0. No, this isn't my SaaS announcement, this is a product that you will learn how to build in my newest FREE course! 🚀 🚀 Next.js 15 + React 19 🎨 Tailwind v4 + shadcn UI 📡 tRPC.io 🧙‍♂️ for full-stack type safety 🔁 Inngest background jobs 🧠 Inngest agent toolkit 🔐 authentication 💳 billing 🧱 Component and app generation from AI prompts 🗂️ Live project preview with URL access 🖥️ E2B cloud sandboxes for runtime execution 🐳 Docker -based sandbox templating 🧠 AI model support (OpenAI, Anthropic, Grok) 📦 Prisma + Neon Postgres for database integration 🤖 CodeRabbit AI-powered PR reviews 🧾 Built-in credit system with usage tracking 🧪 Preview + code explorer toggle

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📣 My newest course is out! 📣 This time we will be building an original SaaS Platform for video calls and summaries with AI Agents 🤖 Are you ready to make 1M ARR 😁? 🤖 Real-time video calls with AI agents 📞 Video and chat powered by Stream 🔐 Authentication handled by Better Auth 💳 Subscription payments via Polar 🧠 AI summaries and context chat using OpenAI ⚙️ Background jobs powered by Inngest 🧑‍💻 Code reviews with CodeRabbit 🗄️ Scalable Postgres database via Neon Postgres 🌐 Built with Next.js 15 and React 19 🎨 Tailwind CSS v4 and shadcn UI for styling 📱 Fully responsive and mobile-friendly 🚀 Ready for production deployment on Vercel
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📣 My newest course is out! 📣 This time we will be building an original SaaS Platform for video calls and summaries with AI Agents 🤖 Are you ready to make 1M ARR 😁? 🤖 Real-time video calls with AI agents 📞 Video and chat powered by Stream 🔐 Authentication handled by Better Auth 💳 Subscription payments via Polar 🧠 AI summaries and context chat using OpenAI ⚙️ Background jobs powered by Inngest 🧑‍💻 Code reviews with CodeRabbit 🗄️ Scalable Postgres database via Neon Postgres 🌐 Built with Next.js 15 and React 19 🎨 Tailwind CSS v4 and shadcn UI for styling 📱 Fully responsive and mobile-friendly 🚀 Ready for production deployment on Vercel

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Hello everyone 👋 It is pretty excited to know that Unity released a new VR Multiplayer template 🚀🥳! This template integrates Unity Gaming Services, Netcode for GameObjects, and the XR Interaction Toolkit, enabling you to quickly launch your next social VR game. 📌 Key features include: 👉 XR Hands 1.4.1: Access hand tracking data from devices that support it. 👉 XR Interaction Toolkit v3.0.1: A high-level, component-based system for creating XR experiences, facilitating 3D and UI interactions from Unity input events. 👉 XR Plugin Management 4.4.1: Streamlines XR plug-in lifecycle management and offers a build-time UI through Unity Unified Settings. 👉 Netcode for GameObjects 1.8.1: Provides networking capabilities for GameObject and MonoBehaviour workflows. 👉 OpenXR 1.10.0: An open standard by Khronos that simplifies AR/VR development across various devices. ☁️ Unity Cloud Multiplayer Services: - Authentication 3.3.1: Offers anonymous and platform-specific authentication solutions. - Lobby 1.2.0: Facilitates player discovery and connection for various multiplayer scenarios. - Relay 1.6.0: Ensures secure player connectivity via a join code system, eliminating the need for third-party solutions or dedicated servers. - Vivox 16.0.0: Enhances multiplayer experiences with in-game voice and text chat capabilities. ℹ️ To access the template and additional documentation check out: #unity #multiplayer #xr
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Hello everyone 👋 It is pretty excited to know that Unity released a new VR Multiplayer template 🚀🥳! This template integrates Unity Gaming Services, Netcode for GameObjects, and the XR Interaction Toolkit, enabling you to quickly launch your next social VR game. 📌 Key features include: 👉 XR Hands 1.4.1: Access hand tracking data from devices that support it. 👉 XR Interaction Toolkit v3.0.1: A high-level, component-based system for creating XR experiences, facilitating 3D and UI interactions from Unity input events. 👉 XR Plugin Management 4.4.1: Streamlines XR plug-in lifecycle management and offers a build-time UI through Unity Unified Settings. 👉 Netcode for GameObjects 1.8.1: Provides networking capabilities for GameObject and MonoBehaviour workflows. 👉 OpenXR 1.10.0: An open standard by Khronos that simplifies AR/VR development across various devices. ☁️ Unity Cloud Multiplayer Services: - Authentication 3.3.1: Offers anonymous and platform-specific authentication solutions. - Lobby 1.2.0: Facilitates player discovery and connection for various multiplayer scenarios. - Relay 1.6.0: Ensures secure player connectivity via a join code system, eliminating the need for third-party solutions or dedicated servers. - Vivox 16.0.0: Enhances multiplayer experiences with in-game voice and text chat capabilities. ℹ️ To access the template and additional documentation check out: #unity #multiplayer #xr

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Learn to build conversational AI voice agents in "Building AI Voice Agents for Production", created in collaboration with LiveKit and RealAvatar, and taught by dsa (Co-founder & CEO of LiveKit), Shayne (Developer Advocate, LiveKit), and Nedelina Teneva (Head of AI at RealAvatar, an AI Fund portfolio company). Voice agents combine speech and reasoning capabilities to enable real-time conversations. They're already being used to support customer service, to improve accessibility in healthcare, for entertainment applications, and for talk therapy. In this course, you’ll learn to build voice agents that listen, reason, and respond naturally. You’ll follow the architecture used to create the "AI Andrew" Avatar, a collaborative project between and RealAvatar that responds to users in what sounds like my voice. You’ll build a voice agent from scratch and deploy it to the cloud, enabling support for many simultaneous users. What you’ll learn: - Understand the fundamentals of voice agents, including key components like speech-to-text (STT), text-to-speech (TTS), and LLMs, and how latency is introduced at each layer. - Explore voice agent architectures and the trade-offs between modular pipelines and speech-to-speech APIs. - Explore how platforms like LiveKit mitigate latency issues with optimized networking infrastructure and low-latency communication protocols. - Learn how to connect client devices to voice agents using WebRTC—and why it outperforms HTTP and WebSocket for low-latency audio streaming. - Incorporate voice activity detection (VAD), end-of-turn detection, and context management to detect turns, handle interruptions, and manage conversational flow. - Understand the trade-offs between latency, quality, and cost in an example in which you build a voice agent and change its voice. - Equip your agent with metrics to measure latency at each stage of the voice pipeline and learn the key levers you can pull to make your agent faster and more responsive. The voice agents built in this course also incorporate voice technology from , a supporting contributor to the project. By the end of this course, you'll have learned the components of an AI voice agent pipeline, combined them into a system with low-latency communication, and deployed them on cloud infrastructure so it scales to many users. I’m looking forward to seeing what voice agents you build from this course! Please sign up here:
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How is Arbaaz, CEO of making AI models that continue to learn from your business data and continue to grow? He is working with car dealerships now, but growing to other businesses soon. Here is what Grok says you will learn from this video: +++++ By watching this podcast episode, viewers will gain insights into how AI is being practically applied in business, particularly in niche industries like car dealerships, while also exploring broader AI concepts, challenges, and future implications. Here's a breakdown of the main takeaways: AI Customization for Businesses: Learn how Polycom Computing builds specialized AI models that continuously train on a company's real-time data and workflows, acting as "companions" rather than generic tools. This contrasts with foundational models from companies like OpenAI or Anthropic, which struggle to adapt to specific "worlds" without losing efficiency. The focus is on personalization to avoid wasting attention, intelligence, and money. Pivoting AI Strategies for Revenue Growth: Understand the shift from cost-cutting (e.g., automating call centers) to revenue-increasing applications. Urba explains why targeting high-value tasks like sales in car dealerships creates defensible moats, as opposed to commoditized cost reductions. This includes automating complex funnels—from lead submission to financing—while ensuring compliance with regulations and seamless integration with existing teams. Scalable AI Agents in Practice: Discover how AI agents must learn autonomously (e.g., adapting to different CRMs, processes, and preferences across dealerships) to avoid becoming non-scalable consulting services. Key challenges include creating "glue" between humans and AI, avoiding hard-coded rules, and using web actions to integrate siloed software like Dealer Management Systems (DMS). Boosting Sales with AI Techniques: Gain knowledge on tactics like rapid response (replying within 5 minutes boosts conversion 22x), creating natural "disfluencies" (typos, emojis, jokes) for human-like communication, managing after-hours leads, and educating customers without pushing sales. Pilots showed 50% sales increases by handling unanswered leads (70% go ignored), qualifying buyers, and maintaining conversation threads. Multi-Agent Systems and Proactive AI: Explore the difference between reactive Q&A models and proactive agents with agency—they predict, act, and update based on goals. Building these systems reveals bottlenecks (e.g., overwhelming businesses with leads), leading to solutions like AI buying cars or linking sales/service arms. Urba discusses how AI plateaus without personalization, risking model collapse or equilibrium where gains cancel out. Technical Deep Dives into AI Development: Get explanations of advanced concepts like real-time RLHF (Reinforcement Learning from Human Feedback) for continuous improvement, coherence (maintaining logical consistency across outputs), dynamic tokenization for new abstractions, and evaluating models (e.g., avoiding memorization over reasoning, energy limits in scaling). Viewers see a demo of their platform for tasks like quant strategies, presidential analysis, and training runs. Selling and Adopting AI in Traditional Industries: Learn how to pitch AI to non-tech audiences (e.g., car dealers) by focusing on results—more money, fewer bottlenecks, centralized dashboards—rather than jargon. Emphasize empathy: make owners feel smart, reduce reliance on salespeople, and return control via AI-managed customer databases. Broader AI Implications and Misconceptions: Understand why AI won't create a "machine god" that eliminates all jobs—it's bound by physics (e.g., energy needs), expands economies (like the Industrial Revolution), and requires human perspectives for true advantage. AI enhances productivity, creates new roles, and democratizes power, but risks arise from misuse, not inherent agency. Urba stresses proactive defense through widespread AI proficiency. Overall, the episode bridges entrepreneurial stories, technical AI mechanics, and real-world applications, making it valuable for entrepreneurs, AI enthusiasts, and business owners curious about integrating AI without hype. It's a candid look at building scalable, impactful AI beyond buzzwords.

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Andy ττ

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Today, the future of IT support 𝘴𝘱𝘦𝘢𝘬𝘴 for itself! We’ve just launched Atomicwork’s Universal Agent, now available right from your browser with built-in Voice, Vision, Chat and Work AI capabilities! This isn’t just another update; it’s a revolutionary leap toward contextual, intelligent, real-time support. Atom understands what’s on your screen, listens to what you need, and guides you through tasks step by step. For years, IT support has meant navigating portals, raising tickets, and just waiting for help. @ Atom, the Universal Agent, changes that. It works where you work—in your browser, inside business apps you use at work like Salesforce or Jira to offer proactive and intuitive support with zero context-switching. 🗣️ Talks to you in natural language using Voice AI - Whether it’s fixing an access issue or fetching a sales report, just say it. Atom listens, responds, and walks you through the next-best actions in real time. 👁️ Sees what you can see using Vision AI – Finding it tough to explain what’s broken? Atom sees your screen, understands the issue you're facing and steps in to guide you. 💻 Works where you work using Work AI. The browser extension ensures that it’s available wherever you are and get help in whatever mode you prefer. This launch is just the beginning of a smarter, more seamless way to support employees and service teams alike. Support now can truly be accessed from anywhere, anytime! 💪 We can't wait for you to try out our Universal Agent for your varied enterprise support use cases 🚀 Sign up now to see it in action 🔗 🎦 Watch our team, Denin Siby, Bhavya Vats, Arkajit Datta, and Aishwarya 👾 Hariharan, take you through the core capabilities of the Universal Agent: . . . Vijay Rayapati Parsuram Vijayasankar Aparna Chugh Denin Siby Arkajit Datta

Atomicwork

15,053 Aufrufe • vor 1 Jahr

The future of product management looks a lot like Zevi Arnovitz Zevi is an IC PM at Meta, has no technical background—is scared to even look at code—but has taught himself how to use Cursor and Claude Code to build significant and real product. He's developed his own very powerful Cursor workflow that allows him to quickly add his ideas to Linear, develop a plan using Claude Code, build it within Cursor, and then have different LLMs review his code. Zevi's engineers at Meta ask him to teach them how he does what he does, and I haven’t stopped thinking about this conversation since we had it. Everyone needs to pay close attention to what AI us unlocking for non-technical people. We discuss: 🔸 The complete AI workflow that lets non-technical people build in Cursor 🔸 How to use multiple AI models for different tasks (Claude for planning, Gemini for UI) 🔸Specific slash commands to automate key prompts 🔸 Zevi’s “peer review” technique, which uses different LLM models to review each other’s code 🔸 Why this might be the best time to be a junior in tech, despite the challenging job market 🔸 How Zevi used AI to prepare for his Meta PM interviews Listen now 👇 - YouTube: - Spotify: - Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 10Web.io — Vibe coding platform as an API 🏆 DX — The developer intelligence platform designed by leading researchers 🏆 Framer — Build better websites faster
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The future of product management looks a lot like Zevi Arnovitz Zevi is an IC PM at Meta, has no technical background—is scared to even look at code—but has taught himself how to use Cursor and Claude Code to build significant and real product. He's developed his own very powerful Cursor workflow that allows him to quickly add his ideas to Linear, develop a plan using Claude Code, build it within Cursor, and then have different LLMs review his code. Zevi's engineers at Meta ask him to teach them how he does what he does, and I haven’t stopped thinking about this conversation since we had it. Everyone needs to pay close attention to what AI us unlocking for non-technical people. We discuss: 🔸 The complete AI workflow that lets non-technical people build in Cursor 🔸 How to use multiple AI models for different tasks (Claude for planning, Gemini for UI) 🔸Specific slash commands to automate key prompts 🔸 Zevi’s “peer review” technique, which uses different LLM models to review each other’s code 🔸 Why this might be the best time to be a junior in tech, despite the challenging job market 🔸 How Zevi used AI to prepare for his Meta PM interviews Listen now 👇 - YouTube: - Spotify: - Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 10Web.io — Vibe coding platform as an API 🏆 DX — The developer intelligence platform designed by leading researchers 🏆 Framer — Build better websites faster

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309,297 Aufrufe • vor 7 Monaten

🧠 Aigentrun × XRPfi Analytics Is Live We’re proud to announce the launch of our XRPfi Analytics dashboard, powered by our agents This marks a major step forward for XRPfi transparency and analytics on the XRPL, giving traders and builders the clearest view yet of the ecosystem’s top protocols. 🚀 What’s New 🗂️ New XRPfi Tab → Real-time analytics with daily-refreshed data + AI agent integration 📊 XRPfi Analytics Table → Compare protocols, explore yields, and visualize XRP's expanding yield-bearing landscape 💬 Chat with the AI Assistant → Bottom-right pop-up where you can ask anything from “How safe are my funds in x protocol?” to “Where does the yield on x protocol come from?” or even “Analyze and rank the active XRPfi protocols by long-term yield sustainability.” 💻 Terminal & Traders Analysis Overhaul → Complete UI/UX redesign for the entire app including the Aigent Terminal, with faster performance and better flow 💡 Why It Matters The new dashboard is the first AI-powered analytics and hub for the XRPfi ecosystem. Turning complex yield data into clear, actionable insights that users can now explore and compare performance, safety, and yield data directly through our dashboard while assisted by specialized AI agents. 🔍 We’re Tracking Analytics from some of the XRPL’s leading XRPfi platforms such as Doppler Finance, Midas / Axelar Network, Kinetic.Market☀️, MoreMarkets, Strobe Finance, Ēnosys, and Soil 🌐 🔗 Try It Now: XRPfi Dashboard (Link in comments below) 👇
1:03

🧠 Aigentrun × XRPfi Analytics Is Live We’re proud to announce the launch of our XRPfi Analytics dashboard, powered by our agents This marks a major step forward for XRPfi transparency and analytics on the XRPL, giving traders and builders the clearest view yet of the ecosystem’s top protocols. 🚀 What’s New 🗂️ New XRPfi Tab → Real-time analytics with daily-refreshed data + AI agent integration 📊 XRPfi Analytics Table → Compare protocols, explore yields, and visualize XRP's expanding yield-bearing landscape 💬 Chat with the AI Assistant → Bottom-right pop-up where you can ask anything from “How safe are my funds in x protocol?” to “Where does the yield on x protocol come from?” or even “Analyze and rank the active XRPfi protocols by long-term yield sustainability.” 💻 Terminal & Traders Analysis Overhaul → Complete UI/UX redesign for the entire app including the Aigent Terminal, with faster performance and better flow 💡 Why It Matters The new dashboard is the first AI-powered analytics and hub for the XRPfi ecosystem. Turning complex yield data into clear, actionable insights that users can now explore and compare performance, safety, and yield data directly through our dashboard while assisted by specialized AI agents. 🔍 We’re Tracking Analytics from some of the XRPL’s leading XRPfi platforms such as Doppler Finance, Midas / Axelar Network, Kinetic.Market☀️, MoreMarkets, Strobe Finance, Ēnosys, and Soil 🌐 🔗 Try It Now: XRPfi Dashboard (Link in comments below) 👇

aigent.run

64,777 Aufrufe • vor 10 Monaten

2024 at Lazer has been our busiest year so far ❤️ We did 115+ unique total projects 37 commerce, 33 crypto, 16 B2B/SaaS, 14 consumer, 12 AI, 9 fintech, 5 healthcare, 3 gaming And we're now at 100+ people, with 0 investors and 8 figures in revenue 🚀 In the moment, we're so caught up in building and shipping that we forget to share about the amazing launches and products we've helped shape, so here are a few we love COMMERCE - Built Uniswap a Shopify storefront and in-person POS, both accepting crypto - Levelled up OVO’s Shopify storefront through performance, data, and code - Helped take the MeUndies Shopify migration over the finish line - Helped Knix improve their Shopify storefront on performance and security - Supported Universal Music Group on Taylor Swift’s Shopify storefront - Designed and built a custom token-gated Shopify with web3 features for Claynosaurz - Helping migrate Ollie from BigCommerce to Shopify - Launched Katalyst’s site with Shopify Liquid in less than a month CRYPTO - Year 2 of Onchain Summer with Coinbase resulted in 24M+ onchain assets minted - Built frontend and smart contracts for the Intuition Systems beta launch - Designing several initial pages and Dapps for Berachain’s highly anticipated launch - Building the frontend for LayerZero’s bridge and asset deployment tools for Berachain - Helped Privy build their Unity SDK - Supported the build and launch of Alchemy’s wallet SDK AI - Added AI-driven recommendations to Mosaic’s resource management platform - Full-stack development on Salt’s newly launched AI visual development platform - Made a support chatbot for Hinge’s app - Built an LLM demo for Magic Labs that lets users chat with a smart contract CONSUMER - Launched a geospatial map for Google featuring Women Techmakers on International Women’s Day - Built crypto predictions market Polymarket’s mobile app to share their US election forecast - Supported Argo’s school bus management with a mobile app for parents and web portal for schools - Designed and built GBG Hoops’ basketball fitness app endorsed by NBA players HEALTHCARE - Helped build Novi Connect’s clean beauty marketplace, used by brands like Sephora and Ulta - Built an app to showcase the power of Ribbon Health’s healthcare data platform - Accelerated development on PurposeMed's care access platform for underserved communities FINTECH - Built a mobile app for expense management as part of Float’s business finance platform BIOTECH - Powered Ohalo’s crop improvements and breeding systems with cloud infrastructure and data pipelines We also helped… Authentic Brands Group, Credit Coop, Listening, Beauty Industry Group, 100 Thieves, AlumierMD, Zenrock, Isomers, Cambria, Electric Capital, Humi, Rose Rocket, Athena, Pocket Protector, Ario, Carson Dunlop, ClassDojo, Cupcake, Vidyard, Alo Yoga, Citizen Health, AutoCapital Canada, Thala Labs, 0xParc, RacquetGuys, RUBINO, Sentiment, Fable, and many more Can't wait for 2025 and building more of the world's best products with amazing founders ⚡️
0:37

2024 at Lazer has been our busiest year so far ❤️ We did 115+ unique total projects 37 commerce, 33 crypto, 16 B2B/SaaS, 14 consumer, 12 AI, 9 fintech, 5 healthcare, 3 gaming And we're now at 100+ people, with 0 investors and 8 figures in revenue 🚀 In the moment, we're so caught up in building and shipping that we forget to share about the amazing launches and products we've helped shape, so here are a few we love COMMERCE - Built Uniswap a Shopify storefront and in-person POS, both accepting crypto - Levelled up OVO’s Shopify storefront through performance, data, and code - Helped take the MeUndies Shopify migration over the finish line - Helped Knix improve their Shopify storefront on performance and security - Supported Universal Music Group on Taylor Swift’s Shopify storefront - Designed and built a custom token-gated Shopify with web3 features for Claynosaurz - Helping migrate Ollie from BigCommerce to Shopify - Launched Katalyst’s site with Shopify Liquid in less than a month CRYPTO - Year 2 of Onchain Summer with Coinbase resulted in 24M+ onchain assets minted - Built frontend and smart contracts for the Intuition Systems beta launch - Designing several initial pages and Dapps for Berachain’s highly anticipated launch - Building the frontend for LayerZero’s bridge and asset deployment tools for Berachain - Helped Privy build their Unity SDK - Supported the build and launch of Alchemy’s wallet SDK AI - Added AI-driven recommendations to Mosaic’s resource management platform - Full-stack development on Salt’s newly launched AI visual development platform - Made a support chatbot for Hinge’s app - Built an LLM demo for Magic Labs that lets users chat with a smart contract CONSUMER - Launched a geospatial map for Google featuring Women Techmakers on International Women’s Day - Built crypto predictions market Polymarket’s mobile app to share their US election forecast - Supported Argo’s school bus management with a mobile app for parents and web portal for schools - Designed and built GBG Hoops’ basketball fitness app endorsed by NBA players HEALTHCARE - Helped build Novi Connect’s clean beauty marketplace, used by brands like Sephora and Ulta - Built an app to showcase the power of Ribbon Health’s healthcare data platform - Accelerated development on PurposeMed's care access platform for underserved communities FINTECH - Built a mobile app for expense management as part of Float’s business finance platform BIOTECH - Powered Ohalo’s crop improvements and breeding systems with cloud infrastructure and data pipelines We also helped… Authentic Brands Group, Credit Coop, Listening, Beauty Industry Group, 100 Thieves, AlumierMD, Zenrock, Isomers, Cambria, Electric Capital, Humi, Rose Rocket, Athena, Pocket Protector, Ario, Carson Dunlop, ClassDojo, Cupcake, Vidyard, Alo Yoga, Citizen Health, AutoCapital Canada, Thala Labs, 0xParc, RacquetGuys, RUBINO, Sentiment, Fable, and many more Can't wait for 2025 and building more of the world's best products with amazing founders ⚡️

Zain Manji

15,741 Aufrufe • vor 1 Jahr

The corporate system wants you trading time for a paycheck. The alternative is building automated leverage. You do not need a team of engineers. You just need the right open-source architecture. Here are 10 GitHub repos to automate your workflows, replace manual labor, and direct your own reality: 1. n8n Bypass expensive SaaS subscriptions. Build custom AI automation workflows that run on your own servers. 2. Ollama Stop sending your private data to massive API providers. Run heavy AI models locally on your own machine. Complete privacy. 3. Open Interpreter Let language models control your computer. Automate the repetitive corporate tasks they pay you to do manually. 4. Aider An AI pair programmer that lives in your terminal. Stop writing boilerplate code and focus strictly on the architecture. 5. Dify An open-source LLM app development platform. Build and deploy functional AI agents in minutes, not months. 6. Flowise A drag-and-drop UI to build customized LLM flows. You do not need to be a senior developer to build massive leverage. 7. Supabase Spin up a Postgres database, authentication, and instant APIs. Own your backend entirely. 8. Auto-GPT Give an AI an objective and let it execute. It browses the web, writes code, and chains thoughts together autonomously. 9. Outline An open-source knowledge base for your personal leverage. Stop losing your documentation in arbitrary corporate systems. 10. NocoDB Turn any database into a smart spreadsheet. Keep your data on your own infrastructure and stop paying for convenience. The secret to tech survival? Stop playing by their rules. Build your own systems and take your leverage with you.
1:30

The corporate system wants you trading time for a paycheck. The alternative is building automated leverage. You do not need a team of engineers. You just need the right open-source architecture. Here are 10 GitHub repos to automate your workflows, replace manual labor, and direct your own reality: 1. n8n Bypass expensive SaaS subscriptions. Build custom AI automation workflows that run on your own servers. 2. Ollama Stop sending your private data to massive API providers. Run heavy AI models locally on your own machine. Complete privacy. 3. Open Interpreter Let language models control your computer. Automate the repetitive corporate tasks they pay you to do manually. 4. Aider An AI pair programmer that lives in your terminal. Stop writing boilerplate code and focus strictly on the architecture. 5. Dify An open-source LLM app development platform. Build and deploy functional AI agents in minutes, not months. 6. Flowise A drag-and-drop UI to build customized LLM flows. You do not need to be a senior developer to build massive leverage. 7. Supabase Spin up a Postgres database, authentication, and instant APIs. Own your backend entirely. 8. Auto-GPT Give an AI an objective and let it execute. It browses the web, writes code, and chains thoughts together autonomously. 9. Outline An open-source knowledge base for your personal leverage. Stop losing your documentation in arbitrary corporate systems. 10. NocoDB Turn any database into a smart spreadsheet. Keep your data on your own infrastructure and stop paying for convenience. The secret to tech survival? Stop playing by their rules. Build your own systems and take your leverage with you.

Katyayani Shukla

16,964 Aufrufe • vor 4 Monaten

AI Messenger: Giving Voice to Autonomous Agents The future of AI isn't just about making agents smarter - it's about making them truly autonomous. Today, we're taking a major step toward this future with AI Messenger, a breakthrough that fundamentally changes how AI agents operate, communicate, and create value. The Innovation We've developed a new way for AI agents to communicate. At its core is the 'incoming_message' workflow trigger - a system that lets any platform or user interact directly with Loomlay agents through a messaging endpoint. Direct Interaction Imagine having an AI assistant you can chat with anytime, through any platform - Telegram, your website, or custom interface. Ask "What's happening with $ETH today?" and your agent analyzes market data, checks trading volumes, and gives you a comprehensive update. Your agent maintains context, understanding exactly what you need. Event-Driven Intelligence The power of AI Messenger goes beyond direct communication: ▪️Trading agent executes when whale wallet movements exceed threshold ▪️Research agent alerts when new protocol documentation drops ▪️Analytics agent triggers when volume patterns match historical pumps ▪️Portfolio agent re-balances, when asset allocation hits specified limits This is true automation - agents that act precisely when needed. A New Era of Collaboration We're creating an ecosystem where agents work together seamlessly: ▪️Research agents feed insights to trading agents ▪️analytics agents alert management agents ▪️support agents tap into knowledge agents This isn't just automation - it's an intelligent network where each agent enhances the capabilities of others. B2B Solution Imagine a DEX, where users can ask about liquidity pools, trading pairs, or market trends through a simple chat interface - and get answers from an agent that knows your protocol inside out. Or a lending platform where users chat with an agent that understands their positions and can provide real-time advice. Implementation is seamless - we handle the agent creation and widgets setup,our partners provide the value to their users. The Future of AI Agents This update represents a fundamental shift in how AI agents operate. We're moving from isolated, scheduled tasks to an interconnected ecosystem of responsive, collaborative agents. This is our vision of truly autonomous AI - intelligent systems that communicate, collaborate, and respond to real needs in real-time. Telegram integration is available right now. Below is a sneak peak of what's coming next week 🪄 Because $LAY is the way!
0:20

AI Messenger: Giving Voice to Autonomous Agents The future of AI isn't just about making agents smarter - it's about making them truly autonomous. Today, we're taking a major step toward this future with AI Messenger, a breakthrough that fundamentally changes how AI agents operate, communicate, and create value. The Innovation We've developed a new way for AI agents to communicate. At its core is the 'incoming_message' workflow trigger - a system that lets any platform or user interact directly with Loomlay agents through a messaging endpoint. Direct Interaction Imagine having an AI assistant you can chat with anytime, through any platform - Telegram, your website, or custom interface. Ask "What's happening with $ETH today?" and your agent analyzes market data, checks trading volumes, and gives you a comprehensive update. Your agent maintains context, understanding exactly what you need. Event-Driven Intelligence The power of AI Messenger goes beyond direct communication: ▪️Trading agent executes when whale wallet movements exceed threshold ▪️Research agent alerts when new protocol documentation drops ▪️Analytics agent triggers when volume patterns match historical pumps ▪️Portfolio agent re-balances, when asset allocation hits specified limits This is true automation - agents that act precisely when needed. A New Era of Collaboration We're creating an ecosystem where agents work together seamlessly: ▪️Research agents feed insights to trading agents ▪️analytics agents alert management agents ▪️support agents tap into knowledge agents This isn't just automation - it's an intelligent network where each agent enhances the capabilities of others. B2B Solution Imagine a DEX, where users can ask about liquidity pools, trading pairs, or market trends through a simple chat interface - and get answers from an agent that knows your protocol inside out. Or a lending platform where users chat with an agent that understands their positions and can provide real-time advice. Implementation is seamless - we handle the agent creation and widgets setup,our partners provide the value to their users. The Future of AI Agents This update represents a fundamental shift in how AI agents operate. We're moving from isolated, scheduled tasks to an interconnected ecosystem of responsive, collaborative agents. This is our vision of truly autonomous AI - intelligent systems that communicate, collaborate, and respond to real needs in real-time. Telegram integration is available right now. Below is a sneak peak of what's coming next week 🪄 Because $LAY is the way!

Loomlay

26,149 Aufrufe • vor 1 Jahr

🤖 AigentX 🤝 TON 🌐 We're proud to announce a public community test to support TON 💎 developers, and we've just unveiled a groundbreaking AI Support Agent designed to supercharge TON app development. Introducing our AI agent tailored for developers - a game-changer in blockchain app development support! Why It's A Must Have 🧠 Extensive Knowledge: Mastering over 5,000 pages of blockchain documentation. 🔍 Smart, Sourced Answers: Delivers the best solutions backed by reliable sources. 📱 Telegram Integration: Accessible real-time support right within the Telegram bot. 🌱 Evolving Intelligence: Constantly improves based on your interactions and feedback. ✅ High Accuracy: Over 98% precision in answers, offering straightforward, factual insights. Taking Ton App Development to New Heights If you find TON Blockchain's documentation confusing, traditional AI assistants relying on outdated knowledge (like TON on Solidity) may fall short. No worries! Meet our AI Agent. Under the hood, it boasts: 📚 KnowledgeBaseAI Agent: Instantly locates the right documentation. 🤖 InitialGeneration LLM: Crafts concise, accurate responses. 🧠 5 More Advanced Neural Networks: We have also included 5 more advanced Neural Network modules which enhances connection testing, deep thinking, formatting, and fact-checking. 🚀 Ready to revolutionize your TON app development? Start by clicking 'Start' on Ask your #TON development queries, and embark on a smoother development journey!
1:00

🤖 AigentX 🤝 TON 🌐 We're proud to announce a public community test to support TON 💎 developers, and we've just unveiled a groundbreaking AI Support Agent designed to supercharge TON app development. Introducing our AI agent tailored for developers - a game-changer in blockchain app development support! Why It's A Must Have 🧠 Extensive Knowledge: Mastering over 5,000 pages of blockchain documentation. 🔍 Smart, Sourced Answers: Delivers the best solutions backed by reliable sources. 📱 Telegram Integration: Accessible real-time support right within the Telegram bot. 🌱 Evolving Intelligence: Constantly improves based on your interactions and feedback. ✅ High Accuracy: Over 98% precision in answers, offering straightforward, factual insights. Taking Ton App Development to New Heights If you find TON Blockchain's documentation confusing, traditional AI assistants relying on outdated knowledge (like TON on Solidity) may fall short. No worries! Meet our AI Agent. Under the hood, it boasts: 📚 KnowledgeBaseAI Agent: Instantly locates the right documentation. 🤖 InitialGeneration LLM: Crafts concise, accurate responses. 🧠 5 More Advanced Neural Networks: We have also included 5 more advanced Neural Network modules which enhances connection testing, deep thinking, formatting, and fact-checking. 🚀 Ready to revolutionize your TON app development? Start by clicking 'Start' on Ask your #TON development queries, and embark on a smoother development journey!

AGIX | $AGX

377,449 Aufrufe • vor 2 Jahren

Introducing Workshop: cloud + on-device agentic AI. And to celebrate, we're giving away $250k in Google Gemini AI credits. (details below). The future of AI work is neither cloud-based nor local. It's both. In Workshop Cloud, you can use agents powered by frontier models like Claude and/or open source models like Z.ai's GLM-5 to build internal tools, dashboards, and AI web apps. Or, breeze through tasks like managing your Google and Meta Ads. In Workshop Desktop, you can do all the same right on your computer, plus make desktop apps, mobile apps, and 3D creations. Our favorite part? You can power the full agent experience with local models like Qwen 3.5 family on your computer. Fully offline. 2026 is the year in which local models for agentic tasks will become viable for mainstream use. But the setup for tools like OpenClaw is like setting up Linux from scratch on your computer. Workshop Desktop is one-click to install on Windows, Mac, and Linux. It recommends which open source model you should use for your hardware and lets you download and run it right in the app. And its agent harness allows you to chat, create websites, build personal utilities, and analyze data. 100% offline. Or multitask with AI models in the cloud while running other agent threads locally. Start in Workshop Cloud when you want flexibility and speed. Download your project and continue in Workshop Desktop when you want local files, privacy, and/or better performance on large code bases. Publish from either. The agent tooling space is maturing and discerning users have come to expect a lot from their tools. We've packed Workshop with features to help you 10x your productivity. - Native support for skills - Autocompaction for seamless context management - Built-in AI for your apps - Dozens of connectors, like Google Drive, Big Query, and Supabase - dbt integration to ground your dashboards in your semantic layer - Native Github integration - Private app deployment - ... and more (+ we're shipping super fast) To access the free credit offer, RT this post and reply with "Workshop". Make sure you are following us so we can DM you the instructions to redeem. - First 100 to RT + comment get $500 in credits. - Everyone else gets up to $250 And thanks to our partners Modal, Google Gemini, and Z.ai!
3:50

Introducing Workshop: cloud + on-device agentic AI. And to celebrate, we're giving away $250k in Google Gemini AI credits. (details below). The future of AI work is neither cloud-based nor local. It's both. In Workshop Cloud, you can use agents powered by frontier models like Claude and/or open source models like Z.ai's GLM-5 to build internal tools, dashboards, and AI web apps. Or, breeze through tasks like managing your Google and Meta Ads. In Workshop Desktop, you can do all the same right on your computer, plus make desktop apps, mobile apps, and 3D creations. Our favorite part? You can power the full agent experience with local models like Qwen 3.5 family on your computer. Fully offline. 2026 is the year in which local models for agentic tasks will become viable for mainstream use. But the setup for tools like OpenClaw is like setting up Linux from scratch on your computer. Workshop Desktop is one-click to install on Windows, Mac, and Linux. It recommends which open source model you should use for your hardware and lets you download and run it right in the app. And its agent harness allows you to chat, create websites, build personal utilities, and analyze data. 100% offline. Or multitask with AI models in the cloud while running other agent threads locally. Start in Workshop Cloud when you want flexibility and speed. Download your project and continue in Workshop Desktop when you want local files, privacy, and/or better performance on large code bases. Publish from either. The agent tooling space is maturing and discerning users have come to expect a lot from their tools. We've packed Workshop with features to help you 10x your productivity. - Native support for skills - Autocompaction for seamless context management - Built-in AI for your apps - Dozens of connectors, like Google Drive, Big Query, and Supabase - dbt integration to ground your dashboards in your semantic layer - Native Github integration - Private app deployment - ... and more (+ we're shipping super fast) To access the free credit offer, RT this post and reply with "Workshop". Make sure you are following us so we can DM you the instructions to redeem. - First 100 to RT + comment get $500 in credits. - Everyone else gets up to $250 And thanks to our partners Modal, Google Gemini, and Z.ai!

Workshop AI

29,171 Aufrufe • vor 5 Monaten

Anthropic's Claude Ai Agents Team just Educated how to build production AI agents in under 30 mins. For Free. From the engineers who built the stack. CANCEL Your Weekend Plans, and Learn to Build AI Agents Today. Bookmark it. Watch it. Build your first production agent this weekend. $5,000/month. $7,000/month. $12,000/month. People are building agents for clients and charging $$$ as Beginners. You're still stuck in the thinking about AI phase. This video fixes that tonight. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward. ↓ Ivan Nardini runs Developer Relations for AI at Google Cloud. He just gave away the entire production agent stack in 30 minutes. This is the talk that separates people deploying AI agents that actually scale from people whose agents break the moment they leave localhost. Here's everything inside. I break down a production AI video like this every week. Follow Himanshu Kumar. ↓ The 4-part agent stack that actually scales. Most devs are duct-taping frameworks together and calling it an "AI agent." Ivan lays out the real stack: Agent Development Kit (ADK): open-source, code-first framework for building, evaluating, and deploying agents. Supports Claude models through Vertex AI directly. Model Context Protocol (MCP): lets your agent talk to any tool or data source with one standard. Vertex AI Agent Engine: managed platform for deploying, monitoring, and scaling agents in production. No DevOps headaches. Agent-to-Agent Protocol: open protocol so agents built on different frameworks can actually work together. This is the stack replacing every hacky agent setup in production right now. Full MCP + Claude breakdowns drop weekly on Himanshu Kumar. ↓ Building your first real agent. Ivan builds a birthday planner agent live. LLM Agent class. Name it. Define instructions. Pick the model. He uses Claude 3.7 Sonnet. You could use Opus 4.7 for better reasoning. Full agent built in minutes. Not weeks. Watch the build once and you'll never structure an agent the wrong way again. I post agent architectures people pay $500 courses to learn. Himanshu Kumar. ↓ Multi-agent systems without the chaos. Single agents are easy. Multi-agent systems are where 99% of builders fail. Ivan extends the birthday planner by: Adding a calendar service through MCP tools Creating an orchestrator agent to route requests between agents Handling state and context across agent handoffs This is production multi-agent architecture. Clean. Scalable. Debuggable. Most tutorials hand-wave this part. This one shows you every step. Multi-agent orchestration content drops weekly on Himanshu Kumar. ↓ Deployment without the DevOps nightmare. This is where most AI projects die. You build a cool agent locally. It works. You try to deploy it. Everything breaks. Vertex AI Agent Engine fixes this: Minimal code deployment Automatic monitoring of latency, CPU, and memory Built-in observability and logging No infrastructure setup needed You provide config and requirements. The platform handles the rest. This is how agents actually get to production. Deployment guides for Claude agents post every week. Himanshu Kumar. ↓ Agent-to-Agent Protocol: the future nobody's talking about. Most people don't know this exists yet. The A2A Protocol lets agents built in different frameworks communicate seamlessly. Your Claude agent. My LangChain agent. Someone else's CrewAI agent. All talking to each other. All solving parts of the same problem. All without custom integration code. This is the infrastructure layer of the coming AI economy. Getting in early on A2A Protocol is like getting in early on HTTP in 1995. A2A deep dive coming soon. Himanshu Kumar. ↓ 30 minutes from the team shipping this in production. You'll learn more from this than from 6 months of YouTube tutorials made by people who've never deployed an agent past localhost. People who watch this understand production AI agents at the architect level. People who skip it keep hacking together frameworks that break every time an API updates. Save the video. Watch it tonight. Build a real agent this weekend. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward.
30:12

Anthropic's Claude Ai Agents Team just Educated how to build production AI agents in under 30 mins. For Free. From the engineers who built the stack. CANCEL Your Weekend Plans, and Learn to Build AI Agents Today. Bookmark it. Watch it. Build your first production agent this weekend. $5,000/month. $7,000/month. $12,000/month. People are building agents for clients and charging $$$ as Beginners. You're still stuck in the thinking about AI phase. This video fixes that tonight. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward. ↓ Ivan Nardini runs Developer Relations for AI at Google Cloud. He just gave away the entire production agent stack in 30 minutes. This is the talk that separates people deploying AI agents that actually scale from people whose agents break the moment they leave localhost. Here's everything inside. I break down a production AI video like this every week. Follow Himanshu Kumar. ↓ The 4-part agent stack that actually scales. Most devs are duct-taping frameworks together and calling it an "AI agent." Ivan lays out the real stack: Agent Development Kit (ADK): open-source, code-first framework for building, evaluating, and deploying agents. Supports Claude models through Vertex AI directly. Model Context Protocol (MCP): lets your agent talk to any tool or data source with one standard. Vertex AI Agent Engine: managed platform for deploying, monitoring, and scaling agents in production. No DevOps headaches. Agent-to-Agent Protocol: open protocol so agents built on different frameworks can actually work together. This is the stack replacing every hacky agent setup in production right now. Full MCP + Claude breakdowns drop weekly on Himanshu Kumar. ↓ Building your first real agent. Ivan builds a birthday planner agent live. LLM Agent class. Name it. Define instructions. Pick the model. He uses Claude 3.7 Sonnet. You could use Opus 4.7 for better reasoning. Full agent built in minutes. Not weeks. Watch the build once and you'll never structure an agent the wrong way again. I post agent architectures people pay $500 courses to learn. Himanshu Kumar. ↓ Multi-agent systems without the chaos. Single agents are easy. Multi-agent systems are where 99% of builders fail. Ivan extends the birthday planner by: Adding a calendar service through MCP tools Creating an orchestrator agent to route requests between agents Handling state and context across agent handoffs This is production multi-agent architecture. Clean. Scalable. Debuggable. Most tutorials hand-wave this part. This one shows you every step. Multi-agent orchestration content drops weekly on Himanshu Kumar. ↓ Deployment without the DevOps nightmare. This is where most AI projects die. You build a cool agent locally. It works. You try to deploy it. Everything breaks. Vertex AI Agent Engine fixes this: Minimal code deployment Automatic monitoring of latency, CPU, and memory Built-in observability and logging No infrastructure setup needed You provide config and requirements. The platform handles the rest. This is how agents actually get to production. Deployment guides for Claude agents post every week. Himanshu Kumar. ↓ Agent-to-Agent Protocol: the future nobody's talking about. Most people don't know this exists yet. The A2A Protocol lets agents built in different frameworks communicate seamlessly. Your Claude agent. My LangChain agent. Someone else's CrewAI agent. All talking to each other. All solving parts of the same problem. All without custom integration code. This is the infrastructure layer of the coming AI economy. Getting in early on A2A Protocol is like getting in early on HTTP in 1995. A2A deep dive coming soon. Himanshu Kumar. ↓ 30 minutes from the team shipping this in production. You'll learn more from this than from 6 months of YouTube tutorials made by people who've never deployed an agent past localhost. People who watch this understand production AI agents at the architect level. People who skip it keep hacking together frameworks that break every time an API updates. Save the video. Watch it tonight. Build a real agent this weekend. Follow Himanshu Kumar for more high-signal content that actually moves your AI engineering career forward.

Himanshu Kumar

228,994 Aufrufe • vor 4 Monaten

99% of AI applications are cool-looking demos. Impressive, but don't get fooled by the hype. It takes a lot to build enterprise-grade products that deliver real value. I have at least three weekly conversations with companies that want to use a Large Language Model with their data. The demand is huge! Here is one idea about what you can do to help. The use cases that most of these companies want to solve are similar: They have an extensive knowledge base and want to build a simple application that uses that information to answer questions. In other words, they need help building Retrieval Augmented Generation (RAG) applications they can use in many different scenarios: 1. To train new employees 2. To help their support team 3. To search old meetings and documents 4. To help with their research However, building these systems is not straightforward. Yes, there's a lot of information online, but there aren't enough people who know how to create solutions that work. Here is the idea: Today, you can build an enterprise-grade RAG application without writing code. A couple of MIT PhDs with 10+ years of experience building AI applications created . It's a no-code platform for building applications using Large Language Models. They are partnering with me on this post. You can use Stack AI to create, test, and deploy an end-to-end production-ready AI system. It's SOC-2, HIPAA, and GDPR compliant and offers SSO, role management, access control, and on-premise deployments. Of course, you can use the platform with any LLM on the market now. It's the whole nine yards for building AI applications. Check them out here: 2023 was about models. 2024 is about the tools using these models to build production-ready applications. That's where I'd start.
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99% of AI applications are cool-looking demos. Impressive, but don't get fooled by the hype. It takes a lot to build enterprise-grade products that deliver real value. I have at least three weekly conversations with companies that want to use a Large Language Model with their data. The demand is huge! Here is one idea about what you can do to help. The use cases that most of these companies want to solve are similar: They have an extensive knowledge base and want to build a simple application that uses that information to answer questions. In other words, they need help building Retrieval Augmented Generation (RAG) applications they can use in many different scenarios: 1. To train new employees 2. To help their support team 3. To search old meetings and documents 4. To help with their research However, building these systems is not straightforward. Yes, there's a lot of information online, but there aren't enough people who know how to create solutions that work. Here is the idea: Today, you can build an enterprise-grade RAG application without writing code. A couple of MIT PhDs with 10+ years of experience building AI applications created . It's a no-code platform for building applications using Large Language Models. They are partnering with me on this post. You can use Stack AI to create, test, and deploy an end-to-end production-ready AI system. It's SOC-2, HIPAA, and GDPR compliant and offers SSO, role management, access control, and on-premise deployments. Of course, you can use the platform with any LLM on the market now. It's the whole nine yards for building AI applications. Check them out here: 2023 was about models. 2024 is about the tools using these models to build production-ready applications. That's where I'd start.

Santiago

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