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Most teams build backends by stitching together five or six different systems. Motia shows how simple it can be when one primitive powers everything. APIs, events, background jobs, workflows, AI agents, and real time streams all built with Steps. Works in JavaScript, TypeScript, and Python.

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13,121 просмотров • 7 месяцев назад •via X (Twitter)

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Mansa AI is an enterprise-grade AI + Web3 platform designed to move artificial intelligence from experimentation into real-world execution. Built for creators, developers, and businesses, it focuses on deploying AI that actually works across modern digital systems, not just in isolated demos. 🚀 Production-ready AI infrastructure Mansa AI enables teams to deploy AI systems designed for live environments, handling real workflows, real data, and real operational demands without constant manual oversight. 🧠 Autonomous AI agents At its core, Mansa AI allows users to build autonomous agents that automate decision-making, coordinate tasks, monitor live signals, and execute complex workflows across dynamic environments. ⚙️ Fully customizable logic Agents can be configured with custom behaviors, triggers, and responses. From content generation and analytics to operational automation and intelligent orchestration, logic adapts to specific business strategies. 🔗 Web3 and off-chain integration Mansa AI bridges blockchain ecosystems with traditional systems, enabling cross-chain coordination, smart contract interactions, and seamless integration with existing enterprise infrastructure. 📊 Real-world use cases The platform supports automation for operations, customer engagement, analytics, data pipelines, content workflows, and AI-driven optimization across products and teams. 📈 Built for scale Whether launching as a startup or deploying across enterprise systems, Mansa AI is designed to scale AI operations without adding complexity or fragmentation. Mansa AI transforms artificial intelligence into deployable infrastructure. By combining autonomy, customization, interoperability, and scalability, it enables teams to own, operate, and grow intelligent systems that deliver real value in production environments.

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Today, Anthropic announced plugins for Claude Cowork, launching 11 pre-built plugins designed around real work. Now, AI can query and take action directly in systems like Box, rather than starting from scratch every time. Plugins make context persistent and workflows repeatable. Learn how it works:

Today, Anthropic announced plugins for Claude Cowork, launching 11 pre-built plugins designed around real work. Now, AI can query and take action directly in systems like Box, rather than starting from scratch every time. Plugins make context persistent and workflows repeatable. Learn how it works:

Box

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The next wave of AI will not be one model doing everything. It will be specialized agents built around real domains, real knowledge, and real usage. That is what OptimAI is building with Search, Claw, Persona Agents, and Marketplace. Create an agent. Give it expertise. Publish it. Let it be used. That is how intelligence becomes infrastructure. 💡Build yours at:

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OptimAI Network

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Robert Sasu | dev/acc

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AI agents are blind without real-time BNBCHAIN analytics. ClipX fixes that. ClipX OpenClaw skill + lightweight Python client, it delivers: • TVL • Fees • Revenue • Social Hype • Meme rankings • Market insights and different types of data in-real time All in one stream - fast, simple, agent-ready. Watch it in action 👇 BNB Chain Four.meme-華語 Four.Meme Fora pieverse

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ClipX

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New course: Nvidia's NeMo Agent Toolkit: Making Agents Reliable, taught by Brian McBrayer 🐬 from NVIDIA. Many teams struggle to turn agent demos into reliable systems that are ready for production. This short course teaches you to harden agentic workflows into reliable systems using Nvidia's open-source NeMo Agent Toolkit (NAT). Whether you built your agent in raw Python or using a framework like LangGraph, or CrewAI, NAT provides building blocks for observability, evaluation, and deployment that turn proofs-of-concept into production-ready systems. NAT makes it easy to troubleshoot and optimize agent performance with execution traces, systematic evaluations, and CI/CD integration. Skills you'll gain: - Build configuration-driven agent workflows with REST APIs and minimal code - Add observability with tracing to visualize agent reasoning and debug performance bottlenecks - Create systematic evaluations using gold-standard datasets to measure and improve agent reliability - Deploy multi-agent systems with authentication, rate limiting, and professional web interfaces - Orchestrate agents from different frameworks to collaborate on complex tasks Join and learn how to turn agent demos into reliable systems!

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Andrew Ng

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Santiago

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Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.

Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.

Santiago

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CyrilXBT

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Santiago

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Just watched a demo of Merge Agent Handler and this actually looks pretty useful if you’re building AI agents. Most agents can generate responses, but getting them to actually take actions across real tools is still messy. Integrations are one thing, but handling auth, permissions, and security usually makes it way more complicated than it should be. What I liked is that it feels built for real workflows — you can actually see what your agent is doing instead of just hoping it works. Feels like a practical layer between AI agents and real work getting done. Worth checking out:

Just watched a demo of Merge Agent Handler and this actually looks pretty useful if you’re building AI agents. Most agents can generate responses, but getting them to actually take actions across real tools is still messy. Integrations are one thing, but handling auth, permissions, and security usually makes it way more complicated than it should be. What I liked is that it feels built for real workflows — you can actually see what your agent is doing instead of just hoping it works. Feels like a practical layer between AI agents and real work getting done. Worth checking out:

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Most people will spend 4 hours tonight consuming. Zero creating. Then wonder why nothing changes. 1) Scroll until you fall asleep. 2) Or watch this. A Stanford lecture on Agentic AI that teaches you more about how AI automation actually works than 6 months of copying Make and n8n tutorials. Tool calling. Multi-step workflows. Planning. Reflection. The foundations behind every automation system that actually works. Most people learn this by copying tutorials blindly. Stanford teaches you WHY agents work the way they do. Watch the lecture first. Then go through 9 real build projects across 2 weeks: APIs. Webhooks. LLM integration. AI workflows. No theory. Just build. The people who do this weekend will understand AI automation at a level that makes everything they build after faster, cleaner, and more powerful. The people who skip it will still be copying tutorials in 2027 wondering why nothing they build actually works. Completely free. Bookmark this before you open Netflix.

Most people will spend 4 hours tonight consuming. Zero creating. Then wonder why nothing changes. 1) Scroll until you fall asleep. 2) Or watch this. A Stanford lecture on Agentic AI that teaches you more about how AI automation actually works than 6 months of copying Make and n8n tutorials. Tool calling. Multi-step workflows. Planning. Reflection. The foundations behind every automation system that actually works. Most people learn this by copying tutorials blindly. Stanford teaches you WHY agents work the way they do. Watch the lecture first. Then go through 9 real build projects across 2 weeks: APIs. Webhooks. LLM integration. AI workflows. No theory. Just build. The people who do this weekend will understand AI automation at a level that makes everything they build after faster, cleaner, and more powerful. The people who skip it will still be copying tutorials in 2027 wondering why nothing they build actually works. Completely free. Bookmark this before you open Netflix.

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How One Man Is Using Hebrew, Arabic, and English To Heal The Middle East How much good can you do by speaking 3 languages fluently?! Yirmiyahu speaks Arabic, Hebrew, and English - and is determined to heal the divide between Jews and Arabs, one conversation at a time. He dives into how using his background can be used to build trust, and shows us all how we can lead by example. Share this story with anyone who will feel inspired by using the powers of language for good! Follow buildersofmideast for more 🙌

buildersofmideast

36,144 просмотров • 10 месяцев назад

Unitree G1 now has a cluster control system that lets many robots work together with precise coordination. It connects multiple robots on one network, even across different systems and hardware. AI plans and executes actions in real time, making all robots move in sync like one system.

Unitree G1 now has a cluster control system that lets many robots work together with precise coordination. It connects multiple robots on one network, even across different systems and hardware. AI plans and executes actions in real time, making all robots move in sync like one system.

Space and Technology

23,834 просмотров • 2 месяцев назад