#AI application deployment
18 related articles
·3 min
Multi-Agent Communication & Collaboration in Feishu: A Complete Guide to Configuration and Group Chat Orchestration
Learn how to configure Open Cloud for multi-Agent communication, including session_visibility, agent_to_agent toggle, and whitelist setup, plus Feishu group chat orchestration for AI team collaboration.
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·3 min
Grill Me Skill: Let AI Interrogate You to Rapidly Extract Tacit Knowledge and Boost Project Efficiency
Learn how the Grill Me skill uses AI-driven systematic questioning to extract tacit knowledge, with checkpoint mechanisms to optimize context quality and boost first-iteration success from 70% to 90%.
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Legora: Building a Legal AI Interpreta…
·2 min
Legora: Building a Legal AI Interpretation Platform Powered by Claude
Legora chose Anthropic's Claude as its core AI engine to build intelligent interpretation tools for the legal industry. CEO Max Junestrand's "rising tide" strategy delivers precise legal analysis through application-layer innovation.
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·2 min
Gemini 3.5 Flash Teams Up with Antigravity: Multi-Agent Collaboration to Build an Entire City
Deep dive into how Gemini 3.5 Flash and Antigravity platform use multi-subagent architecture to design and build a complete virtual city from scratch.
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·3 min
Firebase Integrates with AI Studio: Four Core Capabilities for Production-Grade Agent Applications
Deep dive into Google Firebase's integration with AI Studio, covering four core capabilities—database auto-configuration, authentication, security rules drafting, and zero-config deployment—for production-grade AI agent apps.
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·4 min
Firebase AI Logic Update: Expanded Model Support and Enhanced Output Integrity Explained
Firebase AI Logic gets major updates at Google I/O, expanding AI model support and enhancing output integrity. Learn how these changes impact developers.
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·3 min
Replit Canvas: An AI Multimedia Creation Canvas Combining Image, Video, and Audio
Deep dive into Replit Canvas: multimodal AI generation for images, video, and audio, with sketch-to-image, WYSIWYG editing, and real-time collaboration.
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·2 min
Andrew Ng's Agent Skills Course Explained: Building Reusable Professional Skills for AI Agents
Deep dive into Andrew Ng's Agent Skills course with Anthropic, covering Skills architecture, progressive loading, MCP integration, and hands-on examples for building reusable AI agent skills.
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Tutorials·2 min
MCP Protocol in Practice: Building an AI Investment Analysis Agent with TradingView + Notion
A detailed guide on MCP protocol vs Skills, integrating TradingView and Notion MCPs to build an automated investment analysis Agent with market scanning, backtesting, and report generation.
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Tutorials·3 min
Fully Automated Invoice Reimbursement with Local AI Agent: From Process Breakdown to Deployment
How to build a fully automated invoice reimbursement system with local AI Agents, covering OCR, info extraction, and form generation with MinerU+Qwen3+Qianwen Po.
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Industry Insights·2 min
Decoding the U.S. AI Executive Order: Balancing Development, Safety, and Cyber Defense
Deep analysis of the U.S. AI Executive Order's three strategic pillars: developing top AI models, ensuring safety, and providing cybersecurity tools to trusted defenders.
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Tutorials
pnpm Monorepo Full-Stack AI Engineerin…
·2 min
pnpm Monorepo Full-Stack AI Engineering in Practice: Building a Multimodal Conversation System
Learn how to build a full-stack multimodal AI conversation system using pnpm Monorepo architecture, covering local model integration, image understanding, and streaming chat.
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Product Reviews·1 min
Tasi Harness: Local AI Agent for Browser Automation
Tasi Harness is a locally deployed AI Agent browser automation tool that drives browsers via natural language to complete searches, data collection, and form filling. A deep dive into its features, technical highlights, and use cases.
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Tutorials·2 min
Complete Breakdown of Andrew Ng's LangChain Course: Five Core Components and Hands-On Guide
Deep dive into Andrew Ng and Harrison Chase's LangChain course, covering the five core components—Models, Prompts, Indexes, Chains, and Agents—to help developers master LLM app development.
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Tutorials·3 min
Complete Breakdown of Andrew Ng's Agent Course: A Practical Guide to the Five Core Modules of AI Agent Development
Deep dive into Andrew Ng's viral AI Agent course covering five core modules: Reflection, Planning, Tool Use, Multi-Agent Collaboration, and Memory, with practical learning paths for LLM agent development.
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Deep Dives·2 min
What Is the MCP Protocol? Understanding the USB-C of the AI World
MCP (Model Context Protocol) is a unified standard for connecting AI models to external tools. This guide explains MCP's core concepts, practical value, and provides a quick-start tutorial.
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Tutorials·3 min
Enterprise Multi-Agent Development: Low-Code Platforms vs. Hand-Written Code — An In-Depth Comparison
In-depth comparison of two enterprise multi-agent development approaches: low-code platforms like Dify vs. hand-written code with LangGraph. Covers efficiency, flexibility, security, and prompt injection defense strategies.
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Product Reviews·2 min
LangBot: A Deep Dive into the 16K-Star Multi-Platform AI Bot Development Framework
An in-depth look at LangBot, an open-source production-grade AI bot platform supporting WeChat, DingTalk, Discord & more, with ChatGPT, DeepSeek, Agent, RAG & plugin capabilities.
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