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A systematic overview of the AI Agent tech stack: RAG retrieval, Agent planning, MCP protocol, AI Gateway, and observability — helping developers build production-grade AI systems.

A deep dive into LangGraph multi-agent architecture — covering hierarchical, network, and pipeline patterns with three hands-on projects using LangGraph 0.3.

A systematic breakdown of LangChain's six core modules (Models/Prompts/Chains/Memory/RAG/Agent) and LangGraph's state graph, persistence, and HITL — with production deployment tips.

A comprehensive guide to AI Agent development: covering Agent vs. Chatbot differences, framework selection, tool calling design, RAG pipeline setup, and production deployment best practices.

A deep dive into Databricks Agent Framework (Mosaic AI): unify LangGraph/OpenAI agents via ChatAgent, log & evaluate with MLflow, version with Unity Catalog, and deploy Model Serving Endpoints for production AI agents.

Databricks tech lead Sandy shares a five-pillar framework for production-grade AI Agents—evaluation, observability, data foundation, orchestration, and governance—with a £85K retail banking failure case to bridge the demo-to-production gap.

Deep dive into NVIDIA AI-Q Blueprint production deployment on Oracle Cloud Infrastructure, covering NIM microservices, RAG architecture, multi-agent orchestration, and OCI GPU selection for enterprise AI agents.

Deep dive into NVIDIA AI-Q Blueprint production deployment on Oracle Cloud Infrastructure, covering NIM microservices, RAG architecture, multi-agent orchestration, and OCI GPU selection.

A deep dive into AI Agent architecture and engineering practices, covering tool design, ReAct execution patterns, Vercel deployment, and production considerations to bridge the prototype-to-production gap.

Complete guide to commercial AI agent development from scratch, covering requirements analysis, architecture design (ReAct framework, deep search, intent recognition), hands-on Coze platform implementation, workflow creation, and production deployment.

A complete learning path for AI Agent development covering core architecture, ReAct paradigm, multi-agent collaboration, RAG integration, and lightweight deployment to guide developers from basics to production.
TutorialsA complete guide to building a financial analysis Agent system from scratch using Cursor AI and MCP protocol, covering three-layer architecture design, MCP Server development, and production deployment.
Product ReviewsPhrony is an infrastructure platform for AI Agent production deployment, offering multi-Agent orchestration, human-in-the-loop escalation, audit trails, and anomaly detection.
TutorialsDeep dive into OpenClaw's industrial-grade Agent architecture with its three-layer design, pluggable Skills system, and memory management. Includes a step-by-step LangChain reproduction guide with an enterprise HR assistant example.

Numbat is an open-source AI Agent security detection and response tool supporting cross-framework deployment with Agent behavior visibility and pre-execution interception capabilities.

Exploring whether AI can proactively file tickets for programmers. From architectural constraints and security risks to AI Agent solutions, analyzing the current state and future of AI feedback loops.

From Iraqi stew to Singaporean cuisine across centuries—using software refactoring concepts to decode cultural evolution, code reuse, and incremental change.

Explore AI agent delegation boundaries: from code completion to autonomous agents across three levels, analyzing verifiability, error costs, and context to build pragmatic trust strategies.

Exploring how AI drives large-scale MMO development, from scalable content generation to dynamic NPC interaction, analyzing technical pathways, challenges, and industry implications.

Analysis of whether spending 20% more on hardware for self-hosting Kimi K3 to gain 20% task performance improvement is worthwhile, covering inference precision, VRAM optimization, and tiered deployment.