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Graph Workflow

7 articles · Page 1 of 1
AI Architecture Hub
AI Architecture Hub
Jul 29, 2026 · Artificial Intelligence

Breaking Down Agent Engineering: Graph, Loop, and Harness – A Full Implementation Guide

The article analyzes the hidden challenges of large‑scale repository security audits, explains the three‑layer architecture of Graph, Loop, and Harness, compares legacy single‑Loop agents with modern graph‑based workflows, and provides concrete standards, pitfalls, and step‑by‑step deployment practices for production‑grade AI agents.

AI automationAgent EngineeringGraph Workflow
0 likes · 16 min read
Breaking Down Agent Engineering: Graph, Loop, and Harness – A Full Implementation Guide
Su San Talks Tech
Su San Talks Tech
Jul 9, 2026 · Artificial Intelligence

Spring AI 2.0 vs Spring AI Alibaba: Which Framework Fits Your Needs?

This article compares Spring AI 2.0 and Spring AI Alibaba, detailing their architectures, core capabilities, pros and cons, and ideal scenarios, and explains how the two can be combined to leverage both atomic AI integration and enterprise‑grade multi‑agent orchestration.

Enterprise AIGraph WorkflowJava AI frameworks
0 likes · 19 min read
Spring AI 2.0 vs Spring AI Alibaba: Which Framework Fits Your Needs?
Architect's Ambition
Architect's Ambition
May 13, 2026 · Artificial Intelligence

Deep Dive into Spring AI Alibaba: Architecture, Core Features, and Practical Implementation Guide

This article provides a comprehensive analysis of Spring AI Alibaba, detailing its five‑layer architecture, core capabilities such as unified model access, cloud‑native integration, and Agentic AI features, and offers concrete code examples and production recommendations to help Java developers quickly build and deploy AI agents.

AI agentsAgent FrameworkCloud Native
0 likes · 12 min read
Deep Dive into Spring AI Alibaba: Architecture, Core Features, and Practical Implementation Guide
Fun with Large Models
Fun with Large Models
Dec 17, 2025 · Artificial Intelligence

Quick Guide to LangGraph 1.0: Core Concepts, Nodes, and Edges

This article introduces LangGraph 1.0 as a programming‑language‑style framework for AI agents, explains its core abstractions—State, Node, Edge, Reducer, and Human‑in‑the‑Loop—shows how to define state and node functions, builds simple and parallel graphs with static, conditional, and MapReduce edges, and demonstrates conflict‑resolution using built‑in and custom reducers.

AI agentsGraph WorkflowLangChain
0 likes · 17 min read
Quick Guide to LangGraph 1.0: Core Concepts, Nodes, and Edges
Fun with Large Models
Fun with Large Models
Aug 28, 2025 · Artificial Intelligence

A Deep Dive into LangGraph: Understanding the New Graph‑Based AI Agent Framework

The article compares LangGraph with LangChain, explains why a graph‑based architecture offers greater flexibility than linear chains, outlines LangGraph’s three‑layer core architecture and its ecosystem tools—including LangSmith, LangGraph Studio, CLI, and Agent Chat UI—while noting its reliance on LangChain and the need for VPN for CLI usage.

AI agentsGraph WorkflowLLM
0 likes · 11 min read
A Deep Dive into LangGraph: Understanding the New Graph‑Based AI Agent Framework