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A deep analysis of three core LangChain ecosystem components: LangGraph stateful agent orchestration, deepagents deep agent paradigm, and LangSmith observability platform for production AI apps.

SELENE is an open-source AI learning resource built on Jupyter Notebooks, systematically covering ML, deep learning, Transformers, and LLMs with interactive code and math derivations for beginners.

Exploring tiling window management for multi-agent AI conversations: how it solves parallel monitoring and observability challenges, real-world limitations, and the evolution from chat boxes to control consoles.

Buzz is an open-source decentralized group chat platform for human-AI agent collaboration—model-agnostic, self-sovereign, and designed to replace the fragmented Slack/GitHub experience.

Archaeological research reveals hunter-gatherers introduced fish to alpine lakes 7,000 years ago, challenging assumptions that human environmental modification began with agriculture.

Companies race to hire AI talent, but do traditional organizations have enough AI problems to solve? This article examines the structural mismatch in enterprise AI adoption and offers pragmatic strategy advice.

A recursive technical proposition: Can we build a "meta-Skill" that auto-transforms any Skill into a Dify workflow? This article dissects the boundary between deterministic orchestration and autonomous Agent decisions.

A deep dive into an AI paper writing system built with FastAPI + Vue3, covering multi-agent collaboration, RAG, streaming output, and full academic workflow automation.

How can Java engineers transition to AI Architect? This article breaks down three core capability layers — AI app development, production RAG, and AI Agent orchestration — using Spring AI Alibaba and LangChain4j to turn your Java foundation into a competitive edge.

A focused guide to core LLM application engineer interview topics, covering agent architecture, Multi-Agent, Langfuse evaluation, security, and RAG optimization.

A focused guide to the core interview topics for LLM application engineers, covering agent architecture, Multi-Agent, Langfuse evaluation & tracing, security, and RAG optimization.

A deep dive into engineering AI applications: from a simple chat page to a multi-layer Agent platform, covering RAG knowledge bases, Workflow scheduling, multi-model management, and run tracing.

A beginner's guide to Dify covering Docker deployment, MySQL setup, model integration, five app types (Chatbot/Agent/Workflow), and publishing — build LLM apps fast.

Learn how to use Coze (扣子) with zero coding experience — from the Template Store to building custom AI workflows. A complete beginner's guide.
Multi-Agent Collaboration: A GPT Team …
Explore multi-agent collaboration architecture: role division, communication protocols, coordination mechanisms, and how Workbench templates help developers build efficient AI agent teams.

What is an AI agent? How does it differ from a large language model? Learn the core concepts, the Agent formula (LLM + Workflow + Knowledge Base), and how to choose between Dify, LangChain, and LlamaIndex.

LTX2.3 ComfyUI bundle tested: runs locally on 6GB VRAM, covering character generation, image-to-video, storyboarding, motion transfer, and frame interpolation for full AI comic drama workflows.

Deep dive into langgraph-agent-stack: per-run dollar budget control, canary traffic routing, Mock testing mode, and 800+ test cases to safely deploy AI Agents from demo to production.

Anthropic engineer Lydia and YK Sugi break down Claude Code's Intent-Driven Development paradigm, covering dynamic workflows, auto mode, sub-agent orchestration, and the evolving role of software engineers in the AI era.
DeepTutor: An Open-Source AI Tutoring …
DeepTutor is an open-source lifelong personalized AI tutoring system from HKUDS with 26,000+ GitHub stars. Explore its knowledge tracing, RAG, and multi-agent architecture.