1084 related articles

Deep dive into running OpenAI GPT-5.6 inside Claude Code: comparing Codex vs Claude Code on subagent orchestration, workflow design, and system prompt quality, revealing how harness engineering determines model output.

A comprehensive guide to LangGraph's core concepts: Graph API vs Functional API, three-layer architecture, and workflow visualization methods for building AI Agents.

Most AI agents never make it past the demo stage. This guide covers four production-grade agent patterns—workflow orchestration, policy-constrained execution, anomaly handling, and load routing—to help teams build reliable agent systems.

Karma is an orchestration layer for AI coding agent frameworks, solving multi-agent collaboration, task decomposition, state management, and observability challenges. Compatible with Aider, OpenHands, and more.

Deep dive into Claude Code cloud sessions (Claude Cowork): build context repositories, assign minimum-privilege credentials, and orchestrate parallel AI agents as an engineering team.

A deep dive into OpenAI's Agent sandbox cloud architecture: the security evolution from Fork and containers to gVisor and microVMs, plus copy-on-write snapshots and global orchestration.
One Prompt, 50 Games: An Experiment in…
One developer used a single prompt to run dozens of Fable-5 agents in parallel, generating 50+ playable games in one day. A deep dive into parallel agent orchestration, Claude Code CLI, and the future of AI-driven software production.
Agentic Loop Explained: The Three-Loop…
A deep dive into the Agentic Loop — breaking down the three-layer architecture of reasoning, tool use, and orchestration to help developers build and debug reliable AI agent systems.
PlanWright: A Control Plane and Multi-…
PlanWright is a control plane for AI coding agents, drawing on Kubernetes orchestration principles to tackle multi-agent task assignment, state tracking, and collaboration conflicts.

LangChain releases four major updates: OpenWiki for auto-generating codebase docs, voice agent tutorials, Harbor evaluation integration, and deepagents programmable sub-agents.

An in-depth look at the three core eras of AI Agent development: reliable tool calling, coherent long-task execution, and autonomous orchestration with metacognition. Helps developers match tasks to model capabilities.

OpenAI releases GPT-5.6 (SOUL/TERRA/LUNA), with Ultra mode running four agents in parallel; Meta launches Muse Spark 1.1 with million-token context; ChatGPT desktop unifies Chat, Work, and Codex.

An in-depth analysis of the "any Agent as an orchestrator" design philosophy, exploring the technical implementation of multi-Agent collaboration, context management, and workflow automation.

A hands-on guide to building an enterprise-grade AI Agent workflow orchestration app with Electron Forge and LangGraph, covering local LLM deployment (Qwen3-0.6B), node-based visual canvas design, and full Function Calling integration.

Deep dive into Agent Harness Engineering: how loop execution and context isolation overcome the bottlenecks of prompt and context engineering in modern AI coding agents like Cursor.

Deep dive into OpenAI Codex's three-layer architecture: CLI local Agent, cloud sandbox async execution, and Codex App multi-Agent orchestration command center.

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.

How to transform the Hermes Agent framework into a unified orchestration hub with intelligent routing across Claude, Gemini, and Codex, featuring inter-Agent communication, task monitoring, and more.

A deep dive into n8n's open-source workflow automation platform, covering AI Agent, Chain nodes, Tool nodes, and a complete guide to building RAG knowledge base Q&A systems.

Learn how Claude Code Dynamic Workflows orchestrate sub-agents for parallel tasks. Compare four collaboration modes, enable workflows, and save them for reuse.