#Subagent architecture
93 related articles
·2 min
The Complete Guide to Agent Skills: Andrew Ng × Anthropic Joint Course Breakdown
Andrew Ng's DeepLearning.ai teams up with Anthropic to teach Agent Skills: file structure, progressive disclosure, MCP integration, and the full path from Claude.ai to the Agent SDK.
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·2 min
Claude Code for QA Engineers: A Practical Handbook from Basics to Engineering-Level Implementation
A practical Claude Code handbook built for QA engineers — covering environment setup, spec-driven development, Skill encapsulation, MCP integration, and AI test sub-agents across 10 core modules.
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·3 min
OpenCode In-Depth Review: Can This Open-Source Coding Agent Replace Claude Code?
OpenCode is an open-source terminal coding agent with 180K+ GitHub stars, supporting hundreds of models and a dual-layer agent architecture — completely free. See how it compares to Claude Code.
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·3 min
Claude Code Enterprise Guide: Environment Setup, Git Workflows, and Switching to Chinese AI Models
Enterprise guide to Claude Code: CLI setup, switching to DeepSeek and other Chinese AI models, Git workflow automation, and bug fix loops to boost team productivity.
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·3 min
The Truth About Codex Ultra Mode: It's Not a Reasoning Level
Deep dive into OpenAI Codex's Ultra mode: it's not a reasoning level but a system prompt switcher. Learn why Ultra burns tokens, the V1/V2 agent system issues, and how Claude Code Workflows gets it right.
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·3 min
The Complete OpenAI Codex Practical Guide: From Installation to Enterprise Deployment
A complete guide to OpenAI Codex: CLI setup, slash commands, AGENTS.md, MCP integration, multi-agent collaboration, and a RAG customer service project walkthrough.
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·3 min
Codex Efficiency Guide: Practical Strategies to Avoid Burning Through GPT-5.6 Credits
GPT-5.6 (Sol) is powerful but burns credits fast. Learn reasoning tier selection, Fast Mode, and prompt stop-point strategies to get the most out of Codex.
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·3 min
Multi-Agent Collaboration with Claude Code and Codex: A Guide to Architecture Design and State Management
A deep dive into Claude Code and Codex multi-Agent collaboration: architecture design, state-driven coordination, private/public zone division, and building efficient AI programming teams.
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·6 min
A Deep Dive into AI Agent Harnesses: The Core Engineering Behind Agent Frameworks
What is an AI Agent's harness? This article systematically dissects the core components of agent frameworks: context management, tool use, control loops, and caching strategies—revealing why the same model performs so differently across harnesses.
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·5 min
GPT-5.6 Released: Hands-On Analysis of Programmatic Tool Calling and Autonomous Agents
GPT-5.6 is officially released with core upgrades including programmatic tool calling, autonomous subagent delegation, and higher token information density. A hands-on card game build reveals its Agentic power.
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·4 min
The Three Eras of AI Agents: The Capability Leap from Tool Calling to Autonomous Orchestration
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.
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·6 min
The Complete Beginner's Guide to Claude Code: From Installation to Advanced Usage
Claude Code is one of the most powerful AI coding agents, running in the terminal to write code, batch operations, build web projects, and more. This guide covers installation, connecting local models via CC Switch, permission modes, CLAUDE.md, Skills, MCP, Subagents, and more.
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·3 min
GPT-5.6 Three-Model Architecture Explained: Sol/Terra/Luna Pricing and Performance Overview
GPT-5.6 introduces a Sol/Terra/Luna three-model architecture. Terra delivers near-flagship performance at half the price, with new Max and Ultra reasoning tiers.
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·4 min
Harness Engineering: The Third Phase of AI Coding and a Practical Guide to agents.md
A deep dive into Harness Engineering — the third phase of AI coding. Based on research across 2,853 GitHub repos, explore agents.md, Skills, MCP, and eight configuration mechanisms to control your AI coding assistant.
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·7 min
LangSmith Engine: An Intelligent Operations Tool That Automatically Diagnoses and Fixes Agent Failures
LangChain's LangSmith Engine is an intelligent agent tool for tracking Agent failures, prioritizing issues, and auto-drafting fixes. Deep dive into its core capabilities, sandbox isolation, sub-Agent architecture, and continuous evaluation challenges.
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·7 min
The Birth of Claude Code: Design Philosophy from Internal Tool to AI Programming Assistant
An in-depth look at Claude Code's development and design philosophy: why the CLI form, how the "minimal scaffolding" architecture works, and how it balances safety with autonomy in AI programming.
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·3 min
Claude Code Agent Teams: A Practical Guide to AI Team Collaboration in Software Development
A deep dive into Claude Code Agent Teams: how they differ from Subagents, contract-first design, model allocation strategies, and a real case of 16 agents building a C compiler.
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·4 min
Hunyuan Hy3 Goes Open Source + GPT-5.6 Leaked + Japan's Robot Strategy: AI Breaks Through on Multiple Fronts
Tencent Hunyuan 3 open-sourced with 295B MoE; GPT-5.6 Sol Ultra may bring multi-subagent collaboration to Codex; Alibaba FunASR upgraded; Japan plans 10M AI robots by 2040.
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·6 min
Claude Code Chinese Guide: A Complete Path from Zero to an Efficient Workflow
A systematic Claude Code learning guide built for Chinese developers, covering ten core modules including Slash Commands, Memory, MCP, and Hooks, with a three-tier path to build an AI coding workflow in 11–13 hours.
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·6 min
Vibecoding in Practice: Architecture Trade-offs and Implementation of a Dual-Engine TTS Router
Alibaba Cloud vs Volcano Engine TTS: why "I want both" is the mature engineering decision. Dual-engine routing design, priority trap debugging, and vibecoding-powered implementation.
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