#Orchestrator
301 related articles
·5 min
The Complete Claude Code Guide: Installation, Core Features, and Advanced Workflows
An in-depth guide to Anthropic's Claude Code agentic coding tool, covering installation, pricing plans, model selection, token management, CLAUDE.md global memory, MCP integration, Subagents, and more.
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·3 min
Knowledge Graph-Enhanced RAG: Building a More Powerful Q&A System
A deep dive into the DeepLearning.AI & Neo4j course 'Knowledge Graphs for RAG' — covering core concepts, vector retrieval synergy, and hands-on SEC filing demos.
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·4 min
UK Sovereign AI: How Cosine AI Is Punching Above Its Weight Against American Compute Dominance
Cosine AI founder reveals how the UK's first sovereign LLM is being built — from government compute grants and RL credit attribution to multi-agent orchestration and synthetic data pipelines.
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·4 min
Codex Major Upgrade: GPT-5.6 Powers Full-Stack Development from Idea to Deployment
OpenAI Codex gets a major upgrade with GPT-5.6: extended reasoning, multi-agent parallelism, browser control, one-click Sites deployment, task orchestration, and mobile dev support.
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·2 min
How to Choose Long-Horizon AI Workflow Tools? A Deep Comparison and Decision Framework for Leading Agent Solutions
Why do chatbots fail at long-horizon workflows? We compare Manus, Perplexity Comet, Claude, ChatGPT and more across task type, total cost, and automation level.
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·4 min
7 Core Components for Designing Long-Running AI Agents
A deep dive into the 7 core components for building long-running AI Agents: Goal, Evaluator, Verifier, Loop, Orchestration, Observability, and Memory.
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Multi-Agent Collaboration: A GPT Team …
·2 min
Multi-Agent Collaboration: A GPT Team Engineering Paradigm and Practical Guide
Explore multi-agent collaboration architecture: role division, communication protocols, coordination mechanisms, and how Workbench templates help developers build efficient AI agent teams.
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·2 min
The Complete Guide to AI Agents: Concepts, Principles, and Top Development Tools
A deep dive into AI agents: core concepts, how they differ from LLMs, the Agent = LLM + Workflow + Knowledge Base formula, and a comparison of Coze, Dify, LangChain, and LlamaIndex.
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·2 min
From Workflow Graphs to Distributed Protocols: Dissecting Multi-Agent System Architecture Paradigms
How does Cosmonapse replace LangGraph's graph structure with event-driven distributed protocols? A deep dive into two multi-agent architecture paradigms, their trade-offs, and when to use each.
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·3 min
Multica: An Open-Source Tool for Managing Multiple AI Coding Agents from a Single Dashboard
Multica is an open-source AI Agent management tool that unifies Claude Code, Codex, Cursor and more into one visual dashboard with kanban, task queues, and cloud deployment support.
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·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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·4 min
Pi Agent Deep Dive: Four Core Advantages of a Minimalist Open-Source Framework
Pi is a minimalist open-source Agent framework with just 4 default tools and under 1,000 tokens in its system prompt, with 70K GitHub stars. Deep dive into its 4 core advantages vs. Claude Code and Codex.
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·2 min
Loop Engineering Explained: The New Development Paradigm of Closed-Loop AI Agent Iteration
Loop Engineering is an emerging AI dev paradigm where Agents iterate in controlled loops instead of one-shot outputs. Learn the 4-year evolution and what it means for developers.
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·2 min
OpenAI GPT-Live: The Full-Duplex Voice AI Revolution
OpenAI's GPT-Live voice model family brings full-duplex interaction, task delegation, GPT-5-level intelligence, real-time translation, and image understanding to voice AI.
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Claude Is Mr. Meeseeks: The Disposable…
·2 min
Claude Is Mr. Meeseeks: The Disposable Nature of AI Agents and Its Engineering Implications
Using Rick and Morty's Mr. Meeseeks to explain Claude and AI agents: stateless execution, task atomicity, and multi-agent recursive failure risks. A deep dive for developers building better AI workflows.
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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
OpenClaw Multi-Agent AI Programming Workflow in Practice: From Coder to Manager
Deep dive into OpenClaw multi-agent AI programming workflows: context layering, CMUX parallel terminal management, work trees, and manager-perspective debiasing for scalable AI dev automation.
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·3 min
Cosmonapse: A Decentralized Multi-Agent Framework Built on an Event Bus
Cosmonapse is an open-source multi-agent framework that replaces central orchestrators with peer nodes, using typed signals and an event bus to fully decouple tool calls, memory, and HITL. Supports Python and TypeScript under Apache 2.0.
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·3 min
GPT-5.6 Practical Guide: 7 Tips to Save Tokens and Boost Efficiency
7 practical GPT-5.6 optimization tips for Codex: control context windows, choose thinking modes, limit sub-agents, and trim agents.md to save tokens and cut costs.
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·2 min
GPT-5.6 Deep Dive: A Qualitative Leap in Coding and Frontend Capabilities
A 1-billion-token deep dive into GPT-5.6 Solar Max reveals qualitative leaps in coding stability, Skills compliance, and frontend design. Includes version selection guide.
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