#Multi-Agent system
1326 related articles
Industry Insights·1 min
Claude Code Architecture Deep Dive: Why a Single-Loop Design Beats Multi-Agent Systems
Deep dive into Claude Code's architecture: single-loop control, no RAG, 9,400-token tool prompts, and model tiering. The minimalist design behind a $1B AI coding tool.
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Tutorials·1 min
Multi-Agent Systems in Practice: Five Coordination Patterns That Cut Costs by 85%
Deep dive into five multi-agent coordination patterns: cost routing, context isolation, Agent Swarm, Generator-Verifier, and Smart Friend. Real cases show weekly costs dropping from $700 to $100 with 58% critical bug detection.
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Tutorials·1 min
Multi-Agent Collaborative Medical Consultation System: RAG + Local Deployment Practical Guide
A complete guide to building a multi-agent medical consultation system with RAG knowledge retrieval, local LLM deployment, and multi-agent architecture design.
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Deep Dives·2 min
How NVIDIA's Multi-Agent System Automates Financial Signal Discovery
Deep analysis of NVIDIA's multi-agent system for quantitative financial signal discovery, covering architecture design, LLM financial reasoning, and automated backtesting iteration.
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Deep Dives·1 min
Factory Missions Architecture Deep Dive: How a Multi-Agent System Runs Continuously for 16 Days
Deep dive into Factory Missions multi-agent architecture: how validation contracts, serial execution, and structured handoffs enable an AI coding system to run 16 days without losing context.
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Deep Dives·1 min
Ralph Loop: The New AI Programming Paradigm That Beats Multi-Agent Systems Through Iterative Trial and Error
Ralph Loop is a 2025 AI programming paradigm: a memoryless AI Agent repeatedly reads the same Prompt, accumulates experience via file systems, beating multi-agent architectures through iterative loops.
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Tutorials·1 min
LangGraph 1.0.5 Tutorial: Master AI Agent Orchestration & Multi-Agent Systems in Six Lessons
Complete guide to LangGraph 1.0.5 tutorial series covering durable execution, memory management, Human in the Loop, streaming, time travel, and multi-agent collaboration.
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Tutorials·3 min
LangGraph Multi-Agent in Practice: Building a Medical Agent System from Scratch
A deep dive into LangGraph multi-agent architecture for healthcare, covering LangChain, RAG, and MCP integration, from requirements analysis to Agent orchestration.
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·3 min
Getting Started with MARL (Multi-Agent Reinforcement Learning): A Complete Path from Theory to Code
A systematic guide to learning MARL from theory to code, covering CleanRL, PettingZoo, PyMARL tools, IQL/VDN/QMIX/MADDPG algorithm progression, and practical tips for bridging theory and implementation.
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·2 min
AI Agents Running a Real Company: Experiment Results and Capability Boundary Analysis
What happens when AI agents are tasked with running a real company? This analysis examines agent performance, critical shortcomings, and practical enterprise deployment advice.
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·3 min
Graph Engineering: The Core Paradigm and Design Patterns for AI Agent Orchestration
Deep dive into how graph engineering uses state machines and directed graphs to constrain AI agent behavior, covering reflection, routing, human-in-the-loop, and parallel execution patterns.
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·3 min
Graph Engineering: The Core Paradigm and Design Patterns for AI Agent Orchestration
Explore how graph engineering uses state machines and directed graph structures to constrain AI agent behavior, covering reflection, routing, human-in-the-loop, and parallel execution patterns.
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·4 min
Tiling Window Management: A New Interaction Paradigm for Multi-Agent Conversations
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.
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·3 min
What Kind of GUI Do AI Agents Need? The Evolution from Chat Boxes to Task Consoles
Exploring GUI design for AI Agents: why chat boxes fall short, and how ideal agent interfaces need task visualization, human-in-the-loop intervention, state presentation, and multi-agent orchestration.
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·3 min
Claude Opus 5 Plays Pokémon: A 12-Hour AI Experiment in Multi-Agent Loop Architecture
Deep analysis of Claude Opus 5 playing Pokémon for 12 hours via multi-agent loop architecture, exploring Agent design patterns, long-horizon planning, and AI Agent trends.
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·3 min
Claude Opus 5 Plays Pokémon: Analyzing a 12-Hour AI Experiment Under Multi-Agent Loop Architecture
In-depth analysis of Claude Opus 5's 12-hour Pokémon gameplay through multi-agent loop architecture, exploring multi-Agent design, long-horizon planning, and AI Agent trends.
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·2 min
Noisegate: Adding Differential Privacy Guardrails for Untrusted AI Agents
Noisegate is a differential privacy gateway for untrusted AI agents that injects calibrated noise into data flows, providing mathematically proven privacy guarantees when AI Agents process sensitive data.
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·3 min
AI Agent Authentication and Authorization: Core Analysis of the IETF Draft and Security Best Practices
Deep analysis of the IETF Internet-Draft on AI Agent authentication and authorization, covering identity attribution, delegation chains, least privilege, OAuth 2.0 extensions, and MCP integration.
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·2 min
Noisegate: Adding Differential Privacy Guardrails for Untrusted AI Agents
Noisegate is a differential-privacy gateway for untrusted AI agents, injecting calibrated noise into data flows to provide mathematically guaranteed privacy protection for sensitive data processed by AI Agents.
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·2 min
Moving State Out of Framework Memory: A Multi-Agent Architecture Refactoring Guide
Exploring how 70% of multi-agent memory is consumed by non-reasoning state, and a refactoring approach using email threads to replace framework memory for better token efficiency, auditability, and resilience.
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