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Multi-Agent Articles

Browse 431 articles about Multi-Agent.

Claude Opus 4.6 Runs Autonomous Tasks for 14.5 Hours at 50% Completion — No Competitor Is Close

Claude Opus 4.6 achieves 50% task completion at a 14.5-hour autonomous horizon. No competing model has published a comparable benchmark.

Claude Multi-Agent LLMs & Models

Claude Standard Memory vs Dreaming: Why Passive Storage Isn't Enough for Long-Running Agents

Standard Claude memory passively stores facts. Dreaming actively reorganizes them on a schedule. Here's why the difference matters for long-running managed…

Claude Multi-Agent Comparisons

Codex /goal: OpenAI's 'Ralph Loop' Feature That Ran a Device Driver Project for 14 Hours Without Stopping

Codex's /goal feature keeps a task alive across turns until complete — one user ran it on a device driver project for 14 hours overnight. Here's how it works.

GPT & OpenAI Automation Multi-Agent

GPT Realtime 2 Can Stay Silent on Command and Keep Listening — Here's Why That Changes Voice Agents

GPT Realtime 2 can be told to go silent, listen to a side conversation, and re-engage on command — solving the biggest friction point in live voice agents.

GPT & OpenAI Multi-Agent LLMs & Models

Hermes Agent's 5-Pillar Architecture: How It Learns, Schedules, and Improves Itself Over Time

Hermes Agent is built on five pillars: memory, skills, soul, crons, and a self-improving loop. Here's how each one works and why the combination matters.

Multi-Agent Automation AI Concepts

Hermes Agent Cron Jobs in Plain English: Set Up Automated GitHub Backups with a Single Sentence

Hermes Agent lets you schedule cron jobs in plain English. Type 'every night at 12am, push changes to GitHub' and it creates the skill and cron automatically.

Automation Workflows Multi-Agent

Hermes Agent Five Pillars: Memory, Skills, Soul, Crons, and Self-Improvement

Hermes Agent is built on five core pillars that make it a self-improving personal AI. Learn how memory, skills, crons, and the soul file work together.

Multi-Agent Automation AI Concepts

How to Set Up Hermes Agent on a VPS with Telegram in Under 30 Minutes: Complete Setup Guide

Hermes Agent runs on your own VPS, connects via Telegram, and uses your ChatGPT subscription — no API key billing. Here's the complete setup walkthrough.

Workflows Automation Multi-Agent

Hermes Agent vs Claude Code: Which Should You Use and When?

Hermes Agent and Claude Code serve different workflows. Learn when to use each, how they compare on autonomy and scheduling, and how to combine them.

Claude Multi-Agent Comparisons

Hermes Agent vs OpenClaw: Which Self-Hosted AI Agent Is Right for On-the-Go Agentic Work?

Hermes Agent has 140K stars and runs on any VPS. OpenClaw has 350K stars and was built by a now-OpenAI engineer. Here's how to choose between them.

Comparisons Multi-Agent Automation

How to Set Up Hermes Agent on a VPS: Docker vs Root Install

Learn how to deploy Hermes Agent on a virtual private server using Docker or root install, connect Telegram, and set up GitHub backup with automated crons.

Multi-Agent Automation Workflows

How to Manage Multiple AI Agents Across VPS Servers: A Claude Code Organization System

Running multiple AI agents across different servers gets messy fast. Learn how to use a Claude Code project to track passwords, configs, and agent setups.

Multi-Agent Workflows Productivity

MCP vs CLI in Agentic Workflows: 35x Token Overhead and 72% vs 100% Reliability — The Data You Need

MCP servers use 35x more tokens than CLI tools on the same task, with reliability dropping from 100% to 72% as complexity grows. Here's when to use each.

Workflows Automation Multi-Agent

Prompts vs Skills vs Plugins vs MCPs: The 10-Minute Framework That Stops You Wasting 40% of Your AI Time

Most AI users conflate prompts, skills, plugins, and MCPs — and waste 40%+ of their time. This 10-minute framework clarifies exactly when to use each.

Workflows Automation Prompt Engineering

ReAct Loop vs Linear AI Workflow: Why n8n and Zapier Can't Do What Claude Code Does

A ReAct loop reasons, acts, observes, and iterates until done. A linear workflow just executes steps. Here's why the difference matters for real agentic work.

Comparisons Workflows Automation

What Is Proactive AI? How Agents Are Shifting from Reactive to Anticipatory

AI agents are evolving from chatbots that wait for prompts to proactive systems that find patterns and suggest automations. Here's what that shift looks like.

Multi-Agent AI Concepts Automation

What Is the ReAct Loop? How AI Agents Reason, Act, and Iterate

The ReAct loop is the core reasoning pattern behind agentic AI systems. Learn how agents reason, act, observe results, and iterate to complete complex tasks.

Workflows AI Concepts Multi-Agent

Anthropic Dev Day: 6 New Managed Agent Features That Change How Claude Handles Long-Running Work

Dreaming, Outcomes, multi-agent orchestration, Claude Finance — Anthropic's dev day introduced the most complete managed-agent stack yet.

Claude Multi-Agent Automation

Anthropic Managed Agents vs Open-Source Agent Frameworks: Which Should You Build On?

Anthropic now has native Dreaming, Outcomes, and orchestration. But open source shipped these primitives first. Here's how to choose your stack.

Claude Multi-Agent Comparisons

Anthropic Restricts Third-Party Agents, OpenAI Opens Up: Which Provider Should You Build On?

Anthropic locked down always-on agent subscriptions. OpenAI opened Codex to everyone. Here's how to pick the right provider for your agentic workflow.

Multi-Agent Claude GPT & OpenAI