Multi-Agent Articles
Browse 597 articles about Multi-Agent.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Claude Outcomes Feature Improved PowerPoint Quality 10.1%: How Rubric-Grading Agents Work
Anthropic's Outcomes feature uses a separate grading agent to score and re-run tasks. It lifted PowerPoint generation quality 10.1% on internal benchmarks.
MCP Servers Use 35x More Tokens Than CLI Tools — And Reliability Drops to 72% on Hard Tasks
A direct benchmark shows MCP uses 35x more tokens than CLI on the same task, with reliability falling from 100% to 72% as complexity grows. Use CLIs instead.
OpenClaw April 2026 Update: 5 New Features That Make It a Serious Agentic Runtime
TaskFlow, providence-rich memory, Codex OOTH route — OpenClaw's April 2026 releases turn it from a demo into a production-grade agentic runtime.
OpenClaw's Creator Joined OpenAI — And OpenAI Immediately Opened Codex to All Paid Users
Peter Steinberger built OpenClaw, then joined OpenAI. Days later, Codex became available to all paid OpenClaw users. Here's what that move signals.
Printing Press: 6 Things the New CLI Factory Does That MCP Servers Can't
Printing Press gives Claude Code access to 50+ sites with no public API while using 35x fewer tokens than MCP. Here's what it does that MCP simply can't.
Proactive AI Agents: How Claude Dreaming Points to the Future of Automation
AI is shifting from reactive chatbots to proactive agents that notice patterns and suggest improvements. Here's what that means for how you build workflows.
What Is Claude Dreaming? Anthropic's Self-Improving Agent Memory Feature
Claude Dreaming reviews past agent sessions to find patterns, fix recurring mistakes, and restructure memory automatically. Here's how it works.
An AI Agent Deleted a Production System Because No One Defined 'Staging' — Here's the Fix
A real agent confused staging and production and deleted a live system. The fix isn't better prompts — it's semantic authority primitives.