Multi-Agent Articles
Browse 597 articles about Multi-Agent.
Agent Harness vs Framework: What's the Difference and Which Do You Need?
Frameworks like LangChain require human assembly. Harnesses ship as working agents. Here's how to choose between them for your AI workflow.
Agent Harnesses Beat Model Upgrades: 5 Benchmarks That Prove the Harness Is Now the Product
GPT-5.5 jumped from 61.5% to 87.2% functionality just by switching harnesses. Here's what the data says about harness vs model choice.
How to Use AI Agents to Run LLM Benchmarks: A Custom Evaluation Framework
Instead of relying on public benchmarks, you can build custom AI evaluation systems using agents. Here's how one developer built a gravity-well benchmark.
How to Use AI for Short-Form Video Creation: A 5-Skill Automation System
A skill system can take one long-form YouTube video and produce five captioned, reframed short-form clips automatically. Here's how the pipeline works.
How to Build a Minimal Agent Harness in Python: Step-by-Step with Session Persistence
Build a working agent harness in under an hour using append-only JSON session logs and dynamic system prompt assembly from agents.md files.
Cursor SDK vs Claude Code Harness: Which One Gets More Out of Your Model?
Opus 4.7 scores 91.1% in Cursor vs 87.2% in Claude Code's own harness. The harness gap is now bigger than the model gap.
Hermes Agent vs OpenClaw: Which Open-Source AI Agent Should You Use?
Hermes Agent and OpenClaw are both open-source AI agents with persistent memory and tool integrations. Here's how they compare for real automation work.
What Is the NVIDIA Neotron 3 Nano Omni? A Multimodal AI Model for Agents
NVIDIA's Neotron 3 Nano Omni combines text, image, video, and audio processing in one open model. Here's what it does and why it matters for AI agents.
Sam Altman Says the Harness Is Now Inseparable from the Model — Here's What That Means for Builders
Sam Altman told Ben Thompson he can't always tell if a great Codex result came from the model or the harness. What builders need to know.
What Is an Agent Harness? The Architecture Behind Claude Code, Codex, and Cursor
An agent harness turns a language model into an autonomous agent. Learn the 9 core components every modern harness needs and how they work together.
AI Agent Evaluation: How to Build Custom Benchmarks That Actually Test Intelligence
Public benchmarks are often contaminated by training data. Learn how to build custom AI agent benchmarks using simulation environments and iterative testing.
AI Agent Frameworks Compared: BMAD, GSD, Hermes, and Building Your Own
BMAD, GSD, and Hermes are popular AI coding frameworks—but most are overengineered. Here's how to evaluate them and when to build your own instead.
How to Build an Agentic Operating System with Claude Code
An agentic OS gives every Claude Code skill shared business context—brand voice, client data, and goals—so every output improves over time.
Salesforce Headless 360 and AI Agents: What It Means for RevOps Automation
Salesforce Headless 360 exposes CRM data via MCP, APIs, and CLI—letting AI agents like Claude act inside Salesforce without a human clicking through the UI.
How to Use Sub-Agents in Claude Code to Manage Context and Speed Up Research
Sub-agents let Claude Code run parallel research tasks without bloating the main context window. Learn how to use them for faster, cleaner AI workflows.
What Is Claude Managed Agents? Anthropic's Infrastructure Layer for AI Teams
Claude Managed Agents lets teams run long-running AI agents without building infrastructure. Here's what it is, how it works, and who should use it.
How to Use AI Agents for Data Migration: Lessons from Real-World Testing
AI agents can handle messy business data migrations—but they need the right guardrails. Learn what works, what fails, and how to validate outputs safely.
How to Build an AI Agent That Runs Overnight: A Practical Guide
Learn how to set up AI agents that work autonomously while you sleep—using parallel sessions, VPS hosting, scheduled tasks, and notification hooks.
How to Build a Multi-Agent AI Workflow Without Writing Code
Multi-agent workflows let AI handle complex, parallel tasks autonomously. Learn how to design and deploy them using no-code platforms like MindStudio.
GPT 5.5 vs Claude Opus 4.7: Which Model Should You Use for Agentic Work?
GPT 5.5 and Claude Opus 4.7 are the top frontier models right now. Here's how they compare on coding, writing, data work, and long-horizon agentic tasks.