Multi-Agent Articles
Browse 597 articles about Multi-Agent.
7 Things You Must Do Before Deploying a Multi-User AI Agent
From model control to budget limits and eval frameworks, here are the seven production requirements every team needs before shipping an AI agent to real users.
How to Build an AI Dark Factory: Autonomous Code That Ships Itself
A dark factory hands your codebase entirely to AI agents. Learn the architecture, governance layers, and validation patterns needed to make it reliable.
How to Build a Hybrid AI Architecture: Local Models + Cloud Frontier Models
Use frontier models like Claude Opus for complex reasoning and local open-source models for classification, embeddings, and transcription to maximize ROI.
Claude Code Agent Teams: How to Run Multiple AI Agents in Parallel on the Same Project
Claude Code agent teams let frontend, backend, and testing agents collaborate in real time. Learn when to use teams vs sub-agents and how to configure them.
Progressive Disclosure in AI Agents: How to Load Context Without Killing Output Quality
Loading too much context at once causes context rot. Progressive disclosure loads reference files only when needed, keeping Claude focused and outputs sharp.
Claude Code Agent Teams vs Sub-Agents: Which Pattern Should You Use?
Claude Code agent teams let agents communicate directly via a shared task list. Learn when to use teams vs sub-agents and what the token cost difference is.
What Is the Anthropic Managed Agents Dashboard? How to Monitor Sessions, Vaults, and Costs
Anthropic Managed Agents includes a full dashboard for monitoring sessions, environments, credential vaults, and token costs. Here's what every tab does.
What Is Anthropic's Managed Agents? How to Deploy AI Agents Without Infrastructure
Anthropic Managed Agents handles sandboxing, auth, and tool execution so you can deploy production AI agents without managing your own infrastructure.
Claude Code Split-and-Merge Pattern: How Sub-Agents Run in Parallel Within One Session
The split-and-merge pattern lets Claude fan out work to up to 10 sub-agents simultaneously and merge results—all within a single terminal session.
What Is the Agent Discovery Problem? Why AI Agents Need an App Store to Find Each Other
As every business deploys AI agents, agent discovery becomes a massive unsolved problem. Learn what an agent-native app store would look like.
What Is the AI Trading Bot Challenge? How OpenClaw Performed With $10,000 Over 30 Days
Two creators gave OpenClaw $10,000 each to trade stocks for 30 days. Both bots outperformed the S&P 500 during a volatile market. Here's what happened.
What Is the Anthropic OpenClaw Ban? Why Third-Party Harnesses Were Blocked
Anthropic blocked Claude subscriptions from powering third-party tools like OpenClaw. Learn what changed, why it happened, and what to do instead.
How to Build an AI Stock Trading Bot With OpenClaw: Strategy, Setup, and Lessons Learned
Learn how to build an autonomous stock trading agent with OpenClaw, including strategy design, cron job scheduling, and what not to do with options.
Inside Claude Code's Shared Task List: How Agents Avoid Conflicts
Claude Code's shared task list uses git worktrees and status flags to prevent file conflicts when multiple agents edit a codebase. Here's the mechanic in detail.
What Is the Claude Code Builder-Validator Chain? How to Build Quality Checks Into AI Workflows
The builder-validator chain uses one sub-agent to build and another to review, giving you automated quality checks without manual code review.
Run Multiple Claude Code Sessions in Parallel With Git Worktrees
Use the Claude Code -w flag to spin up isolated git worktrees and run several AI coding sessions in parallel — one per branch, with zero context bleed.
What Is the Claude Code Operator Pattern? How to Run Multiple AI Agents in Parallel Terminals
The operator pattern lets you run multiple Claude Code sessions in isolated Git worktrees simultaneously, each with its own clean context window.
What Is the Claude Managed Agents Dashboard? How to Monitor Sessions, Environments, and Costs
Anthropic's Managed Agents dashboard gives you full visibility into agent sessions, token usage, environment permissions, and credential vaults.
Archon Explained: The Meta-Agent Framework for AI Coding Workflows
Archon is a meta-agent framework that orchestrates AI coding agents through YAML pipelines. Here's what a harness builder is and why teams are adopting one.
Harness Engineering: Orchestrating AI Coding Agents
Harness engineering is the discipline of orchestrating multi-agent AI coding sessions into reliable pipelines. Here's how the practice is taking shape.