What an AI agent swarm is, and how it runs a business.

It starts with a standing team.

Every company on Xaedros starts with five agents. The Director takes every request, yours or a customer's, and hands it to the agent that owns it. The Researcher investigates leads, competitors and markets. The Closer runs customer conversations toward a booked job. The Accountant keeps invoices, payments and margins straight. The Influencer writes social in your voice.

Each agent owns one kind of work, so each can be checked and improved on its own. Meet the standing team.

Agents create the agents they need.

When work comes up that nobody on the team owns, an agent creates a specialist for it on the spot. That specialist can create its own specialists, up to three levels deep, so a hard problem gets as many agents as it needs.

New agents do not start from zero. Each one inherits the team's approved patterns and every high-confidence learning in its domain, so it is useful from its first task. When its work is done, it is retired.

The limits that keep it under control.

A team that grows on its own needs limits that hold on their own. These are built into every agent.

Why a swarm does more than a single assistant.

A single assistant forgets the conversation when you close it and needs you in the middle of every task. A swarm shares one record of your customers, jobs, schedule and invoices, loads what actually happened before it starts again, and passes work between agents without you.

That is how the hours come back. Current AI could take on work that fills 60 to 70% of employee time, and the cost of hiring for that work is what a swarm replaces.

When a request is beyond what a company's Director can handle, it goes up to the head office Director, which decides whether it makes sense and builds the capability itself. See the full architecture.

Sources.

McKinsey Global Institute, The economic potential of generative AI

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