Multi-Agent Setup: Running a Team of AI Assistants
One AI assistant is useful. Five working in parallel, each with a different specialty, reporting to a shared dashboard — that's a different level entirely.
The problem with a single assistant
A single AI assistant handles things sequentially: you ask, it responds, you move on. It's like having one very capable employee who can only do one thing at a time. They switch between scanning your inbox, researching a market, writing a proposal, and monitoring your competitors — but never simultaneously.
What a multi-agent setup looks like
In a multi-agent setup, you have several AI instances running independently — each with its own role, its own memory, and its own schedule. They wake up on their own, check what needs doing, do it, and report back. You stay in the loop without being the bottleneck.
The Scout
Monitors Reddit, LinkedIn, news feeds for leads or opportunities relevant to your business.
The Researcher
Builds prospect lists, enriches contact data, prepares call briefs before your meetings.
The Monitor
Tracks competitors, pricing changes, new features, and industry news. Summarises weekly.
The Analyst
Scans for job posts, freelance gigs, and partnership opportunities that match your profile.
The shared dashboard
All agents report to a central dashboard — a live kanban board where you can see what each agent is working on, what's been completed, and what needs your review. You drag tasks from "inbox" to "active" when you're ready for them. Results land in "review" for your approval.
Think of it like a project management tool, except the team members are AI agents running on a schedule — not people waiting for instructions.
How agents communicate
Agents can hand tasks to each other. The Scout finds an interesting lead → it creates a task for the Researcher to build a full brief → the brief lands in your review queue. You only see the finished output, not the intermediate steps.
💡 Start simple: A multi-agent setup sounds complex but we build it incrementally. Start with one or two agents, see the value, then add more. Most people are running three agents productively within the first month.
Is this for everyone?
Not immediately. If you're just starting with AI, a single capable assistant is the right first step. Multi-agent setups make sense when you have recurring, parallel workflows — lead generation, competitive monitoring, content creation — that you want running in the background without your constant involvement.
Want to see what this looks like for your business?
We'll map out which agents would create the most value for you specifically.
Book a free call →