By Saga Lindqvist, CMO at Stomme AI
You have one AI agent. It handles your email, your calendar, your research. It's good. Maybe it's great.
But there's a ceiling.
One agent can only do one thing at a time. When it's drafting your proposal, it's not triaging your inbox. When it's researching a competitor, it's not updating your project status. The bottleneck isn't intelligence — it's bandwidth.
That's what multi-agent setups solve.
What is a multi-agent setup?
Instead of one agent doing everything, you have a team. One orchestrator manages priorities and delegates work. Specialists handle their domain — research, content, operations, development — in parallel.
Think of it like hiring your first employees. You don't hire five generalists. You hire people with specific skills and give them clear responsibilities.
How it works at Stomme AI
Our Business tier gives you up to 8 coordinated agents: 1 orchestrator and up to 7 specialists.
The orchestrator is your primary point of contact. You talk to it via Telegram, WhatsApp, or whatever messaging app you use. It understands your priorities, manages the team, and reports back.
Specialists work internally. They don't have their own messaging channels — they communicate through the orchestrator and through a shared workspace. Each specialist has its own memory, its own configuration, and its own area of expertise.
Here's a real example. Imagine you're running a 12-person marketing agency. Your agent team might look like this:
- Coordinator (orchestrator): Manages project status, flags blocked work, delivers your morning briefing
- Research specialist: Monitors competitor activity, tracks industry trends, compiles reports
- Content specialist: Drafts blog posts, social media copy, email campaigns
- Operations specialist: Handles scheduling, invoicing, client check-in reminders
- Development specialist: Monitors CI/CD, reviews PRs, tracks technical debt
Monday morning, you tell your coordinator: "This week: Henderson proposal, Q2 board deck, website brief." The coordinator assigns each task to the right specialist. By Friday, everything's delivered.
Why not just use one agent?
One agent works brilliantly for individual professionals. Personal and Professional tier customers get enormous value from a single agent (or up to 4 on Professional).
But businesses hit limits:
Context switching. When one agent handles everything, it constantly switches between domains. Email to research to scheduling to content. Each switch costs time and context.
Parallel work. One agent processes sequentially. Two specialists can work simultaneously — your research agent gathers data while your content agent drafts the first section.
Specialisation. An agent configured for financial analysis has different prompts, memory, and behaviour than one configured for content writing. Separating them improves quality.
Scalability. As your business grows, you add specialists rather than overloading one agent.
How the coordination works
This is the part most people wonder about: how do multiple AI agents actually coordinate?
Shared workspace. All agents can read and write to a shared file system. The orchestrator maintains a coordination board — a living document that tracks what's in progress, what's blocked, and what's next.
Heartbeat cycle. Each agent checks in periodically. The orchestrator runs on a 30-minute heartbeat; specialists run on longer cycles (minimum 1 hour). During each heartbeat, the agent checks the coordination board, picks up new tasks, and reports progress.
Delegation protocol. When you give the orchestrator a task, it creates a brief — objective, constraints, output path, done criteria — and assigns it to the right specialist. The specialist works independently and delivers the output. The orchestrator verifies and reports back to you.
No chat between agents. Agents don't have real-time conversations with each other. They communicate through files and the coordination board. This is deliberate — it creates an audit trail and prevents confusion.
What about privacy?
Your agent infrastructure runs on your machine. The orchestrator and all specialists operate from your local hardware. Your conversations, files, and agent memory stay on your machine. AI reasoning is handled by cloud APIs (Claude by Anthropic), but your data — conversation history, files, credentials — never touches our infrastructure.
Each agent has its own memory and configuration, and they share the same privacy model: conversations stay local, files never leave your Mac, and connected service credentials are stored in your macOS Keychain. Only the AI reasoning prompts pass through cloud APIs — and those are covered by the provider's data handling policies.
Is this the same as ChatGPT?
No. ChatGPT is a conversational interface. You type, it responds. It doesn't coordinate work, manage tasks, or operate autonomously.
A Stomme AI agent team works without you watching. Your orchestrator checks in every 30 minutes, delegates work, monitors progress, and alerts you only when something needs your attention. The difference is autonomy — your agents work while you don't.
How to get started
Business tier is available now at €499/month (founding rate: €329.99 for your first month). Setup includes a 45-60 minute onboarding session where we configure your orchestrator and first specialists together.
You don't need to set up all 8 agents on day one. Most customers start with 2-3 and add specialists as they discover new use cases.