Nuno M. Tavares — AI automation consultant in New Jersey, founder of Automated Marketer and Rapid Active Marketing — not the Portuguese footballer of the same name.
Here’s the direct answer: AI agents for business aren’t single tools you prompt one at a time anymore. They can organize themselves into teams. They assign each other tasks. They run whole departments — marketing, operations — with almost no manual routing from you. That changes what you hire for, not just what you automate.
What changed: AI agents for business moving from tool to organization
Quick answer: AI agents for business used to mean one chatbot answering one question at a time. That’s no longer the ceiling. On a new platform called Buzz, built by Twitter and Cash App co-founder Jack Dorsey, agents from Claude, ChatGPT, and local models talk to each other, pull contacts from a CRM, check revenue, and complete real work without a human routing each step.
I tested this myself on Buzz. On the surface it looks like Slack. Underneath, the channels aren’t full of people. They’re full of AI — Claude, ChatGPT, even local models — talking to each other, pulling contacts out of my GoHighLevel account, checking revenue numbers, and getting real work done without me routing every step.
That’s the part owners need to sit with. This isn’t one chatbot answering one question. It’s a structure. Agents with names, roles, and reporting lines, working inside channels the same way a team works inside a Slack workspace.
Why this is different from the automations you already have
Most business owners already run some kind of automation — a workflow that sends an email, a bot that answers a form fill. Buzz is a different layer. You create an agent, give it a job title and instructions, and then it recruits and manages other agents on its own. I built one called Bob and told it directly: “You control the marketing team… acting almost as a CMO.” Bob then pulled in the other agents already sitting in my workspace and assigned them individual tasks without me telling it who does what.
What a self-organizing marketing team actually looks like
Quick answer: a self-organizing marketing team is a lead agent plus several worker agents dropped into one channel with a single instruction — no manual task assignment from the owner. In testing, a lead agent named Bob split a marketing-plan request among three worker agents and each one started on its piece immediately, visible in the channel in real time.
In the demo, I created three agents that came pre-loaded with the platform — Fizz, Honey, and Bubble — then added Bob as the lead. I put all four into a “marketing team” and dropped that team into a marketing channel. Then I gave one instruction: get the team together and build a marketing plan.
Bob didn’t ask me who should do what. It delegated. Fizz, Honey, and Bubble each picked up a piece of the plan and started working, visible in the channel in real time, the same way you’d watch a Slack thread move. That’s the shift — the org chart got built by the agent, not by me.
The GoHighLevel example is the part owners should pay attention to
I asked Fizz — set up as the general operator — to build a GoHighLevel team: agents with access to the right skills and connectors, focused entirely on that account. It created an operations agent, a CRM agent, a comms agent, and ran what it called a smoke test to confirm everything worked. It came back having pulled real numbers: 14,120 contact records, the latest entries, and revenue earned the day before. No manual query. No dashboard click. It just reported back like a staff member would.
What this does to headcount and delegation decisions
Quick answer: self-organizing agents take over the coordination work — routing tasks, checking status, chasing updates — not the judgment calls. That shifts the real question for owners from “what can I automate” to “what am I still paying a person to coordinate,” without meaning you should cut staff immediately.
Here’s the thing nobody’s saying out loud yet: if an AI agent can recruit its own sub-agents, assign tasks, and check its own work with a second model acting as reviewer, the question isn’t “what can I automate” anymore. It’s “what am I still paying a person to coordinate.”
That’s not a call to fire your team tomorrow. It’s a call to look honestly at your roles. Some are pure coordination — routing tasks, checking status, chasing updates. Others need judgment you actually trust a human with. Coordination is exactly what a lead agent like Bob or Fizz does for free, all day, without getting tired.
The owners I talk to on strategy calls are already feeling this pressure. They don’t want another course explaining prompt engineering. They want to know which of their current delegation decisions are about to become unnecessary. That’s a strategy conversation, not a tooling one.
The one honest gotcha with self-organizing agents
Quick answer: this is still early technology, and it shows. Agents can lose track of channels, misfire, or need to be rebuilt mid-session, and running it without per-token billing means self-hosting on a VPS with real memory and processing power. It is not something you hand to an untrained employee and walk away from.
This is still early, and it shows. Getting agents to actually recognize each other and hold state took restarts and repeated commands in the demo — at one point the system insisted a channel didn’t exist when it clearly did, and I had to recreate agents before the team would function. Want to run this without touching APIs or paying per token? You’ll need to host it yourself on a VPS with real processing power — Buzz recommends at least 8GB of RAM and two cores. Want to use your existing Claude or OpenAI subscriptions instead of API billing? That install has to sit on your local machine, not a cloud server. It’s not a five-minute setup. And it’s not something you hand to an untrained employee and walk away from.
Not even close to production-stable for a business that can’t tolerate a bad day of agent confusion. That’s the trade you’re making for being early.
How owners should think about adopting this now
You don’t need to rebuild your whole company around self-organizing agents this quarter. You need to know where the technology is headed so your next hire, your next tool purchase, and your next org chart decision aren’t obsolete in six months. That’s the exact gap between “I read an AI newsletter” and having someone who’s actually built the thing sitting across from you.
If you want to walk through what this means specifically for your business — where agents replace coordination versus where you still need a human — that’s a conversation worth having directly. You can book a strategy session or look into working with me directly if you want this mapped against your actual operation instead of a demo.
Keep learning
- AI Agents for Business: GoHighLevel’s New Super Agents
- AI Automation Consultant: Fix Email Deliverability First
- AI Automation Consultant: Route App Payments via CRM
Frequently asked questions
Are AI agent teams the same thing as automation workflows?
No. A workflow follows a fixed path you built in advance. A self-organizing agent team decides its own path — a lead agent can recruit other agents, assign them tasks, and adjust based on what it finds, without you specifying every step.
Do I need to know how to code to set up something like this?
No, but you do need patience. Tools like Buzz are still in early development, which means installs can be finicky and agents sometimes need to be restarted or rebuilt. It’s approachable for a non-coder, but not yet plug-and-play.
Should a small business replace employees with AI agent teams right now?
Not wholesale, and not without a real strategy behind it. The honest use case today is coordination-heavy work — status checks, data pulls, first-draft content — not judgment calls that carry real risk if they go wrong.
What’s the real risk of adopting this too early?
Instability. Agents can lose track of channels, misfire commands, or need to be recreated, as shown in testing. If your business can’t tolerate that kind of hiccup in a client-facing process, you’re not ready to run it unsupervised yet.
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