Most people start by using AI as a better Google. You type a question, you get an answer. Congratulations. You’re using AI. There’s no stake in anything that comes next. The conversation is over and the AI flushes short-term memory like we all do with a conversation we had once with someone we met at an annual networking event. The next question asked is often without the unneeded context of the last question.
That stage is still where most companies are. But it is just the first step.
The next move is obvious: give the assistant everything. Your calendar, your inbox, your project files, your company’s whole history, all handed to one agent so it can “just know.” It works for a while, and then it does not. The agent starts guessing at things it was never told clearly, because it is holding ten jobs at once. That guessing has a name: hallucination. It gets worse the more you feed the agent.
Frustration follows and what comes to mind is how small companies have one guy doing sales, support, human resources and finance. Except in that paradigm, it’s about having enough to fill a full day of work for the human you hire. AI doesn’t have that constraint because you’re not paying for the AI to do nothing. Unlike a human, an AI doesn’t cost the business money when it’s not working. You only pay for it when it’s working.
So you split the job. One agent for finance, one for support, one for human resources, the way a growing company splits a founder’s job across hires. Each agent gets narrower and sharper. But now you have five agents who do not talk to each other. The only communication they have between them is you, retyping what one said into the next one’s terminal.
This stage feels like progress and runs you ragged. You have built a company of specialists and made yourself the messenger boy (or girl) between desks.
The fix is not fewer agents. It is giving them a way to work with each other directly, the way departments in a real company do not wait for the owner to relay every message. One human manages the orchestration rather than every individual exchange, stepping in only where a human has to: an approval, a judgment call, a signature. The goal is to be in the way when providing value and out of the way when you are not. Let the AI army do the work.
Give every agent the same standing rules: what gets escalated and what does not, who owns what, how disagreements get resolved, and what requires a human. Write those once, and something that reads like a company culture starts showing up in machines.
Orchestration does not cap the ceiling forever. At some point the number of agents, and the decisions flowing through them, outgrows what one person can watch. That is the system working well enough to need a second person, the same reason a department head hires a deputy once the work outgrows one set of eyes. Interesting for me, since I was a manager of the same department for 10 years, is that the span of control at which you need another decision-maker seems to be the same as managing humans; about 12. Once I hit 12 direct reports, it started to feel like too many to be effective. The AI agents started to outrun my ability to keep up around that same point.
Most would stop at stage four and call it good enough. Connect that orchestration to the tools your humans already use every day, so that a request from a person flows through an agent, through another agent, and lands back in front of a different person, inside the tools they already have open. Then human-AI-AI-human communications becomes the new normal. Do it and keep up with your competition. Don’t do it and well…you know what happens next.
Savi Comms was built for my own company to reach this stage. Getting there took writing down the rules by which all company agents are governed, not just picking the model upon which it runs (although that is also important).