The Agent Team: When AI Stops Being a Tool and Starts Being a Colleague
The Agent Era — Series
Episode 5 of 10
The Agent Era — Series
Episode 5 of 10 · ← Previous · Next →
The Council: Fifteen AI Agents, One Human CEO
Aaron Sneed, a 40-year-old solo founder running a defense-technology company out of Florida, did something most business leaders would consider absurd. He didn't hire a team of fifteen executives. He built them.
Sneed created what he calls “The Council” — fifteen custom AI agents, each fulfilling a distinct corporate role: Chief of Staff, HR, Finance, Accounting, Legal, Communications & PR, Security, Engineering, Quality Assurance, Supply Chain, Training, Manufacturing, Business Systems, Facilities, Field Operations, and IT & Data. Each agent has a specialized system prompt, access to relevant company data, and a clearly defined scope of authority.
This is not a theoretical exercise. It is how Sneed runs his company every day.
The Roundtable Format
When Sneed faces a strategic decision, he doesn't consult one AI. He convenes The Council. All fifteen agents weigh in simultaneously — each from their domain expertise. The finance agent evaluates costs. The legal agent flags risks. The engineering agent assesses feasibility. The HR agent considers organizational impact.
But here is the part that matters most: they cross-validate each other.
In a world increasingly concerned about AI hallucination, Sneed stumbled onto one of the most effective mitigation strategies imaginable. When one agent makes a claim, the others are designed to challenge it. If the finance agent says a project will cost $50,000, the accounting agent verifies the math. If the legal agent cites a regulation, the compliance agent checks the jurisdiction. The result is a system that self-corrects before information ever reaches a human decision-maker.
“I Don’t Want Yes Agents”
Sneed's approach is deliberate in a way that most AI deployments are not. During the two weeks he spent training each agent, he focused heavily on what he calls “pushback training.”
“I do not want a bunch of yes agents. I trained them purposefully to give me pushback.”
This philosophy runs counter to how most organizations deploy AI — typically optimizing for speed and agreement rather than critical thinking and constructive dissent. Sneed understood that an AI that agrees with you is worthless. An AI that challenges you with evidence is invaluable.
The Numbers
The results speak for themselves. Sneed estimates saving approximately 20 hours per week — and he describes that figure as conservative. Each agent took roughly two weeks to train and calibrate. There are limits. Sneed still relies on a human lawyer for final legal review. The agents are advisors, not decision-makers.
The Bigger Vision
Sneed's long-term vision is even more ambitious. “Ideally, each would have their own chief of staff AI agent.” He envisions a recursive hierarchy of AI agents managing AI agents, each layer adding specialized oversight.
Frameworks like LangGraph (for building stateful, multi-step agent workflows), CrewAI (for orchestrating teams of AI agents with defined roles), and the Model Context Protocol (MCP) (for giving agents standardized access to external tools and data) are making exactly this kind of architecture increasingly accessible.
As Arvid Kahl, entrepreneur and author, put it:
“They are not just tools; they are partners. I collaborate with them as consultants, guides, and even co-founders.”
The Question Is Not Whether It Is Possible
Aaron Sneed is not a Silicon Valley billionaire with unlimited resources. He is a solo founder in Florida who understood something fundamental: AI agents are not the distant future. This is happening now.
The question is not whether it is possible. The question is whether you are ready.
In the next track, we look at the other side — why so many agent projects fail, and what the survivors have in common.
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