Nine months ago, Sam Brown was out of a job. The reason, he’ll tell you without a sense of bitterness, was artificial intelligence. The company he’d spent years building a career inside decided it needed fewer people, and he was one of them.
The company has taken no outside funding. When venture capitalists came calling, Fathom got all the way to the finish line on a term sheet and walked away—not because the deal was bad, but because they genuinely couldn’t figure out what they’d spend the money on.
Brown explained to Fortune that the partnership is essentially like collecting a paycheck. “We’d rather take the money now and then, there’s not a lot to reinvest in, because we don’t have huge costs.”
The results bore him out. In all of 2024, one of Gunhus’ consulting clients, Tiger Aesthetics, did not open a single net new account. Within one quarter of deploying Fathom, he said they had opened 225. “The bosses over at Tiger are like, ‘[Give them] whatever they want.’ They just saved a ton of money.”
Hooten, the CEO and the junior member of the group at 39, explained to Fortune that his 12 agent co-workers hold real operational roles—one runs customer success for a national sales force; another wakes up every two hours to scan the competitive landscape and file a briefing.
His background was in sales, not software, Hooten explained, and so he looks at the AI agent era as a chance to build things that he never had the skills to, before. When a colleague told him that he couldn’t build an automated sales tool that actually worked, he built it anyway, and on his first day using it in the field, he closed $440,000 in a single day.
Gunhus said he had firsthand experience with the customer service bot: a Tiger Aesthetics rep called with a support issue, was walked through the solution by what they believed was Hooten on the line, and had no idea they’d been talking to an AI. “The rep has no idea what’s going on, literally.”
Like Fathom, KNOWIDEA is a three-person operation. And like Fathom, Sejpal passed on early VC money. “If I wanted to exit, I would have taken VC money really quickly,” he said. He turned down a spot in Antler, one of the world’s largest startup accelerators, because he didn’t want to dilute equity before proving his model. Instead, he took a strategic investment check, from a consulting firm, not a venture fund, at a $15 million valuation.
His pitch to enterprise clients is almost a philosophy as much as a product. “Leaders need clarity,” Sejpal told Fortune from a hotel room (he said he spends nearly all his time traveling). “That’s it. There is no other reason, a dashboard, a report, all of it is just to bloody get clarity.” His platform ingests decentralized data and produces ranked, risk-weighted insights for C-suite decision-makers.
Crucially, Sejpal is careful about what his platform won’t do. On the question of AI hallucinations, a persistent concern among executives considering high-stakes AI tools, he draws a clear line. “At the core of decision-making is clarity plus judgment,” he said. “Our job is to give clarity. Your job is to make the judgment.” His system flags predictions that deviate dramatically from market norms and filters them out before they reach a client.
Sejpal, who grew up in India and moved to Canada to attend the University of Waterloo, spent years inside some of the largest people consulting firms in the world before deciding the industry was ripe to be disrupted. His vision of where the three-person company model leads is more radical than his current headcount suggests. He doesn’t think three-person teams are the endgame: he thinks they represent the beginning of a total restructuring of how work gets organized.
“I don’t want to ever hire an account executive or a customer success manager,” he said. “The only two roles that we want to hire are FDEs and FDCs, forward deployed engineers and forward deployed consultants.” One person who understands what data to select, and one who understands what context to apply. “Everything else,” he said, “can be automated using artificial intelligence.”
That logic extends to his larger argument about the enterprise. Take 20-person project teams, for example: “I think that is going to slim down to a two-person team. FDC plus FDE can do all of the work, and then one supervisor who can overlook. That’s it. It’s as non-complicated as that.”
It hasn’t been as lucrative for Sejpal as it has for the Fathom co-founders, but he’s not concerned about that yet. His savings dwindled for months until the spring of 2026, when he finally started drawing a salary, but he cheerfully said that his excitement about what he’s doing is more than enough for him. “If I if I wanted to make money, there are much simpler, less strenuous, mentally and body-exhausting tasks that I can do. I’m worried every single night, I have night sweats thinking how I’ll make salary for my employees, how I’ll grow my team and 20 other headaches. I could have made much more money without having a single of those stress.”
The VC model was built around the assumption that you needed massive capital to build technology: engineering teams, customer success departments, sales headcount. That assumption is now structurally broken. A platform that once required $10 million in seed funding to staff can be assembled by three experienced operators and a suite of AI agents for the cost of a dinner out.
That’s more or less the same conclusion Sam reached nine months ago, sitting with a pink slip and a decision to make about what came next. He doesn’t sound like a man who was laid off. He sounds like a man who got lucky.
