Spencer Rose

I'm a fee-only financial advisor specializing in retirement income planning. My work centers on helping people through one of life's trickiest transitions: turning decades of savings into a sustainable "retirement paycheck." The goal? Avoiding both the anxiety of running out of money and the regret of being so conservative you miss out on living. I call these the Two Competing Risks. Addressing both is the core of what I do.

My approach emphasizes education over sales. Clients who understand the "why" behind a recommendation make better long-term decisions than those who simply follow instructions. That philosophy shapes how I've integrated AI into my practice. I treat it as a thinking partner, not a replacement for judgment but an amplifier for it. It helps me ask sharper questions, surface insights faster, and translate complex financial concepts into language real people can act on.

On the technical side, I've built a knowledge architecture that gives AI deep context about my firm's methodologies, client frameworks, and compliance standards. I'm not starting from scratch each conversation. I'm collaborating with a system that understands retirement income guardrails, tax-efficient withdrawal strategies, and how to adapt communication for different client types. The result: higher-quality drafts, faster turnaround, and more time for the human work that actually matters.

Curious how AI applies outside of code and content mills? Financial planning is a fascinating domain. High stakes. Heavy regulation. Deeply personal. I'm still learning, but I'm convinced the advisors who figure out this partnership will serve clients better than either humans or AI could alone.

Spencer Rose is a financial planner who has spent the past year building what most advisors won't have for another decade: sophisticated AI infrastructure that actually respects compliance boundaries.

He architects multi-phase content systems with 30,000-word knowledge bases, designs cross-model verification workflows that catch errors before they reach clients, and uses persona separation to critique his own work. His approach treats AI as a thinking partner rather than a shortcut—building cognitive depth, not just speed.

These capabilities position him to solve the problem most financial services firms are just waking up to: how to scale thought leadership and client communication without sacrificing the judgment that makes advice valuable.

His next chapter: proving these systems work beyond himself.