Heading North

Prior to May 23, 2024, I would have described myself as a career life insurance professional with both breadth and technical depth built over three decades traversing the supply chain. I began as a pricing actuary and went on to serve in senior roles spanning product development, pricing and product management, and business leadership—including chief financial officer, head of Risk Selection, and ultimately CEO of AIG's global life business.

During those thirty years, any success I had came from what I consider fundamentals: striving to make every team better, whatever my role; and viewing underwriting, distribution, and operations (as just examples) not as silos but as interconnected risk–return trade-offs that define the decision framework itself. That, combined with a logic-driven mindset and a lifelong focus on structure, continuous improvement, and process optimization, has shaped how I approach everything.

But if there is one thing I have long recognized as an innate capacity, it's that I'm an insatiable learner. I was fortunate: my parents instilled not only the importance of learning but the curiosity to understand how things work. They also taught me to learn well—with absolute fearlessness. I love to learn, and now, with LLMs, that capacity is in hyperdrive.

May 23, 2024 — Down the Machine Learning Rabbit Hole

By May 23, I had already come to a simple realization: rapid advances in machine learning—and the overwhelming proof-of-concept demonstrated by tools like ChatGPT—meant we no longer live in an "if/then" world.

That a decade of accelerating technological progress—

• greater volume, structure, and accessibility of data;
• exponential gains in compute power;
• global collaboration through the open-source community; and
• the modular connectivity of microservice-based APIs

had resulted in machine cognition deployable at scale, placing us at the beginning of a transformation on par with the shift from the agricultural to the industrial and information ages—or The Dawn, as I have come to think about it.

But on May 23, 2024, with a brief respite before finishing a nearly completed article—the central marketing piece for the risk advisory services business I had spent months preparing to launch—I sat down to finally learn Python and build a neural network. Within weeks, I knew the article—and the risk advisory services business behind it—were lost, and I was going to build something. I needed a company name, and I registered life-nervous-system.com for the next ten years.

I've described this fantastical journey elsewhere, but in short, it's been the most intense and transformative year of my life—I've learned more than at any other time, including the five-plus years I spent earning my FSA.

life-nervous-system and the Manifesto

The life-nervous-system and its site are still being built. But behind that "under construction" banner is a working chat interface wired to a compute-native stack with Node.js, Python orchestration, Rust integrations, and tool execution that my son, Jackson Rishel, and I developed. While I don't know where the first dollar of revenue will come from, I'm unconcerned. I know we're heading north, and I see the outcomes as inevitable. Whether the path bends slightly east or west along the way is irrelevant.

That conviction began the first time I used ChatGPT—when I realized we were at The Dawn—and everything I've learned since has only deepened it.

The staggering scale of this transformation became clear as I went down the rabbit hole. Around the Fourth of July 2024, I pushed deeper into the technology—and for two weeks I became consumed by it, losing track of time entirely. During that period, I interrogated every facet of the life insurance industry—and any industry, really—analyzing how this technology would transform it.

A year later, I sat down to capture what had taken shape during that period—and what emerged was a personal manifesto I titled The Dawn of a New Epoch—And the Life Insurance Industry Is About to Be Disrupted.

It’s a structural argument—not about some vague notion of "AI", but about the convergence of machine learning, cognitive architecture at scale, and the brittle infrastructure of industries like life insurance that make such change inevitable.

And it isn't about a new app or a trend. It's about the wholesale transformation of an industry that hasn't fundamentally changed in half a century.

Call to Action

On every checklist for anything in the marketing domain, there's always a line that says: include a call to action. So here are mine.

First, read The Dawn of a New Epoch.

That's where I am. It's the framework through which I now see the world, and it explains the logic behind everything I've said here. I'm not revisiting the argument, and I'm certainly not interested in poorly informed "AI is evil because it has bias" takes. Because yes, those dangers exist—but they're nuanced, deeply technical conversations that depend not only on how the technology is built, but how it's deployed and used in contexts like policyholder equitability.

Second, partnership.

If you've read it and see what I see, then I'm interested in talking. The path from here involves meaningful work, and there are opportunities to collaborate along the way. As one example, I have an LLM training project on deck—built around a curated knowledge base to test structured data generation and adaptive tuning methods. Within it, there’s room to shape how the solution is structured for my purpose. There will be more like it. If you're serious, let's talk. If not, that's fine too.

Third, selective work.

I'm self-funding and compute time and model calls are expensive. As a result, while consulting isn't the goal, I'll take on a limited number of projects where I know I can add value and stay aligned with my direction of travel. So if you need someone who understands the interconnected nature of risk across the life insurance supply chain—and can assess it with independence, technical depth, and strategic clarity—let me know. Whether that takes the form of an independent risk review or targeted strategic guidance, that's a win-win.

That's it. Those are the calls to action. Everything else—the theory, the logic, the argument—is already in the paper.

If you get it, you'll know why this matters. If you don't, that's fine too. I'm heading north either way.