Longevity for All: Smarter Systems, Not Just More Signals

Fifteen years ago, one of my first big-stage talks was about data and wisdom. Back then, I argued that we were chasing numbers without asking the bigger question: “What problem are we trying to solve?”

Fast forward to today, and healthcare is more quantified than ever. Wearables, blood panels, microbiome maps, genome readouts, we have millions of data points. Yet population health outcomes haven’t shifted much. For many, the result isn’t health, but data neurosis.

I’m reminded of the Pi paradox. Mathematicians have calculated trillions of decimals, but the circle doesn’t get any “rounder.” At 3.1416 you can land a rover on Mars. At 31 trillion digits, you’re no closer to “the bottom.” Biology is like that. The more we measure, the deeper the well seems.

The Problem with More Data

Healthcare systems, startups, and even patients are seduced by the idea that more measurement equals more control. We hoard dashboards, chase biomarkers, and obsess over the latest sensors.

But more isn’t always better. Without clarity on the problem we’re solving, data becomes noise. Instead of insight, it creates anxiety:

• Patients left wondering what their latest “out-of-range” metric really means.
• Clinicians overwhelmed by feeds they can’t integrate into workflow.
• Founders burning capital on collection, not application.

Data without wisdom leads to three risks:

1. False confidence - believing tracking = prevention.
2. Overload - drowning frontline staff in signals.
3. Inaction - when no one knows what to do with the numbers.

What Wisdom Looks Like in the AI Era

Wisdom isn’t the opposite of data. It’s what gives data meaning.

Clinicians develop wisdom through pattern recognition across thousands of patient encounters. AI, meanwhile, can process subtle correlations humans would never spot. The opportunity lies in combining the two, intuition and intelligence.

The challenge is workflow. No physician wants to scroll through raw data from 100 patients’ devices. What they need is a system that flags: “These five are trending high-risk. Act here.”

That’s wisdom at scale.

Founders and healthtech leaders need to ask:

• Are we defining the patient outcome first?
• Are we choosing the minimum useful data to get there?
• Are we closing the loop from signal → decision → action → improvement?

Because wisdom isn’t dashboards. It’s responsiveness.

Founder Responsibility

For founders, the temptation is to keep building more features, more integrations, more metrics. It looks good on a slide deck. But the companies that scale are those that focus.

I tell every Series A founder I advise:

• Pick one pathway, one KPI, one loop to close.
• Validate the workflow with clinicians.
• Build trust in the data, not just volume.

Your job isn’t to dazzle investors with decimals. It’s to build systems that make prevention possible.

We already have the tools. Continuous biometrics, AI diagnostics, digital twins - the potential is here. But unless we design for wisdom, all we’re doing is collecting digits of Pi.

The circle doesn’t get more circle. Biology doesn’t get simpler.

The future of healthcare won’t belong to the companies with the most data. It will belong to those who make the right decision, at the right time, for the right person.

Data without wisdom is dangerous. Data with wisdom can change the world.

I’d love to hear your perspective — how do we make prevention mainstream?