For this special Q&A episode of The Augmented Life, my co-founder, Ash Kalb, and I decided to take a break from our usual format and put ourselves in the hot seat. We tackled some of the biggest, most pressing questions from our audience—questions that sit at the bleeding edge of biohacking, personal optimization, and the future of human augmentation.
Cameras are hugely underused in health tracking, primarily because of privacy concerns. But that’s changing. Local AI processing now allows video models to analyze health data without sending footage to the cloud—eliminating the biggest roadblock to adoption.
For example, companies are developing apps that estimate blood pressure from facial micro-expressions. That’s massive—because traditional cuffs are inconvenient and rarely used consistently. Cuffless monitoring could be a game-changer.
Another frontier? Hydration sensors. We all know hydration is critical, but most of us rely on guesswork. Wearable hydration sensors are starting to emerge, promising real-time tracking to optimize daily water intake.
And then there’s toilet monitoring—yes, really. Startups are launching sensors that analyze urine and stool samples directly in the toilet, providing insights into hydration, microbiome health, and even viral load. Ash signed up for two: the U-Scan (a urine analyzer) and the Throne (which takes pictures of your poop). Not sure how his household feels about that, but I give full marks to Throne for the perfect startup name.
I have a strong opinion here: Don’t. It’s a false choice.
Instead of waiting for a single wearable to track everything, build a highly personalized tech stack that works for you.
Take me, for example—I wear both an Oura Ring and an Apple Watch. They track different things, and together, they give me a more complete picture of my health. Some people refuse to wear watches, while others prefer them for workouts but switch to rings overnight. The key is customization—building a stack that suits your life and preferences.
Your body changes over time. Your wearables should too.
Right now, we’re drowning in data but starving for insights.
The biggest opportunity for AI isn’t just collecting more data—it’s making sense of what we already have. But there’s a huge problem: today’s best AI wellness models are trained on clinical data, not consumer wearables.
That means AI can interpret hospital-grade vitals, but it struggles with the time-series data from wearables like Oura Rings and Apple Watches. That’s a major gap. To bridge it, we need AI models that actually understand real-world personal health tracking.
This is exactly what we’re building at Fulcra—a system that connects fragmented personal data to the AI that will actually make it useful.
The breakthrough here comes down to light. New devices use camera-based sensors and advanced signal processing to measure blood pressure without a cuff.
Right now, the best tech can give an accurate blood pressure reading in about one minute—but a minute is a long time for a consumer experience. The next step is reducing that time while improving reliability.
More frequent readings will allow us to track long-term trends, not just individual numbers. Think of it like HRV—until recently, we only looked at heart rate, but now we understand that variability over time is a critical metric. The same will happen with blood pressure once we have more granular, continuous tracking.
Most biohackers I know get stuck in optimization mode—always hunting for the “best” device, the “most accurate” data. But that mindset actually slows you down.
The better approach? Take an abundance mindset. Over-collect now, sort it out later. If you’re not collecting data today, you’ll never have it when you need it.
And here’s the bigger picture: If you want the future to have better sensors, you have to support today’s imperfect ones. Look at what happened with Roombas—early adopters bought them when they were clunky, and now we have an entire industry of home robots. The same thing applies to niche biohacking devices. If you want more innovation, vote with your dollars today.
Most people don’t realize this, but the internet is two completely different things:
That second category produces hundreds of zettabytes of data—orders of magnitude more than the text and images used to train today’s AI models. But right now, all of that data is siloed. AI can’t use it effectively because it’s locked away in separate apps and devices.
This is where high-bandwidth edge connectivity (aka 5G) comes in. The faster we can move raw behavioral data from the edge to AI models, the faster we can unlock meaningful insights. This is why breaking down data silos is so important.
Implantable microsensors could be a massive leap forward in real-time health tracking. One area I’m particularly excited about? Cortisol monitoring.
Right now, most wearables estimate stress levels using indirect markers like HRV. But real-time hormone trackingwould allow us to measure stress directly—without needing to infer it from secondary metrics.
Imagine an AI assistant that could detect when you’re about to make a bad decision and prompt you to step away. Instead of looking back at your stress levels after the fact, you’d have real-time interventions when you actually need them.
That’s the future we’re building toward—one where technology doesn’t just measure our health, but actively helps us optimize it.
