Humans & Longevity
I think, humans would become the first species to solve ageing and could eventually live up to 300 years or more.
I recently read Andreessen Horowitz’s The State of Longevity, and it struck me how quickly longevity has moved from niche and slightly fringe to a legitimate consumer healthcare category.
People aggressively want to spend more time, effort & money on the pursuit of living healthier and longer. And we are slowly but steadily making progress towards it.
We have more health data than ever
We can now collect a lot of information about our own health. Your watch estimates your heart rate, sleep, activity and sometimes aspects of your cardiovascular fitness. You can get comprehensive bloodwork without a doctor ordering every test. You can track your glucose, recovery and training load. Increasingly, AI can translate all of it into something that looks understandable.
But data isn’t understanding, and understanding isn’t action.
Look at the full body checkup. Many adults in India have a recent one from Redcliffe, Orange Health, Thyrocare or Lal PathLabs: 40 to 90 numbers with the lab’s “normal” range next to each, and nobody to explain them. Lab PDFs end up in WhatsApp, sleep sits in one app and steps in another, and nothing connects, so nothing adds up. A routine report checks whether you’re sick today. It doesn’t tell you how fast you’re heading there.
Take a fasting glucose of 98 mg/dL. It sits inside a typical 70 to 100 range, so it gets a green tick and the word “Normal”. It can still be an early signal worth a second look, and nothing on the report says so. Normal for the lab isn’t the same as optimal.
I can know that my LDL is higher than I’d like, my sleep has deteriorated over the last month and my resting heart rate has gone up. That still doesn’t tell me what to do tomorrow morning. Should I change my diet? Exercise differently? Sleep more? Talk to a doctor? Repeat the test? Ignore it because the change isn’t clinically meaningful?
I think this is where the next generation of health products gets built.
The hard part is turning data into better decisions and then making consumers of that data take meaningful actions.
The problem with the quantified-self era
There’s also a risk that longevity becomes another version of consumer wellness. We’ve seen this with supplements. Every new biomarker becomes an optimisation opportunity, every new wearable promises deeper insights, every new molecule gets billed as the next breakthrough. Suddenly staying healthy feels like a full-time job.
I don’t think it should go that way. If longevity means waking up every morning to measure 25 biomarkers, take 17 supplements, optimise a sleep score and obsess over every fluctuation in glucose, we’ve probably built the wrong product.
The best health technology should eventually become invisible and reduce cognitive load. It should decide which biomarkers are worth testing so you don’t have to. It should tell you what matters, what doesn’t, and what you can do about it, and it should know when the right answer is:
Don’t worry about this.
When your numbers look good, it should say so plainly, and explain the reassuring patterns the same way it explains the worrying ones.
Healthcare has always been reactive
Another problem with today’s healthcare is that most of us interact with healthcare when something is already wrong. You develop symptoms, see a doctor, get tested, receive a diagnosis and get treated. There’s nothing wrong with that model. Modern medicine is extraordinarily good at treating disease. But it isn’t designed around the question:
How do I stay healthy for the next decade or the next 30 years?
That’s a different problem & It requires treating health as continuous rather than episodic. Your bloodwork from six months ago matters, and so do your sleep over the last year, your fitness trajectory, your family history, your metabolic health and your behaviours. Most of all, the relationships between them matter. A lab report lists markers one by one, but triglycerides, HDL, HbA1c and ALT can all move together when the body handles sugar and fat a certain way. Read separately, each number can look fine. Read together, they tell a story.
That’s what interests me about the “healthcare home” idea a16z discusses. We already have dashboards that put every health metric in one place. The opportunity is a product that understands the person behind the data. A ten-minute appointment that ends with “everything is normal” leaves one question open: Normal for whom, and for how long?
Healthspan comes first
Adding years isn’t enough. If someone lives to 100 but spends the final 25 years with chronic disease, disability and declining independence, that’s not a compelling outcome.
What matters is healthspan. How long can you remain physically capable? Cognitively healthy? Independent? How long can you keep doing the things that make life worth living?
That’s also how I think about much longer lives. The version I find convincing holds the body at a younger biological age rather than stretching out old age. If aging is a speed, the long bet is slowing it far enough that the body stops getting older. Getting there starts with measuring it, then detecting risk earlier and intervening before small problems become large ones, in ways people can actually follow.
Longevity shouldn’t just be for people who can afford to optimise
Much of the current discourse is shaped by Silicon Valley, wealthy early adopters and people willing to spend significant money on optimisation. New technologies almost always start like that. But if longevity is going to become a meaningful healthcare movement, it has to reach ordinary people.
That’s where India gets interesting. India doesn’t have the same healthcare system, consumer behaviour or disease profile as the United States. We have a huge population, rapidly improving digital infrastructure, increasingly accessible diagnostics and ubiquitous smartphones. Preventive healthcare, though, is still not embedded in everyday behaviour for 99% of the population.
That’s an unusual opportunity. We don’t need to copy the American longevity market. Indians develop diabetes and heart disease earlier, and at lower body weights. Reading that risk against the South Asian metabolic profile, with more visceral fat and insulin resistance, is a different job from reading it against a Western average. So is fitting a protocol to how people here actually eat, work and sleep, rather than to a Californian’s routine. It also has to work on a phone first.
India might skip a generation of healthcare
Another thing that I find interesting about India is that we don’t have to reproduce the systems that existed elsewhere. India skipped traditional banking infrastructure in many ways because UPI made digital payments seamless. The same could happen in healthcare.
Imagine a young person in India connecting the wearable they already wear, getting periodic bloodwork, understanding their major health risks, tracking meaningful changes over time and receiving personalised guidance without navigating a dozen disconnected services. That kind of product would help someone answer:
How am I doing? What should I care about? What should I change? Is it working?
That’s much closer to what I think preventive health should look like.
Thriiv
This is also why I’m building Thriiv. Our line at Thriiv is that -
“Aging is a speed, and you can slow yours.”
Thriiv measures how fast your body is really aging, then builds a protocol from your own data to slow it down, and adapts it as you change. And it is optimised in a way that health becomes something you can understand and actively manage, not something you only think about when you’re sick.
The membership we’re currently building runs on a four-step loop. You bring your blood work (or get one done via Thriiv) and connect your wearable, and Thriiv estimates your biological age and shows what’s driving it. You get a protocol built from your data rather than population averages. It ranks the changes most likely to slow your aging by impact. As new data comes in, the protocol updates. What works stays, and what doesn’t changes. When you retest, you watch your biological age and markers move over time.
Most health apps give you a number, like a recovery score of 64, and leave you to work out what it means. We’d rather tell you what it means for how you’re aging, and then give you the next move like “Move dinner before 8pm this month. Your fasting glucose is drifting up.”
We’re opening in stages, starting with the waitlist.
The first product that we would be launching is a free analysis of the blood report you already have. You upload the bloodwork, and Thriiv reads the markers, compares each one with the lab’s range and with what’s optimal, and explains in plain language what stands out and how the markers connect. It explains and doesn’t diagnose, and it doesn’t recommend medicines or supplements, as of now. It tells you which tests your report is missing, like ApoB, hs-CRP or fasting insulin, and what each would clarify. It also gives you questions to take to your doctor, with your own numbers in them. The protocol and biological age come later, with the membership.
We’re still very early, and I don’t have all the answers. Building in this space has made me realise how many questions there are -
- What should go into a meaningful health score?
- Which biomarkers are useful?
- How should wearable data be interpreted?
- How do you tell a clinically meaningful signal from noise?
- How do you personalise recommendations?
- How do you make something scientifically rigorous without making it impossible for a normal person to understand? and many more questions.
We have some answers so far. Everything that Thriiv tells you also shows its reasoning, so you see which markers drove each change and why. Your data is encrypted, never sold, and yours to export or delete anytime.
Solving ageing consists of very hard problems, and they’re the ones I find most interesting. I think whoever makes health data useful will win, whether or not they collect the most of it.
Where this is going
Over the next decade, health data will become more continuous and AI will get better at interpreting it. Diagnostics will get cheaper, wearables less intrusive and drugs more targeted. People will expect to understand what is happening inside their own bodies, more and more.
Further out, I think humans will live 300 years or more. If medicine can hold the body at a biological age of 25 to 35, illness stops being the usual cause of death and accidents become the main risk.
People in their 200s could keep working, which would help with falling birth rates and shrinking workforces. Scientists could run projects that span centuries, and people would have more time to pursue their own goals. Medicine would shift from treating age-related illness to treating injuries, since most of what sends people to the doctor today would disappear. Governments may push these treatments if they cost less than care in old age.
If we treat ageing like a disease, and successfully defeat it, I feel that would be humanity’s greatest achievement.