Building an Army of Superhumans
Building an Army of Superhumans
What does it look like and how do we get there?
What is a superhuman? There’s plenty of American culture to feed what this looks like. Enter Chris Evans in the first Captain America.
Yea, we may not have a strange full body machine with multiple simultaneous injection points that immediately increases your muscle mass and aerobic performance. For the critics, there are certainly some gray areas to do something similar over a longer time horizon. But for now we’ll assume most people would not subject themselves to injections to reach a physical health threshold while potentially gambling peak short term fitness levels in exchange for a reduced life expectancy or other health problems.
However, there are other mechanisms to reach a physical health threshold that could be considered “superhuman”. But to do that, we have to first define what superhuman means to the American population. I’d argue a good method to determine this would be to:
Step 1: Select and evaluate common health metrics used by elite athletes and longevity experts
Step 2: Look at the distribution of these metrics across the United States across different age groups
Step 3: Then choose an arbitrary (for now) percentile to reach and exceed in each metric and define a combinatory “score” that wraps all into a singular number we can use to evaluate at scale
Step 1: Select and Evaluate Metrics
To prevent hours of research of too much detail, I’ll keep this list simple (and certainly not exhaustive) to argue the main point of building superhumans with a combined metric score, where the actual de-structured metrics can be changed in the future. Here I’m combining metrics that are associated with longevity and physical performance.
Hours of nightly sleep + strict sleep-wake schedules
Lipid Profile
Resting Heart Rate
VO2 Max
Heart Rate Variability
Lactate Threshold
Total + Free Testosterone - Hypogonadal men have lower life expectancy than men with full androgenization, as well as hypogonadism effect on muscle growth
Step 2: Defining and Distribution Across the U.S.
Again, for simplicity we’ll keep our distribution of metrics across the US rather than the world for both applicability and ease of access to information.
Hours of nightly sleep - we’ll simplify this to 7 hours per night. Currently greater than 33% of American adults and under this threshold. Although an easy number to attain, many still struggle. The average amount of sleep across the U.S. is 6.8 hours per night. An unconfirmed average wake up time is 7:09 am, which we can assume means an average sleep time of around midnight.
Lipid Profile - again we’ll simplify this. The field of Lipidology is LARGE. A lipid is simply organic non-water soluble molecules (referred to as hydrophobic). Lipids can be broken down into many classes, but for our purposes we’ll focus on free sterols and esterified sterols. Cholesterol is found under these classes, where it can either be free (unesterified, called unesterified cholesterol or UC) or esterified (called cholesterol ester). This is a very deep rabbit I have to dive down to further define what peak looks like, but a few key takeaways about cholesterol are:
Resting Heart Rate - Defined as the number of times your heart beats per minute while you're at rest. Average American RHR is between 60-100 BPM, whereas well trained athletes’ RHR is between 30-40 BPM
VO2 Max - Defined as the maximum amount of oxygen that an individual can utilize during intense or maximal exercise. Average Americans sit at 35 to 40 mL/kg/min, whereas well trained athletes hold a VO2 max of 65-80 ml/kg/min.
Heart Rate Variability - Defined as a measure of the variation in time between each heartbeat, regulated by our autonomic nervous system. Average American HRV is between 55 and 105 ms, whereas in athletes found between 70-105 ms. HRV is a much more individualized metric where endurance athletes tend to be higher on the range than strength athletes.
Lactate Threshold (LT) - Defined as the point at which, during incremental exercise, lactate builds up in the bloodstream at a level that is higher than resting values and is measured in millimoles per litre (mmol/L). Average adults hit their LT at 50-60% of their VO2 max, whereas elite athletes hit their LT at 85-95% of VO2 max.
Total + Free Testosterone - There are a number of ranges on the internet and many disputed definitions for what “normal” is. A rough total testosterone range for males is 249-836 ng/dL, with free testosterone in the range of 4.5-25.0 ng/dL.
Step 3: Choose an Arbitrary Percentile and a Single Score
This is the difficult (fun) part. But it would take a large amount of testing and responses to physical training, nutrition, sleep, recovery, and behavioral changes to understand what works. For now, we’ll wait to define what a total score would look like now that we have a rough understanding of what elite looks like in the previous metrics.
How Do We Get There?
Now that we’ve defined an abstract view of what superhuman looks like, how do we achieve that at scale across the U.S.?
We can break that down into phases where would look at the most simple to the most complex answers.
Phase I: Onboard as many people as possible to a simple platform/community that provides specific training, nutrition, sleep, and recovery tracking and programs specific to the individual. This is the most straightforward method as it is almost all digital, and infinitely scalable as the platform + community grow.
Phase II: Now we grow slightly in complexity. At this point we have to understand exactly what is working for who, and understand how their background and health levels are impacted by the tracking/training provided. This is important because it would allow a narrowing down of the provided training. It would also provide extremely specific and accurate training for individuals only based on a few points about their background and current health. With a large enough dataset it would be possible to immediately provide the most accurate information to each individual, at scale.
Phase III: Improved measurement across the metrics we defined as “superhuman”. This slightly diverges from the previously all digital solution. Now it’s necessary to take physical measurements across the metrics we described and periodically check back in to evaluate exactly what is working and further feed the superhuman dataset. But, that is all that’s needed. From there scale is required to grow the total amount of information and narrow down the approach so it is well understood what works for specific individuals, because we’re all special little butterflies. This is important because it reduces the need for everyone to have a number of physical metrics tested. Once it is understood what works for who based on physical tests it becomes easier to revert back to all digital based solely on a few, easier to test metrics (fun fact, Fount is doing something just like this, but currently runs at $2,999 per month for the first 4 months. Their long term trajectory looks similar to these phases however).
Phase IV: The final phase and the peak of complexity. This is where the dataset is opened up to other organizations who also wish to achieve a certain goal with their specific community or userbase. While the individual data is anonymized and held private for each person, the keyed in “answers to the test” are revealed through the API.
Conclusion
There are many companies that focus on helping people achieve a certain goal, whether it be longevity, improving certain values from a blood panel, a physique goal, weight loss, mental health improvement, and many more.
The US Military trains military aged males and females to hold a certain standard within their community, but that is largely a bare-minimum test that looks at physical fitness and BMI. In Special Operations, there is a much greater emphasis on health combined with job-specific performance. But this takes a near-sighted lens to overall performance and longevity. These men and women are often in incredible shape and the best at what they do. However the health levels they attain could fall off after finishing their careers, and some suffer from chronic pain, lasting injuries, or mental health issues (not an all-case, just an outside view, many continue to be the best at what they do after the military and maintain their physical fitness at extremely high levels).
The bottom line: I have yet to see or experience a capitalism infused attack on American health focused on both performance and longevity building superhumans at scale (it is totally possible this is already happening and I just don’t know, but it’s fun to write about!). Maybe it’s an open question for what the American population looks like in 50 years.
Maybe it’s a foolish view on what humans can achieve at scale if more efforts focused on maximizing health. But just think, this is what we could have:
