I recently discovered that my testosterone level is 796 ng/dL.
That is high-normal for a human man. It is also, rather unexpectedly, in the vicinity of levels reported in breeding bulls.
This was amusing enough to produce several minutes of excellent cross-species boasting. But the more interesting point was not that I could now describe myself as hormonally bovine. It was that I knew the number at all.
Most of us navigate our health through a mixture of symptoms, intuition and sporadic contact with the medical system. We feel fine, until we do not. We go to the doctor, get a small set of standard tests, receive a reassuring—or vaguely alarming—message, and return to our lives.
But the body is constantly producing data.
The question is whether we collect it early enough to be useful.
Testing turns health from a story into a measurement
Before the test, I might have described myself as energetic, reasonably healthy and perhaps unusually vigorous for my age.
After the test, I had an actual number.
That number did not explain everything. Testosterone fluctuates by time of day, sleep, illness, weight, medications and laboratory method. Nor does a high result automatically confer strength, virility, happiness or competence with household repairs.
But it provided a baseline.
And baselines are powerful.
Once you know a number, you can ask better questions:
- Is it changing?
- Is the change meaningful?
- What else moved with it?
- Did an intervention work?
- Is something deteriorating before symptoms appear?
The real value of testing is rarely the isolated result. It is the trajectory.
From episodic medicine to continuous understanding
Traditional healthcare is largely organized around episodes.
You become ill. You schedule an appointment. A clinician investigates the complaint. Treatment follows.
That model is indispensable when something is acutely wrong. But it is less effective at detecting gradual changes that accumulate quietly over years: worsening insulin sensitivity, rising ApoB, nutrient deficiencies, inflammation, liver stress or subtle shifts in thyroid and hormonal function.
These processes often begin long before they produce unmistakable symptoms.
Comprehensive testing creates a different model: measure broadly, identify patterns, intervene and test again.
That is one reason LifeX invested in Function Health. Function is building an accessible system around extensive laboratory testing, clinician-reviewed results and longitudinal tracking. Its current membership includes more than 160 tests annually, with an initial broad panel and follow-up testing several months later.
The product is not merely “more blood tests.” The important innovation is organizing the results into something a normal person can understand and revisit.
Healthcare has historically been excellent at generating data and surprisingly poor at returning that data to the patient in a coherent form.
A new diagnostic stack is emerging
Function is one example of a broader transition underway across the LifeX ecosystem and the preventive-health market.
Axo Longevity is developing a biomarker-driven health platform in Europe, beginning with more than 100 biomarkers and combining the results with longitudinal analysis and personalized guidance.
Compound Life is approaching a related problem from the intelligence layer: helping people integrate health information over time rather than treating each lab report, wearable reading or medical encounter as an isolated artifact.
Around these companies sits a wider diagnostic ecosystem:
- advanced blood and biomarker testing;
- continuous glucose and wearable measurements;
- imaging platforms such as MRI and CT;
- cardiovascular and metabolic risk assessment;
- AI systems that interpret results;
- clinical services that determine what should happen next.
Function’s expansion into imaging through Ezra is illustrative. Blood tests reveal one class of signals; imaging reveals another. The future is not likely to belong to a single diagnostic modality, but to systems capable of combining many imperfect signals into a more complete view of the person.
The emerging health stack looks increasingly familiar to anyone who has watched other industries become computational:
sensors → data → interpretation → action → feedback
Medicine has possessed the sensors for decades. What has been missing is a consumer-friendly operating system.
The first benefit is surprise
Comprehensive testing often reveals something you were not looking for.
In my case, the memorable result was testosterone. But the genuinely useful findings may be less flattering: a nutrient deficiency, an inflammatory marker, an unexpected liver enzyme, an unfavorable lipid pattern or a glucose result moving in the wrong direction.
This is the first major benefit of testing:
It allows the body to disagree with your self-image.
People are poor judges of gradual physiological change. We adapt to fatigue. We normalize poor sleep. We attribute declining fitness to age, stress or workload. By the time a trend becomes subjectively obvious, it may have been developing for years.
A laboratory result is not infallible, but it is refreshingly indifferent to narrative.
The second benefit is specificity
“Get healthier” is not a useful instruction.
Lower ApoB is useful. Improve insulin sensitivity is useful. Correct iron or vitamin D deficiency is useful. Retest liver enzymes after changing medication or alcohol intake is useful.
Measurement converts a moral aspiration into an engineering problem.
This matters because generic health advice is already well known:
- sleep adequately;
- exercise regularly;
- eat mostly nutritious food;
- avoid smoking;
- limit alcohol;
- maintain social connection.
The problem is not that humanity has never encountered these ideas. The problem is knowing which intervention matters most for a particular person—and whether it is working.
Testing supplies the feedback loop.
The third benefit is agency
Historically, laboratory results were generated inside a clinical encounter and effectively belonged to the institution that ordered them. Patients might receive a brief summary: normal, abnormal, repeat in six months.
Consumer-oriented diagnostic platforms change the center of gravity.
The individual can see the results, compare them over time, bring them to different clinicians and build a personal longitudinal record.
That does not eliminate the need for physicians. Quite the opposite: better information can make clinical conversations more productive.
But it changes the patient’s role from passive recipient to informed participant.
The phrase “own your health” can sound like wellness marketing. At its best, it means something concrete: own the history, the measurements and the ability to ask informed questions.
More testing is not automatically better
There is an obvious risk here.
The more things you measure, the more likely you are to find an outlier. Some abnormalities are temporary, statistically inevitable or clinically irrelevant. Excessive testing can create anxiety, unnecessary follow-up and expensive detours.
A panel of 100 results will almost never produce 100 perfectly ordinary numbers.
The answer is not to abandon comprehensive testing. It is to improve interpretation.
A useful testing system must distinguish among:
- Urgent findings that require prompt evaluation.
- Persistent risk markers that justify intervention.
- Trends that deserve monitoring.
- Interesting noise that should not provoke panic.
That hierarchy is where clinicians, longitudinal data and increasingly AI-assisted interpretation become essential. A single abnormal reading is a photograph. Health is a movie.
Even strong bulls should not diagnose themselves from one screenshot.
The real product is the loop
A common mistake is to treat diagnostics as the end of the process.
The blood is drawn. The report arrives. The user stares at a dashboard, orders three supplements and moves on.
But the value of testing comes from closing the loop:
Test → understand → act → retest
The second test can be more informative than the first. It tells you whether the apparent problem was real, whether the intervention mattered and whether the system is moving in the desired direction.
This is why repeated measurement is central to companies such as Function and Axo. A baseline without follow-up is biography. A baseline with follow-up becomes a control system.
Prevention begins with legibility
Much of chronic disease develops gradually and invisibly.
Prevention therefore requires making invisible processes legible early enough to alter them.
That does not mean every disease can be prevented, nor that every biomarker can be optimized into submission. Biology is not software, and mortality remains stubbornly resistant to product management.
But many meaningful risks can be identified earlier than they are today.
And earlier knowledge creates options.
You can change diet before diabetes. Address lipid risk before a cardiovascular event. Investigate persistent inflammation before it becomes background scenery. Correct deficiencies before they become symptoms. Establish a baseline while healthy, rather than reconstructing one after something has gone wrong.
Strong like bull, but measured like a scientist
The testosterone result makes for a good headline.
At 796 ng/dL, my testosterone sits near the upper end of the healthy young-male range and comfortably above the roughly 500–600 ng/dL one might expect from an average 27-year-old; it is also squarely in breeding-bull territory, with studies reporting about 400–1,000 ng/dL depending on breed and season. For a final, humbling comparison, a rutting male deer can reach around 1,180 ng/dL—so I may be strong like bull, but I am not yet prepared to head-butt rivals beside the interstate. These cross-species figures are playful rather than medically equivalent, but the leaderboard is clear: average young man < me ≈ breeding bull < antlered forest lunatic.
It is objectively entertaining to discover that one narrow aspect of your physiology overlaps with that of an animal whose principal professional qualifications are mass, confidence and reproductive enthusiasm.
But the deeper lesson is quieter.
The benefit of getting tested is not to win a biological leaderboard.
It is to replace assumption with evidence.
It is to detect the unexpected, establish a baseline, choose more precise interventions and learn whether those interventions worked.
The future of health will not be built entirely in hospitals and clinics. It will also be built through systems that allow people to measure themselves more comprehensively, understand those measurements and act before disease becomes the organizing fact of their lives.
My own testing happened to reveal that, in one highly specific respect, I am strong like bull.
The more important discovery was that the rest of the dashboard still had things to teach me. (Like that I have only 1 kidney…)
Get Tested—Wherever You Live
The broader lesson is simple: you cannot improve what you never measure. LifeX has backed companies making comprehensive, longitudinal health testing easier across three regions: Function Health in the United States, Axo Longevity across the EU27, and Compound Life in Asia, coming soon. Each is building toward the same essential idea: establish a broad baseline, understand the signals in context, act on what matters, and measure again. Ping me for introductions and access codes—bull comparisons not guaranteed.
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