I have been thinking lately about the modern male body, not in the abstract, classical sense of sculpture or anatomy, but as it appears now in algorithm-fed fragments: torsos without context, shoulders engineered by lighting, and abs that seem less earned than optimized. The images arrive uninvited, endlessly scrolling, quietly persuasive. For young men growing up in this environment, the message is neither subtle nor occasional. It is constant: you are not enough, but you could be, if only you tried harder, lifted more, supplemented better, refined yourself further.
In my own youth, masculinity had its pressures, but they were less clinical, less quantified. Strength was something you demonstrated, not something you curated. Today, it has become a project-meticulously tracked, compared, and often monetized. The rise of “looksmaxxing” fascinates me as both a cultural phenomenon and a kind of quiet epidemic. It begins innocently enough: a better haircut, a gym membership, a protein shake. But it can slide, almost imperceptibly, into biohacking, hormone manipulation, and cosmetic interventions that would have once seemed extreme.
From a scientific perspective, this trend raises questions that go beyond aesthetics. Performance-enhancing drugs, whether anabolic steroids, SARMs, or off-label hormone therapies are not benign shortcuts. They interact with endocrine systems in ways that are still not fully understood, especially when used outside controlled medical contexts.
At the FDA, we often think in terms of risk-benefit ratios, population-level outcomes, and long-term safety signals. What strikes me here is how individual desire shaped by social media and peer comparison can override that calculus. The perceived benefit is immediate and visible; the risks are deferred, abstract, and therefore easier to dismiss.
There is also something deeply human underneath all of this. Young men are not simply chasing vanity; they are negotiating identity, belonging, and worth. In Filipino culture, as in many others, physical presence has always carried meaning strength as a proxy for resilience, appearance as a reflection of discipline. But what feels different now is the industrial scale of comparison. The “ideal” body is no longer local or even national; it is global, algorithmically amplified, and often chemically assisted.
I find myself wondering what we might offer as a counter-narrative. Not a rejection of self-improvement that instinct is ancient and, in many ways, admirable but a reframing of what improvement means. Health is not just visible muscle mass; it is metabolic stability, mental resilience, longevity. These are harder to photograph, harder to sell, but ultimately more sustaining. Perhaps the more radical act today is not to optimize endlessly, but to define one’s own baseline of enough.
As someone who has spent a career evaluating evidence and risk, I am cautious about moralizing. But I do think we owe young people honesty. Bodies are not just projects; they are systems. And systems, once pushed beyond their limits, do not always return to baseline. The pursuit of strength should not come at the expense of health, nor should the desire to belong lead to choices that carry unseen consequences.
In the end, I suspect this is less about muscle and more about meaning. What does it mean to be strong? To be seen? To be valued? These are questions no supplement or surgical intervention can fully answer. And perhaps that is where the real work begins.
- Meta: Laid off 8,000 employees and reassigned another 7,000 to AI initiatives as part of an aggressive restructuring.
- Atlassian: Cut 1,600 jobs (10% of its workforce) as it shifted its corporate strategy for the "AI era".
- Block: Reduced its workforce by roughly 40%, with CEO Jack Dorsey citing the efficiency of AI intelligence tools.
- Cisco: Announced the layoff of 4,000 employees to reorganize and redirect investments toward AI infrastructure.
- Wix: Laid off over 1,000 employees (20% of staff) while adapting to changing times and AI adoption.
- Fiverr: Cut its workforce by nearly 30% to reposition itself as an “AI-first” company.
- Volume: AI emerged as a primary driver of layoffs, accounting for nearly 50,000 job cuts across the economy.
- Entry-Level Squeeze: The most damaging effect is a drastic reduction in entry-level jobs, making it historically harder for new graduates to enter the workforce and gain experience
- Regret and Rehiring: Data shows that a significant number of executives who aggressively replaced workers with AI later experience "automation regret." Approximately 29% of organizations have already rehired for positions they initially cut because AI could not complete the remaining 40% to 50% of complex, human-centric tasks.
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