A note on this series: This is a series of my software engineering philosophies focusing on the intersection of the regulated life science sector and the traditional software design paradigm. No proprietary projects or algorithms are shared; insights are based on my personal experiences and opinions shared within are my own and do not represent the view of my past or current employer.
“Anti-ti-ti-fragile,” as LE SSERAFIM would say. When that K-pop earworm dropped in 2022, tech Twitter briefly discovered Nassim Taleb’s decade-old concept and ran with it like retail investors discovering options trading. But beneath the memes and misunderstandings lies something profound for medical software: what if our Focus Restoration Device™ didn’t just survive chaos but actually got better because of it?
Let me paint you a picture. It’s 3 AM and Marcus’s tweet about pineapple on pizza just went viral. He’s using our SaMD to manage his dopamine levels while simultaneously handling 15 Twitter threads, responding to DMs, and watching his TikTok repost blow up. Traditional software would flag this as “unhealthy behavior.” But what if this apparent chaos is actually a highly evolved adaptation? What if Marcus’s rapid context switching is the optimal attention pattern for riding the algorithm wave? This is where antifragility enters the chat1.
Behold, let’s use ASCII art to explain. Think bridges: adjust the structure and you move fragile -> robust -> antifragile.
Fragile - beam between piers (bends, then cracks)
[ ] [ ]
[ ]========================================[ ]
[ ] crack! [ ]
Robust - arch on top (holds, doesn't improve)
__..-:'':__:..:__:'':-..__
_.-:__:.-:'': : : :'':-.:__:-._
.':.-: : : : : : : : : : :._:'.
_ :.': : : : : : : : : : : : :'.:
[ ]: : : : : : : : : : : : : ::[ ]
[ ]: : : : : : : : : : : : : : [ ]
:::::::::[ ]:__:__:__:__:__:__:__:__:__:__:__:__:__:_[ ]::::::::::
!!!!!!!!![ ]!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!![ ]!!!!!!!!!!
^^^^^^^^^[ ]^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^[ ]^^^^^^^^^^
[ ] [ ]
[ ] [ ]
Antifragile - arch integrated into bridge
(more compression, more strength)
!!!!!!!!!![ ]!!!!!!!!!!!!!!!!!!!!!!!!!!![ ]!!!!!!!!!!!!
: : : : :[ ]: : : : : : : : : : : : : :[ ]: : : : : :
: : : [ ]: : : : : : : : : [ ]: : : : :
: : [ ]: : : : : [ ]: : :
: :[ ]: : : :[ ]: :
[ ][ ][ ] [ ][ ][ ]
Most SaMD today falls into these three camps: Fragile systems break when Marcus’s campaign name contains special characters. Robust systems handle the special characters but learn nothing. Antifragile systems, however, don’t just handle the special characters; they learn that Marcus is creative and evolve new validation patterns. They feed on chaos, turning every edge case into a lesson. Our Focus Restoration Device™ started robust, handling Marcus’s scheduled content calendars and campaign analytics perfectly. But it wasn’t learning from the unpredictable nature of viral content - each trending moment was a crisis to be managed, not an opportunity for growth. We were playing defense against entropy instead of dancing with it.
The shift to antifragility came when we stopped thinking of our device as static software and started architecting it as a learning organism. This doesn’t mean slapping a generic ML model on top - that’s a great way to get an FDA rejection letter. It means building a validated, unchangeable core for safety-critical decisions (like recommending Marcus step away from the screen during a content crisis) and surrounding it with a “Learning Layer.” This outer layer can adapt without re-validating the core, thanks to frameworks like the FDA’s Predetermined Change Control Plan (PCCP)2. This plan allows you to define “change corridors” - pre-approved boundaries within which your software can evolve. For our Focus Restoration Device™, the PCCP lets it learn new patterns of Marcus’s content virality or adapt to new social media platform changes without touching the core logic that ensures his well-being.
This is hormesis in action: the biological principle where small doses of a stressor make you stronger3. Marcus’s morning coffee is him microdosing a neurotoxin to achieve consciousness. We applied this by running “Chaos Rounds” (throwing absurd scenarios at the device based on Marcus’s actual digital lifestyle). We simulated viral campaign explosions, influencer controversies, and even the sudden, inexplicable virality of Marcus’s behind-the-scenes content creation video. The beautiful thing? When our device met Marcus in real-world action - his campaign being debated by two warring brand communities - it didn’t just survive. It recognized a new species of content crisis and adapted its recommendations for managing the influx of engagement notifications. It had feasted on chaos and gotten stronger. The bonus? It’s guaranteed to be TMZ approved.
The future of medical software isn’t about building fortresses (it’s about growing adaptive systems that thrive on the unpredictable nature of Marcus’s digital chaos).
Previous: Part 3 - Testing the Untestable: When Edge Cases Are The Norm
Next: Part 5 - The Human Interface: Why Perfect UX Can Kill (Coming Soon)
References
Footnotes
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Taleb, N. N. (2012). “Antifragile: Things That Gain from Disorder.” Random House. The concept that systems can benefit from volatility and stress, not just resist them. ↩
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FDA (2024). “Marketing Submission Recommendations for a Predetermined Change Control Plan for Artificial Intelligence-Enabled Device Software Functions.” Guidance establishing frameworks for controlled evolution of AI/ML medical devices. ↩
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Calabrese, E. J., & Baldwin, L. A. (2003). “Hormesis: The dose-response revolution.” Annual Review of Pharmacology and Toxicology, 43, 175-197. The biological principle of beneficial stress adaptation. ↩