In software development, an "Exception Error" occurs when a program encounters an unexpected condition that disrupts the normal flow of instructions.
This week, I encountered a critical exception error.
My mother was admitted to the hospital with pneumonia. In the rush to leave work early and travel to the Valley to see her, the "System"—my carefully curated routine of fasting, clean eating, and exercise—encountered a glitch.
The "Crash"
Stress is a powerful disruptor. Triggered by worry and a disruption in my schedule, I reverted to old code. On the drive down, I stopped at a (keto) bakery. I broke my 22:2 fast early (around 2:00 PM) with treats rather than nutrition.
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| Treats from Locally Baked Outlet (picture credit to them) |
By the time I returned to Halifax that evening, I was mentally and physically drained. I managed to cook a compliant dinner—a simple clean keto chicken curry with cauliflower rice—but the tank was empty. I skipped my calisthenics routine.
Technically, the day was a "failure". The fasting window was broken, keto "treats" were consumed, and the workout was missed.
The Reboot
In the past, this "failure" would have triggered a cascade effect. A bad Friday afternoon would have become a "Cheat Weekend," justified by stress. I would have spiralled.
But this time, the recovery protocol executed immediately.
I didn't beat myself up. I didn't treat the weekend as a write-off. I simply went to sleep, woke up the next morning, and went for my cardio. I weighed in, looked at the data, and resumed operations.
Debugging the Logic: The Binary Trap
Why is the reboot so difficult for so many of us? It comes down to a cognitive distortion that I call "The Binary Trap."
In IT, computers think in binary: 1s and 0s. True or False. On or Off. In dieting, we often apply this same rigid logic to ourselves. We view our diet as a binary state:
State 1: I am "On the Wagon" (Perfect compliance).
State 0: I am "Off the Wagon" (Total failure).
When we operate in this binary mode, a single cookie or a missed workout flips the switch from 1 to 0. The internal monologue says, "Well, the system has crashed. The day is ruined. I might as well order a pizza and start again on Monday." Psychologists call this the "Abstinence Violation Effect" - or more colloquially, the "What-the-Hell Effect."
This is a logic error.
Health is not binary; it is analog. It is a spectrum. One meal at 2:00 PM did not erase six months of metabolic healing. It did not clog my arteries or re-fatten my liver instantly. It was simply a data point—a brief fluctuation in a long-term trend line.
To recover, I had to debug this thought process. I had to acknowledge that perfection is not required for progress. A system that runs at 95% uptime is still an incredibly high-performing system. If I had allowed the shame of the 5% downtime to dictate my weekend, I would have dropped my uptime to 60%.
Data beats drama. I refused to let the emotional weight of a slip-up cause a catastrophic system failure.
The Lesson: Mean Time to Recovery (MTTR)
In reliability engineering, we don't just look at how often a system fails; we look at the Mean Time to Recovery—how quickly it comes back online after a crash.
Perfection is not sustainable. Life happens. Parents get sick, schedules break, and stress tests our resolve. The goal is not to be a robot that never falters. The goal is to be a system that is resilient enough to absorb the shock, acknowledge the error, and reboot immediately.
I stumbled on Friday. I was back on track by Saturday morning. That is the victory.
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