S
Shaant
Guest
Personalized insights transformed my nights and energized my days.
Photo by Adi Goldstein on Unsplash
Rest has always been like sand slipping through my fingers. Some nights I was left feeling like I hadnโt slept at all. Iโd awaken staring at the ceiling, feeling crushed by weariness.
Other nights Iโd swear that I was asleep, and yet dragged myself through the day with heavy eyes and a cloudy mind.
For years, I relied on the usual advice. Donโt drink coffee too late. Go to bed at the same time. Keep your room cool and dark.
None of it explained the next morning when I woke up feeling like a machine starting on a dead battery.
Thatโs when I turned to AI.
I had already been using it to explore diet and fitness experiments, but allowing it to analyze my sleep data opened a door I didnโt even know existed.
I gave it the numbers I downloaded from my Apple Watch and the weight and body fat data I had been tracking forever.
By themselves, the numbers just felt like noise.
With the help of AI, they formed a narrative. A narrative about my body, my habits, and the way I spent my nights.
I learned my rest had not happened randomly. It had patterns, thresholds, and correlations.
For example, my weight was directly linked to my sleep apnea. Once I slipped below 100 kilos, everything changed.
My apnea events dropped almost immediately, though not instantly.
The AI indicated a delay. It took my sleep a week or two after weight loss to improve, as if to catch up with my new self.
Sleep was no longer just sleep.
It was data-rich territory, and finally, I had a map.
When the body speaks in numbers, AI knows how to listen
Initially, I couldnโt make sense of all that data. I logged how many nights I used a sleep mask, heart rate variability, weight, and even recorded notes on my meals and workouts.
I felt like I had random pieces of a jigsaw puzzle with no picture on the box.
The AI provided my โpuzzle picture.โ
It demonstrated that small changes, like regaining three kilos, caused my apnea index to rise again. It showed me that lean durations were more important than perfection over time.
It also identified that my โsweet spotโ was around 78 to 80 kilos. This was my therapy result-based weight range and a range that made me feel lighter each morning.
The AI shifted my view of sleep stages.
I used to get stuck on whether I had enough deep sleep. I would โevaluateโ Welltoryโs charts against Apple Health. One would say I had ninety minutes. The other is barely twenty.
I messed with myself, wondering who told the truth.
The AI shifted my perspective and highlighted that sleep stages recorded by wearables arenโt the absolute truth.
What needs to be measured is what is measurable. I needed to stay focused on consistency, heart rate, and recovery.
The liberation was liberating.
This wasnโt about chasing perfect numbers on a screen. It was about understanding which numbers actually mattered for how I felt.
Thatโs why I stopped panicking about โbad nightsโ and instead learned to look at trends long-term.
For the first time, I understood why one bad night did not devastate me, and why short-term solutions to my issues were never effective.
The hidden cost of ignoring rest
Until this experiment, sleep was background noise.
Workouts, work, and relationships were all urgent. Sleep was just happening in between.
The data illuminated my ignorance of the cost.
When I stayed heavy, my AHI scores, the apnea index, were five times worse. I was micro-choking multiple times every night, which created a jagged pattern of rest, leaving me feeling exhausted even though I didnโt consciously wake.
I thought I was powering through, but I was actually fraying the edges.
My blood pressure was up. I was moody. Even small experiences of joy felt dulled.
AI didnโt just give me a confirmation of these effects. It gave me a quantification of them.
I could see the line graphs spike when I put on weight and flatten out when I lost. I could match late-night meals with poor recovery scores. I could trace restless nights back to non-factors like light in my room from a full moon.
The stories my body has been giving me over the years were finally loud enough to hear.
It was a pretty humbling realization to finally understand how much I had been guessing.
One of the things I used to take pride in was my discipline and just โtoughing it out.โ
But what toughness gave me in stubbornness, it robbed my mornings of.
Real toughness did not come from pushing harder, but from listening better.
Rest is not passive; it is precision
For some time, rest has not been viewed as a passive time.
Rest is active. Rest is nonlinear.
In many ways, AI was the lens that gave me access to its structure. I use it to make a single picture out of my disjointed data.
Apple Watch might misinterpret deep sleep, but when the information is considered with data from my sleep tracker notes, body weight charts, and heart rate variability measurements, the AI filters the noise from the truth.
It gives me a picture of the levers I can actually manipulate, such as reducing body weight, managing exposure to light, and modifying my pre-sleep rituals, and the levers I can abandon with confidence.
What surprised me most wasnโt new science but feeling.
Waking up is different now. I have a quiet clarity in the mornings that implies a fog has lifted.
I am much more patient. My workouts feel deeper. Conversations with my girlfriend even feel richer, because they no longer take place at the same time I am running my life on fumes.
Rest is not, it turns out, the absence of activity. It is the base of it.
The AI didnโt provide me with more hours in a day, but my hours back from what was my half-asleep life.
And that is the biggest secret.
Sleep is not about closing your eyes. It is about opening your life.
How AI Showed Me the True Meaning of Rest by Unlocking Sleep Secrets was originally published in Health and Science on Medium, where people are continuing the conversation by highlighting and responding to this story.
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