The 7-Day Experiment That Helped Me Understand My Hunger Cues
As someone who spent years healing from disordered eating, the idea of tracking anything about my food used to make my stomach drop. Numbers once dictated everything I ate—calories, portion sizes, even when I felt “allowed” to be hungry. It took years to rebuild trust with my body, to eat without overthinking it, and to enjoy food again.
So when AI-powered nutrition tools started gaining traction, I wasn’t exactly eager to dive in. But as someone who writes about health and wellness for a living, I couldn’t ignore my curiosity, especially around macronutrients like protein. Study after study links higher protein intake to everything from better body composition and muscle retention to improved satiety and metabolic health.
And yet, despite writing about this nearly every week, I realized I had no idea how much protein I was actually eating. Not because I didn’t care, but because I was wary of falling back into old patterns of obsession.
This time, though, I decided to approach it differently. I wasn’t looking for control or precision. I just wanted insight—to understand how I was fueling my body, not how to restrict it. AI offered a middle ground—a way to gain awareness without getting pulled back into old, rigid tracking habits.
Using AI as a gentle nutrition guide
I started with a simple experiment. Instead of downloading a calorie-tracking app or scanning barcodes, I opened the Notes app on my phone. Throughout the day, I’d jot down what I ate in loose, imperfect terms—nothing measured or weighed. A typical entry might read:
- 1 chicken breast, 1/3 cup quinoa, roasted veggies, a spoonful of hummus.
At the end of the day, I’d paste a few of those meals into an AI tool to estimate my protein intake. My goal was to get a general sense of whether I was nourishing myself the way I thought I was.
If I forgot to log something, I didn’t care. I didn’t track weekends or restaurant meals, because those are about connection and enjoyment—not analysis. Sure, I’d still order something with protein when eating out, but I also enjoyed the fries or dessert without guilt.
Bye-bye snack attacks
Within the first week, a clear pattern started to emerge: on the days I found myself standing in front of the pantry at 4 p.m. or craving something sweet after dinner, I’d almost always eaten less protein, especially at lunch. When I made a conscious effort to bump my midday protein from about 15 grams to closer to 30, those late-afternoon cravings all but vanished.
That small discovery felt surprisingly empowering. I wasn’t forcing myself to resist snacks or using willpower to push through hunger—they just weren’t showing up in the same way. My energy stayed steadier, my focus carried through the afternoon, and I didn’t feel the familiar pull toward a second coffee or a sweet treat to get me through the rest of the day.
AI helped me connect the dots between my habits and my hunger, something that’s easy to overlook when you’re eating on autopilot. Seeing that connection on paper (or in this case, on a screen) validated what my body had been quietly signaling all along: that cravings aren’t a lack of discipline, they’re information.
Instead of trying to outthink or suppress my appetite, I started listening to it—and fueling it. Tracking wasn’t about micromanaging my meals anymore; it was about learning more about my body and responding with curiosity, not control.
The science behind protein
It turns out there’s a reason that small shift made such a big difference. Protein influences key appetite-regulating hormones like ghrelin and peptide YY1, which help signal fullness to the brain. It also slows the absorption of carbohydrates, helping to stabilize blood sugar and energy levels throughout the day.
On a bigger scale, maintaining adequate protein intake supports everything from lean muscle mass to bone health and cognitive longevity. Aim for about 0.7-1 gram of protein per pound of bodyweight a day and 2.5 grams of leucine (an amino acid that kickstarts muscle protein synthesis) at each meal to optimize recovery and strength.
That doesn’t mean you need to weigh food or hit exact macros. For most people, the goal is simply to include a solid source of protein at each meal—about the size of your palm.
Once I started paying attention in this loose, observational way, I naturally made small changes: adding Greek yogurt to breakfast, using bone broth in my soups, or blending an extra scoop of protein powder into smoothies.
The difference in how I felt, especially in my energy and mood, was noticeable. I wasn’t as snacky, my workouts felt stronger, and I had fewer afternoon crashes.
What I learned from tracking (& then letting go)
After about a week, I didn’t need the AI tool anymore. I’d learned what balanced fueling looked like for me. My mental picture of “enough protein” became intuitive instead of numerical.
But the bigger takeaway was psychological: I learned that data doesn’t have to disconnect you from your body—it can deepen your understanding of it. Using AI as an educational tool helped me notice patterns without judgment. I could observe without spiraling into overanalyzing, something that used to feel impossible.
The takeaway
Technology can make it easier than ever to quantify our health habits, but it can also pull us away from intuition if we’re not careful. What I’ve learned is that AI doesn’t have to replace body awareness—it can enhance it.
By using it as a teacher, not a tracker, I gained a clearer understanding of what my body needs to feel nourished, energized, and grounded. And for the first time, numbers didn’t feel like something to fear—they felt like information I could use, then let go of.
