Reliable tracking and calculation of nutrition is cumbersome and unreliable. You never fully know what the exact ingredients are and even then it still remains a theoretical calculation that took a lot of effort, not a measurement. If you wanted to measure nutrition in a very reliable way, you would need to burn an identical portion of your food in a calibrated machine to measure the energy output. And even then, the effect on your body is not taken into account. We try to stick to facts and results: what did you take and what was the resulting measurement in mass, mood, body feel. If you take more than you burn, you gain mass. If you take less than you burn, you lose mass. What you need to do is to log it, adjust, to see what works for you. That is all.

Of course, if you are an elite athlete with a dedicated nutritionist professor, you probably weigh everything you eat and do weekly blood tests and performance measurements. But for the vast majority of athletes and normal people, light logging is enough, as long as you measure as well.

We hold on to easy-to-get measurement data: a scale and your mood/bodily feel. We use a lightweight logging tool and see the effect of it in our measurements. We adapt, we continue and we are happy. 🙂 The a.i. component just helps to recognise data contextually, so it is easier to log.

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