> Overall, having spent a significant amount of time building this project, scaling it up to the size it’s at now, as well as analysing the data, the main conclusion is that it is not worth building your own solution, and investing this much time. When I first started building this project 3 years ago, I expected to learn way more surprising and interesting facts. There were some, and it’s super interesting to look through those graphs, however retrospectively, it did not justify the hundreds of hours I invested in this project.
The whole "qualified self" movement might be more about OCD and perfectionism than anything else.
It was kinda interesting to see how many times I woke up, or track hours, but to be honest I realised after a few months that when my tracker said "You had good sleep", or "You had bad sleep" I was already aware - I woke up smiling, or grumpy depending on how I'd done.
I didn't ever look at the data and think "I want to go to bed now to catch up on the four hours I missed yesterday". I continued to have mostly consistent hours, but if I was doing something interesting I'd stay awake, and if I was tired I'd go to bed earlier naturally. The graphs and data wasn't providing anything of value, or encouraging me to change my behaviour in any significant way.
I was aware that alcohol affects your next day, even a little. That's because people always say that alcohol is bad for you (surprise surprise). I heard this, so you could say that I was aware. I generally thought about this as "a hangover is bad for you." and was somewhat dismissive of the "even a single drink has a bad effect" mantra.
I did some experimenting, and slowly realized that even a single drink can indeed have an impact on the next day. It's not a hangover, but an impact that I could feel nonetheless. I needed to do some light stats and a lot more journaling to build this awareness. I am now aware that I am aware.
I've been wearing an Apple Watch for close to 10 years. I've tracked my weight as well along those years but nothing crazy like OP. The Apple watch tracked plenty.
I had some strange symptoms and two doctors insisted I had a weak heart and potential heart failure. This was shocking! Turns out I do have a really "weak" rhythm, but heart failure is when your heart is progressively getting worse in it's pumping. I don't even remember which metric he looked at in my Apple health - but basically my heart has always been this way. A doctor looking at a single data point might think I have abnormally low blood pressure/heart rate, but if I've had this for 10 years with no change, the medical assessment is very different - it means nothing. Sometimes boring data is exactly what you need. For this reason, I will probably always wear an Apple watch (or equivalent) moving forward.
Data can feel useless for 10 years until one day it becomes critical. The benefit is spiky and uneven.
I would wager that for most people, most data about themselves will be useless and not worth collecting.
Of course you can’t know what data will be useless or not, so unless the cost of collecting it is minimal or nil (wearing a smart watch, writing down your weight each day/week), it’s probably not worth it.
Spending hundreds of hours to build a solution to capture all data about yourself to find interesting patterns has a huge assumption baked into it: that there are interesting patterns to find.
I did something similar to pull data from my Garmin watch. This meant writing all manner of code to pull data out of FIT files (interesting and often infuriating self-describing file format), coming up with schemas to hold that data to make it queryable, adding visualisations, performing analysis, pattern matching, etc.
The end result is nothing really useful, I had a bunch of scripts that semi-automated some jobs that would have taken 1 minute to do manually and only ever needed to be done a max of five times a day, but I learned a load of things along the way. Often these were useful lessons that can be applied to many other things when developing software.
In a similar vein I've gone to lots of trouble to build a cooling system for my homelab rack (ESP32 to control PWM fans, Dallas 1-wire for reading temp/humidity, exposing measurements as metrics for scraping/observability, designing things to deal with the different voltages involved, etc). I could have just gone and bought an off-the-shelf solution from AC Infinity and installed it in minutes but where would the fun in that be.
I do think it's not worth spending a whole lot of time on, though - hence why the first thing I did was add that mechanism to have Claude build it for me, with me mostly glancing at a plan and saying yes/no. It's the perfect thing to vibe-code - if it breaks, I revert a commit and it doesn't matter because nobody depends on it but me.
Why? Because those individuals tend to spin something up, tell everyone about it (online, and offline) and then stop doing it few days later.
The result then ends up being a false signal for others in the same boat. People who read it, feel a spark of recognition ("someone like me actually figured this out"), and then invest real time, energy, maybe money, into replicating something the author themselves quietly abandoned two weeks later.
Just a small heads up from someone who used to get burned in the past :)
I've absolutely not figured it out, but I now have an agent throwing stuff at the wall (with guidance from read access to e.g. my journal and a few other data sources) to figure it out for me, and it's gotten steadily better.
Above all, it's just interesting. I enjoy reading about the day-by-day progression of a crush or my brutally honest feelings about a trip that produced stunning pictures. It weaves nuance into my history.
A good thing.
What's key is be able to visualize metrics easily on the data and frictionless data entry, I've got a decent setup with iPhone Action + Obsidian + QuickAdd scripts on Obsidian Sync (mobile + laptop). for visualization I use Obsidian Bases and Obsidian notes that run Dataview code blocks and Chart.js, couldn't be happier.
I could track things that are not interesting to reflect on like vitamin D supplementation for accountability but I've never bothered, especially if it's taken ~daily.
I’ve started applying this to my personal life by using Memos (https://usememos.com/ - OSS and selfhosted) for tweet style journaling and only tracking outlier data for sleep, fitness, and health. What over tracking and over planning taught me is that anything normal is effectively just noise. If the data isn't an anomaly, it isn't actionable.
Don’t ask how I know…
tymscar•1h ago