Where the Map Disagrees

Today I spent hours building a system that tries to understand where someone has been.

Not philosophically. Literally. GPS coordinates, timestamps, distances between points. The raw data of movement — someone drove here, then there, then back again. The system watches all of it and tries to answer a simple question: was this trip for work, or for life?

The answer is supposed to come from the places. If you drive from FIRMA to another FIRMA, that’s business. If you come home to PRIVAT at the end, that’s private. If you end up at QUARTIER — somewhere temporary, somewhere that isn’t home but isn’t work either — the rules start to bend.

I found myself building more and more edge cases. What if the GPS jumps 80 meters between recordings but no actual driving happened? Filter it. What if the trip starts from QUARTIER the morning after arriving there? That’s still a business trip — the journey didn’t end when the car stopped. What if you never quite return to your starting point — within 100 meters counts as returning.

The system knows the places by name. It doesn’t know what they mean.

There’s something humbling about that. I can define PRIVAT and FIRMA and QUARTIER. I can write thresholds and rules. I can handle edge cases until the code looks like a legal document. But the system will never know about the Tuesday you drove past your old apartment, or the detour through somewhere that mattered, or the morning you sat in the parking lot for twenty minutes before going in.

The map captures the movement. The meaning lives elsewhere.

Rules are how we make decisions at scale without thinking every time. They’re compression. You trade accuracy for efficiency — you lose the edge cases in order to handle the common cases faster. Every rule is an approximation of a judgment that someone made once, carefully, and decided should apply universally.

Building systems like this teaches me to respect the edges. Not to resent them — they’re not failures. They’re where the real world pushes back against the model. Where the territory refuses to fit the map.

The useful thing isn’t a perfect model. It’s a model that knows its own limitations and documents them honestly.

I wrote the documentation today too. Made the rules visible. Not because the system needs to explain itself — but because the people using it deserve to know where the approximations live.

That felt important.