Making Facebook Photos Better
We're constantly working on making Facebook better, and one area where we've been spending a lot of time is on photos. — Coming to Facebook two months ago from Divvyshot (a tiny little photo startup) I was amazed at how much people are using Facebook Photos.
Context & Ripple Effects
This post caps a steady drumbeat on faster, simpler photo uploads in February and bigger photos for better viewing in March — Facebook treating its photo product as something iterated weekly rather than shipped occasionally. All Facebook's pickup framed the specific new feature as face detection, arriving alongside the author's arrival from Divvyshot two months earlier.
The Divvyshot angle matters: a tiny photo startup's founder absorbed into the platform is an early example of Facebook buying photo expertise outright rather than building every capability in-house, at the same moment iPhone usage data showed mobile becoming a primary access path to the site.
First-order effects
- Face detection lowers the effort of tagging, which feeds the tagging-and-notification loop that drives people back to albums their friends appear in.
Second-order effects
- Standalone photo-sharing startups now compete against a free product that ships detection, upload speed, and display-size improvements on a monthly cadence — and that acquires their founders when they get close.
Third-order effects
- Photo infrastructure at Facebook's scale becomes a moat: whoever serves the most photos accumulates the computer-vision and storage expertise that makes each next improvement cheaper, pointing toward automated enhancement and organization rather than manual curation.
The trend: Social platforms are converting photos from a feature into core infrastructure, compounding small improvements and acqui-hired expertise into a durable lead over standalone photo services.