Line5 builds physical AI: robots running computer vision in the field. I joined the early team as an architect and helped set the technical foundation, including the GPU vision pipeline that reads the world in front of the robot. I also worked on defining the communications layer and choosing how tools such as ROS 2 and Zenoh can work well together, each doing the part it is good at.

A significant part of the work was the human factor: backend, robotics, and ML engineers were each used to working to their own standards and each team had their own idea of what code should look like.

I helped build shared ground: common libraries and data types moved into one place that every service imports, and new services started from one template instead of from whichever service happened to be nearest. Ad-hoc structures gave way to typed ones, down to physical quantity types for the navigation math, so a distance in metres could not be quietly added to one in feet. And I pointed the coding agents we had on the team at the same rules and the same lint that gate a person’s branch.