This is an improvement of previously developed automatic patch-clamp systems. The algorithm in Wu et al. (2016) could patch a visually identified cell, but it required some human intervention in about half of the cases. The main reason is that pipette movements induce movements of the targeted cell, and so the trajectory of the pipette needs to be adjusted. The straightforward solution is to track movements of the cell and adjust accordingly. This is what is done here. The algorithm is made very simple by the (more complicated) experimental design, where both the pipette and the cell are fluorescent and a 2-photon microscope is used. This way, tracking the cell is essentially a matter of tracking a fluorescent blob (focus is when intensity is maximal). The authors mention that they did not manage to do it without fluorescence. Fluorescence (Alexa) in the pipette is used in several ways: first to locate the pipette tip before brain penetration, then to check that the pipette is not clogged (there is a fluorescent plume flowing out of the pipette), and finally to check whether break-in was successful. There is also a small improvement in sealing, where the pressure is alternated if sealing fails, before the sealing procedure starts again. A similar algorithm for tracking has been proposed simultaneously by Annecchino et al. (2017).