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ABSTRACT Introduction: The success of the robot assisted radical prostatectomy (RARP) procedures depend on a successful team, however the literature focuses on the performance of a console surgeon. The aim of this study was to evaluate surgical outcomes of the surgeons during the learning curve in relation to the bedside assistant's experience level during RARP. Materials and Methods: We retrospectively reviewed two non - laparoscopic, beginner robotic surgeon's cases, and we divided the patients into two groups. The first surgeon completed the operations on 20 patients with a beginner bedside assistant in February - May 2009 (Group-1). The second surgeon completed operations on 16 patients with an experienced (at least 150 cases) bedside assistant in February 2015 - December 2015 (Group-2). The collected data included age, prostate volume, prostate specific antigen (PSA), estimated blood loss, complications and percent of positive surgical margins. In addition, the elapsed time for trocar insertion, robot docking, console surgery, specimen extraction and total anesthesia time were measured separately. Results: There were no significant differences between the groups in terms of age, comorbidity, prostate volume, PSA value, preoperative Gleason score, number of positive cores, postoperative Gleason score, pathological grade, protection rate of neurovascular bundles, surgical margin positivity, postoperative complications, length of hospital stay, or estimated blood loss. The robot docking, trocar placement, console surgery, anesthesia and specimen extraction times were significantly shorter in group 2 than they were in group 1 (17.75 ± 3.53 min vs. 30.20 ± 7.54 min, p ≤ 0.001; 9.63 ± 2.71 min vs. 14.40 ± 4.52 min, p = 0.001; 189.06 ± 27.70 min vs. 244.95 ± 80.58 min, p = 0.01; 230.94 ± 30.83 min vs. 306.75 ± 87.96 min, p = 0.002; 10.19 ± 2.54 min vs. 17.55 ± 8.79 min, p = 0.002; respectively). Conclusion: Although the bedside assistant's experience in RARP does not appear to influence the robotic surgeon's oncological outcomes during the learning curve, it may reduce the potential complications by shortening the total operation time.