Analyses of computer aided translation typi-cally focus on either frontend interfaces and human effort, or backend translation and machine learnability of corrections. How-ever, this distinction is artificial in prac-tice since the frontend and backend must work in concert. We present the first holis-tic, quantitative evaluation of these issues by contrasting two assistive modes: post-editing and interactive machine translation (MT). We describe a new translator inter-face, extensive modifications to a phrase-based MT system, and a novel objective function for re-tuning to human correc-tions. Evaluation with professional bilin-gual translators shows that post-edit is faster than interactive at the cost of translation quality for French-English and English-German. However, re-tuning the MT sys-tem to interactive output leads to larger, sta-tistically significant reductions in HTER versus re-tuning to post-edit. Analysis shows that tuning directly to HTER results in fine-grained corrections to subsequent machine output. 1