Post-editing of machine translation output is usually done to improve the quality of the machine translation output. This can be done as a translation method, but post-editing can also be used to evaluate and improve machine translation systems or in the context of L2 language learning and writing. In this chapter, we reflect on what sets post-editing apart from revision and human translation, what the impact is on productivity, quality, and cognitive load, and how changes in technology are influencing the post-editing process.