Rico and Torrejon (2012) first reviewed the processes and tasks involved in PE. This was crucial because the competencies and skills listed in the following section of their paper are hypothesised to enable the translator/post-editor to complete the tasks identified earlier. The tasks and processes include (a) ST-related processes, which mainly involve reading, (b) MT-related processes, which encompass reading the MT-output and spotting segments that must be changed, improved, etc., (c) TT production processes relying on the MT-output, (d) TT evaluation processes, (e) reference work-related processes, that is, researching, (f) physical writing processes, and (g) global task-related processes, which control the entire post-editing workflow.

The competencies that enable the post-editor to manage the tasks listed above include linguistic skills, instrumental competence and core competencies (see Figure 4). Core competencies are further broken down into strategic competence and Attitudinal or psycho-physiological competencies, both of which can be traced back to the PACTE model. Strategic competence helps the post-editor in various decision-making processes, whereas attitudinal competence is indispensable in handling subjectivity and uncertainty inscribed in the post-editing workflow.

Linguistic skills include not only communicative and textual competencies in the working languages but cultural and intercultural competence as well. Somewhat surprisingly, subject area competence falls into this category, too.

Instrumental competence, however, has a very different conceptual content than the same phrase used in the PACTE model. Here, it primarily refers to technical knowledge and skills, that is, understanding MT systems, programming, etc. Even research and terminology tasks are seen from a technical perspective, and technical management and maintenance is required from the post-editor. At this point, it is clear that the model is somewhat dated and some of the skills in it (e.g., MT dictionary maintenance) are not relevant at the age of NMT and generative AI.