  Software projects rely on what we call project archetypes, i.e., pre-existing
mental images of how projects work. They guide distribution of
responsibilities, planning, or expectations. However, with the technological
progress, project archetypes may become outdated, ineffective, or
counterproductive by impeding more adequate approaches. Understanding
archetypes of software development projects is core to leverage their
potential. The development of applications using machine learning and
artificial intelligence provides a context in which existing archetypes might
outdate and need to be questioned, adapted, or replaced. We analyzed 36
interviews from 21 projects between IBM Watson and client companies and
identified four project archetypes members initially used to understand the
projects. We then derive a new project archetype, cognitive computing project,
from the interviews. It can inform future development projects based on
AI-development platforms. Project leaders should proactively manage project
archetypes while researchers should investigate what guides initial
understandings of software projects.
