Some AI researchers aim to make useful machines, including robots. Others aim to understand general principles of information-processing machines whether natural or artificial, often with special emphasis on humans and human-like systems: They primarily address scientific and philosophical questions rather than practical goals. However, the tasks required to pursue scientific and engineering goals overlap considerably, since both involve building working systems to test ideas and demonstrate results, and the conceptual frameworks and development tools needed for both overlap. This paper, partly based on requirements analysis in the CoSy robotics project, surveys varieties of meta-cognition and draws attention to some types that appear to play a role in intelligent biological individuals (e.g. humans) and which could also help with practical engineering goals, but seem not to have been noticed by most researchers in the field. There are important implications for architectures and representations.