How can we support software professionals who want to build human-adaptive sociotechnical systems? Building such systems requires skills some developers may lack, such as applying human-centric concepts to the software they develop and/or mentally modeling other people. Effective socio-technical methods exist to help, but most are manual and cognitively burdensome. In this paper, we investigate ways semi-automating a socio-technical method might help, using as our lens GenderMag, a method that requires people to mentally model people with genders different from their own. Toward this end, we created the GenderMag Recorder's Assistant, a semi-automated visual tool, and conducted a small field study and a 92-participant controlled study. Results of our investigation revealed ways the tool helped with cognitive load and ways it did not; unforeseen advantages of the tool in increasing participants' engagement with the method; and a few unforeseen advantages of the manual approach as well.