There are two "Test Design" approaches in CBC software: the "Quick Test" (which is automatically reported when you generate an experimental design) and the "Advanced Test" (which you need to invoke later). If you are looking at a report that tells you it is using OLS, then you are using the "Quick Test".
The "Quick Test" uses OLS (not the actual statistical model you'll end up using to estimate utilities in the end). It zero-centers the design matrix within task and performs a quick OLS analysis. The main virtue of this test is it will quickly report if the design is deficient.
We recommend users also do the "Advanced Test", which you run by clicking Test Design from the Design tab. Then, you check the Advanced Test box. That will generate dummy respondent data with the sample size and None% you request. It runs aggregate logit, reports the standard errors for the utilities and also reports relative D-efficiency. As a basic rule of thumb, we recommend trying to strive for a questionnaire and sample size so that the largest standard error across any of the attribute levels is somewhere around 0.05 for main effects (preferably 0.03)...or 0.10 for interaction effects (preferably 0.06). Of course, this assumes ideal conditions where sample is not terribly expensive to recruit and the population of interest is large.