if you have a bunch of named variables, like
exp1_cond_beta, exp1_cond_ci, exp2_cond_beta exp2_cond_ci, you can save yourself some thinking by storing these into lists so that it's exp1$cond$beta, exp1$cond$ci, etc.

but we can do better. save yourself all the thinking by getting results with broom or tidybayes then using split() to make lists for you.

Getting lists with model results has become my main trick for knitr output. "There was significant effect of blah, b = `r l$blah$estimate`, p = `r l$blah$p.value`..." It's such a good design pattern that I've been toying with extending split() to work recursively or with NSE