diff --git a/NEWS.md b/NEWS.md
index 2e678b33..0a0e5147 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -4,6 +4,8 @@
 
 * Started moving error messages to cli (#499, #502).
 
+* Fixed example for `nested_cv()` (@seb09, #520).
+
 ## Bug fixes
 
 * `vfold_cv()` now utilizes the `breaks` argument correctly for repeated cross-validation (@ZWael, #471).
diff --git a/R/nest.R b/R/nest.R
index d3c6b080..d2d3427e 100644
--- a/R/nest.R
+++ b/R/nest.R
@@ -34,18 +34,18 @@
 #'   inside = vfold_cv(v = 3)
 #' )
 #'
-#' first_outer_split <- bad_idea$splits[[1]]
-#' outer_analysis <- as.data.frame(first_outer_split)
-#' sum(grepl("Volvo 142E", rownames(outer_analysis)))
+#' first_outer_split <- get_rsplit(bad_idea, 1)
+#' outer_analysis <- analysis(first_outer_split)
+#' sum(grepl("Camaro Z28", rownames(outer_analysis)))
 #'
 #' ## For the 3-fold CV used inside of each bootstrap, how are the replicated
-#' ## `Volvo 142E` data partitioned?
-#' first_inner_split <- bad_idea$inner_resamples[[1]]$splits[[1]]
-#' inner_analysis <- as.data.frame(first_inner_split)
-#' inner_assess <- as.data.frame(first_inner_split, data = "assessment")
+#' ## `Camaro Z28` data partitioned?
+#' first_inner_split <- get_rsplit(bad_idea$inner_resamples[[1]], 1)
+#' inner_analysis <- analysis(first_inner_split)
+#' inner_assess <- assessment(first_inner_split)
 #'
-#' sum(grepl("Volvo 142E", rownames(inner_analysis)))
-#' sum(grepl("Volvo 142E", rownames(inner_assess)))
+#' sum(grepl("Camaro Z28", rownames(inner_analysis)))
+#' sum(grepl("Camaro Z28", rownames(inner_assess)))
 #' @export
 nested_cv <- function(data, outside, inside) {
   cl <- match.call()
diff --git a/man/nested_cv.Rd b/man/nested_cv.Rd
index 826a9c47..cdb19761 100644
--- a/man/nested_cv.Rd
+++ b/man/nested_cv.Rd
@@ -48,16 +48,16 @@ bad_idea <- nested_cv(mtcars,
   inside = vfold_cv(v = 3)
 )
 
-first_outer_split <- bad_idea$splits[[1]]
-outer_analysis <- as.data.frame(first_outer_split)
-sum(grepl("Volvo 142E", rownames(outer_analysis)))
+first_outer_split <- get_rsplit(bad_idea, 1)
+outer_analysis <- analysis(first_outer_split)
+sum(grepl("Camaro Z28", rownames(outer_analysis)))
 
 ## For the 3-fold CV used inside of each bootstrap, how are the replicated
-## `Volvo 142E` data partitioned?
-first_inner_split <- bad_idea$inner_resamples[[1]]$splits[[1]]
-inner_analysis <- as.data.frame(first_inner_split)
-inner_assess <- as.data.frame(first_inner_split, data = "assessment")
+## `Camaro Z28` data partitioned?
+first_inner_split <- get_rsplit(bad_idea$inner_resamples[[1]], 1)
+inner_analysis <- analysis(first_inner_split)
+inner_assess <- assessment(first_inner_split)
 
-sum(grepl("Volvo 142E", rownames(inner_analysis)))
-sum(grepl("Volvo 142E", rownames(inner_assess)))
+sum(grepl("Camaro Z28", rownames(inner_analysis)))
+sum(grepl("Camaro Z28", rownames(inner_assess)))
 }