Using rpois and rnbinom with dplyr commands

I am trying to generate random numbers within a tibble where different categories of item are distributed differently. I'm not having much luck. Here's the code and the error it produces:

library(dplyr)

letters <- tibble(letter = c(rep("A", 5), rep("B", 5), rep("C", 5) ))

letters %>%
  rowwise() %>%
  mutate(Proj = case_when(
    letter == "A" ~ rpois(1, lambda = .7746),
    letter == "B" ~ rnbinom(1, size = 3.3848, mu = 1.2),
    letter == "C" ~ rpois(1, lambda = .5057)
  ))

#> Error in `mutate()`:
#> ! Problem while computing `Proj = case_when(...)`.
#> ℹ The error occurred in row 1.
#> Caused by error in `` names(message) <- `*vtmp*` ``:
#> ! 'names' attribute [1] must be the same length as the vector [0]

Interestingly, the code works just fine if I use continuous distributions instead of discrete distributions.

library(dplyr)

letters <- tibble(letter = c(rep("A", 5), rep("B", 5), rep("C", 5) ))

letters %>%
  rowwise() %>%
  mutate(Proj = case_when(
    letter == "A" ~ rweibull(1, shape = 2.3487, scale = 8.174),
    letter == "B" ~ rexp(1, rate = .0442),
    letter == "C" ~ rnorm(1, mean = 0, sd = 1)
  ))

#> # A tibble: 15 × 2
#> # Rowwise: 
#>    letter   Proj
#>    <chr>   <dbl>
#>  1 A       9.82 
#>  2 A       7.72 
#>  3 A      12.9  
#>  4 A       7.81 
#>  5 A       6.44 
#>  6 B      10.4  
#>  7 B       3.14 
#>  8 B       1.48 
#>  9 B      28.7  
#> 10 B      11.0  
#> 11 C      -0.378
#> 12 C      -0.340
#> 13 C       1.81 
#> 14 C       1.03 
#> 15 C      -0.679

^{Created on 2022-07-29 by the reprex package (v2.0.1)}

What's going on here?