I'm sure there is a simple way to create a new column with mutate aggregating many columns at once. So, for a tibble
library(tidyverse)
tbl <- tibble(a = 1:3, ab = 1:3 * 2, b = letters[1:3]) %T>% print()
#> # A tibble: 3 x 3
#> a ab b
#> <int> <dbl> <chr>
#> 1 1 2 a
#> 2 2 4 b
#> 3 3 6 c
apply something like
tbl %>% mutate(aggr_column = sum(vars(starts_with("a")))
and get aggr_column with values c(3, 6, 9)
You can do something like this:
library(tidyverse)
tbl <- tibble(a = 1:3, ab = 1:3 * 2, b = letters[1:3])
tbl %>%
mutate(aggr_column = rowSums(select(., starts_with("a"))))
#> # A tibble: 3 x 4
#> a ab b aggr_column
#> <int> <dbl> <chr> <dbl>
#> 1 1 2 a 3
#> 2 2 4 b 6
#> 3 3 6 c 9
Created on 2018-09-13 by the reprex package (v0.2.0).
I've found my own code that I wrote a week ago 
library(tidyverse)
tibble(a = 1:3, ab = 1:3 * 2, b = letters[1:3]) %>%
mutate(agg = pmap_dbl(select(., starts_with("a")), sum))
#> # A tibble: 3 x 4
#> a ab b agg
#> <int> <dbl> <chr> <dbl>
#> 1 1 2 a 3
#> 2 2 4 b 6
#> 3 3 6 c 9
pmap_dbl is indeed how I would do/did it "in general", but from your questions I got a vibe that you value "code golf" a bit more, so decided to make it as concise as possible