diff --git a/concepts.wip/function-composition/.meta/config.json b/concepts.wip/function-composition/.meta/config.json
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+{
+  "authors": [
+    "colinleach"
+  ],
+  "contributors": [],
+  "blurb": "Julia supports composing multiple functions into one, and piping data through a chain of functions."
+}
diff --git a/concepts.wip/function-composition/about.md b/concepts.wip/function-composition/about.md
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+# About
+
+Julia encourages programmers to put as much code as possible inside functions that can be JIT-compiled, and creating many small functions is, by design, performant.
+
+That tends to leave many small, simple functions, which need to be combined to carry out non-trivial tasks.
+
+One obvious approach is to nest function calls.
+The following example is very contrived, but illustrates the point.
+
+```julia-repl
+julia> first.(titlecase.(reverse.(["my", "test", "strings"])))
+3-element Vector{Char}:
+ 'Y': ASCII/Unicode U+0059 (category Lu: Letter, uppercase)
+ 'T': ASCII/Unicode U+0054 (category Lu: Letter, uppercase)
+ 'S': ASCII/Unicode U+0053 (category Lu: Letter, uppercase)
+```
+
+The disadvantage of this approach is that readability drops rapidly as nesting gets deeper.
+
+We need a simpler and more flexible approach.
+
+## Composition
+
+This is the technique beloved of mathematicians, and Julia copies the mathematical syntax.
+
+An arbitrary number of functions can be [`composed`][comp] together with `∘` operators (entered as `\circ` then tab).
+The result can be used as a single function.
+
+```julia-repl
+julia> compfunc = first ∘ titlecase ∘ reverse
+first ∘ titlecase ∘ reverse
+
+julia> compfunc.(["my", "test", "strings"])
+3-element Vector{Char}:
+ 'Y': ASCII/Unicode U+0059 (category Lu: Letter, uppercase)
+ 'T': ASCII/Unicode U+0054 (category Lu: Letter, uppercase)
+ 'S': ASCII/Unicode U+0053 (category Lu: Letter, uppercase)
+
+# alternative syntax, giving the same result
+julia> (first ∘ titlecase ∘ reverse).(["my", "test", "strings"])
+```
+
+A couple of points to note:
+
+- The starting functions appear in the same order as when nesting, and are executed in right-to-left order.
+- Broadcasting is not simple to use when composing, but can be applied when calling the composed function.
+
+## Pipelining
+
+An alternative might be thought of as the _programmers'_ approach, rather than the _mathematicians'_.
+
+[`Pipelines`][comp] have long been used in Unix shell scripts, and more recently became popular in mainstream programming languages (F# is sometimes credited with pioneering their adoption).
+
+The basic concept is to start with some data, then pipe it through a sequence of functions to get the result.
+
+The pipe operator is `|>` (as in F# and recent versions of R), though Julia also has a broadcast version `.|>`.
+
+```julia-repl
+julia> ["my", "test", "strings"] .|> reverse .|> titlecase .|> first
+3-element Vector{Char}:
+ 'Y': ASCII/Unicode U+0059 (category Lu: Letter, uppercase)
+ 'T': ASCII/Unicode U+0054 (category Lu: Letter, uppercase)
+ 'S': ASCII/Unicode U+0053 (category Lu: Letter, uppercase)
+```
+
+Execution is now strictly left-to-right, with the output of each function flowing in the direction of the arrow to become the input for the next function.
+
+## Limitations, workarounds, and other options
+
+It is no coincidence that the functions used to illustrate composition and pipelining all take a _single_ argument.
+
+Some purely-functional languages, pipe the _first_ argument into a function but allow others to be included.
+
+In contrast, Julia only expects function _names_ (or something equivalent) in a pipeline, without any additional arguments.
+
+There are important technical reasons for this (related to the fact that [`currying`][currying] is not a standard part of the language design).
+The _many_ people who have no understanding of currying should merely accept that this limitation is not a careless oversight, and is not likely to change in future Julia versions.
+
+### Workarounds
+
+We need single-arguments functions that do whatever is needed.
+Fortunately, defining new functions in Julia is easy.
+
+Most simply, we could use an [`anonymous function`][anonymous-function].
+For example, if we have a single input string and we want to split on underscores:
+
+```julia-repl
+julia> "my_test_strings" |> (s -> split(s, '_'))
+3-element Vector{SubString{String}}:
+ "my"
+ "test"
+ "strings"
+```
+
+That vector could then be piped to other functions, as before.
+
+Enclosing the anonymous function in parentheses is optional in this case, but more generally is a useful way to reduce ambiguity.
+
+Equally, we could create a named function, earlier in the program, and reuse it as needed.
+
+[`Closures`][closures] are beyond the scope of this Concept, but anyone familiar with them from other languages will recognise that they offer a more flexible way to create single-argument functions.
+
+```julia-repl
+julia> function makesplit(sep)
+           fs(str) = split(str, sep)
+           fs
+       end
+makesplit (generic function with 1 method)
+
+julia> f_us = makesplit('_')
+(::var"#fs#32"{Char}) (generic function with 1 method)
+
+julia> "my_test_strings" |> f_us
+3-element Vector{SubString{String}}:
+ "my"
+ "test"
+ "strings"
+
+# alternatively:
+julia> "my_test_strings" |> makesplit('_')
+3-element Vector{SubString{String}}:
+ "my"
+ "test"
+ "strings"
+```
+
+Once `makesplit()` is defined, it can be used to work with any separator.
+Note that `makesplit('_')` is a _function call_ that evaluates to another function, which in turn receives input from the pipe.
+
+If this seems confusing, that is normal at first (but it becomes clearer with practice).
+
+### Other options
+
+There has been a long discussion about making pipes more versatile in base Julia, but the various suggestions are mutually incompatible and no agreement has been reached.
+
+Meanwhile, users have taken the usual approach of creating various installable packages that address specific needs.
+None will work within Exercism, but take a look at these if you are interested:
+
+- [`Chain.jl`][chain]
+- [`Underscores.jl`][underscores]
+- [`DataPipes.jl`][datapipes]
+
+[comp]: https://docs.julialang.org/en/v1/manual/functions/#Function-composition-and-piping
+[chain]: https://github.com/jkrumbiegel/Chain.jl
+[underscores]: https://c42f.github.io/Underscores.jl/stable/
+[datapipes]: https://github.com/JuliaAPlavin/DataPipes.jl
+[closures]: https://en.wikipedia.org/wiki/Closure_(computer_programming)
+[currying]: https://en.wikipedia.org/wiki/Currying
+[anonymous-function]: https://docs.julialang.org/en/v1/manual/functions/#man-anonymous-functions
diff --git a/concepts.wip/function-composition/introduction.md b/concepts.wip/function-composition/introduction.md
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+# Introduction
diff --git a/concepts.wip/function-composition/links.json b/concepts.wip/function-composition/links.json
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+++ b/concepts.wip/function-composition/links.json
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+[
+  {
+    "url": "https://docs.julialang.org/en/v1/manual/functions/#Function-composition-and-piping",
+    "description": "Manual section on function composition and piping."
+  }
+]