This is essentially the principle behind algebraic effects (which, in practice, do get implemented as delimited continuations):

When you have an impure effect (e.g. check a database, generate a random number, write to a file, nondeterministic choices,...), instead of directly implementing the impure action, you instead have a symbol e.g "read", "generate number", ...

When executing the function, you also provide a context of "interpreters" that map the symbol to whatever action you want. This is very useful, since the actual business logic can be analyzed in an isolated way. For instance, if you want to test your application you can use a dummy interpreter for "check database" that returns whatever values you need for testing, but without needing to go to an actual SQL database. It also allows you to switch backends rather easily: If your database uses the symbols "read", "write", "delete" then you just need to implement those calls in your backend. If you want to formally prove properties of your code, you can also do that by noting the properties of your symbols, e.g. `∀ key. read (delete key) = None`.

Since you always capture the symbol using an interpreter, you can also do fancy things like dynamically overriding the interpreter: To implement a seeded random number generator, you can have an interpreter that always overrides itself using the new seed. The interpreter would look something like this

```

Pseudorandom_interpreter(seed)(argument, continuation):

  rnd, new_seed <- generate_pseudorandom(seed, argument)
  with Pseudorandom_interpreter(new_seed):
       continuation(rnd)

```

You can clearly see the continuation passing style and the power of self-overriding your own interpreter. In fact, this is a nice way of handeling state in a pure way: Just put something other than new_seed into the new interpreter.

If you want to debug a state machine, you can use an interpreter like this

``` replace_state_interpreter(state)(new_state, continuation):

  with replace_state_interpreter(new_state ++ state):
       continuation(head state)

```

To trace the state. This way the "state" always holds the entire history of state changes, which can be very nice for debugging. During deployment, you can then replace use a different interpreter

```

replace_state_interpreter(state)(new_state, continuation):

  with replace_state_interpreter(new_state):
       continuation(state)

```

which just holds the current state.