diff --git a/DESCRIPTION b/DESCRIPTION
index 49654176..11a64f95 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: monty
 Title: Monte Carlo Models
-Version: 0.2.39
+Version: 0.2.40
 Authors@R: c(person("Rich", "FitzJohn", role = c("aut", "cre"),
                     email = "rich.fitzjohn@gmail.com"),
              person("Wes", "Hinsley", role = "aut"),
diff --git a/R/packer.R b/R/packer.R
index eb0000f2..6c2a68cb 100644
--- a/R/packer.R
+++ b/R/packer.R
@@ -2,7 +2,7 @@
 ##' unstructured vector of numbers (the vector being updated by an
 ##' MCMC for example) and a structured list of named values, which is
 ##' easier to program against.  This is useful for the bridge between
-##' model parameters and a models's implementation, but it is also
+##' model parameters and a model's implementation, but it is also
 ##' useful for the state vector in a state-space model.  We refer to
 ##' the process of taking a named list of scalars, vectors and arrays
 ##' and converting into a single vector "packing" and the inverse
diff --git a/R/rng.R b/R/rng.R
index 583e261b..f83074c3 100644
--- a/R/rng.R
+++ b/R/rng.R
@@ -297,7 +297,7 @@ monty_rng <- R6::R6Class(
     ##'
     ##' @param size The number of trials (zero or more, length 1 or n)
     ##'
-    ##' @param prob The mean probability of sucess on each trial
+    ##' @param prob The mean probability of success on each trial
     ##'   (between 0 and 1, length 1 or n)
     ##' 
     ##' @param rho The dispersion parameter (between 0 and 1, length 1 or n)
diff --git a/R/runner-callr.R b/R/runner-callr.R
index 67a5318e..dc2d282a 100644
--- a/R/runner-callr.R
+++ b/R/runner-callr.R
@@ -4,7 +4,7 @@
 ##' this is the same as "worker" processes.  Unless your chains take a
 ##' few seconds to run, this will be slower than running with the
 ##' default serial runner ([monty_runner_serial]), however for long
-##' running chains, the speedup will typically scale with workers
+##' running chains, the speed-up will typically scale with workers
 ##' added, so long as your chains divide neatly over workers.
 ##'
 ##' @title Run MCMC chains in parallel with `callr`
diff --git a/R/runner.R b/R/runner.R
index 6cc9f0d8..35788cc4 100644
--- a/R/runner.R
+++ b/R/runner.R
@@ -54,7 +54,7 @@ monty_runner_serial <- function(progress = NULL) {
 ##' Run MCMC chains in parallel (at the same time).  This runner uses
 ##' the `parallel` package to distribute your chains over a number of
 ##' worker processes on the same machine.  Compared with
-##' [monty_runner_callr] (Whch is similar to the "worker" support in
+##' [monty_runner_callr] (Which is similar to the "worker" support in
 ##' `mcstate` version 1), this is very simple.  In particular we do
 ##' not report back any information about progress while a chain is
 ##' running on a worker or even across chains.  There's also no
diff --git a/README.md b/README.md
index 4740e905..40632517 100644
--- a/README.md
+++ b/README.md
@@ -1,7 +1,7 @@
 # monty
 
 <!-- badges: start -->
-[![Project Status: Concept – Minimal or no implementation has been done yet, or the repository is only intended to be a limited example, demo, or proof-of-concept.](https://www.repostatus.org/badges/latest/concept.svg)](https://www.repostatus.org/#concept)
+[![Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public.](https://www.repostatus.org/badges/latest/wip.svg)](https://www.repostatus.org/#wip)
 [![R-CMD-check](https://github.com/mrc-ide/monty/actions/workflows/R-CMD-check.yaml/badge.svg?branch=main)](https://github.com/mrc-ide/monty/actions/workflows/R-CMD-check.yaml)
 [![codecov.io](https://codecov.io/github/mrc-ide/monty/coverage.svg?branch=main)](https://codecov.io/github/mrc-ide/monty?branch=main)
 <!-- badges: end -->
@@ -10,8 +10,6 @@
 
 See the [package vignette](https://mrc-ide.github.io/monty/articles/monty.html) for a basic introduction.
 
-The package is in an early, though rapid, stage of development and we cannot guarantee that interfaces will not change (in fact, we can guarantee that they **will** really).  However the core concepts have now solidified.
-
 The core of the package is built around some basic ideas:
 
 * you have some [statistical model](https://mrc-ide.github.io/monty/reference/monty_model.html) from which you would like to draw samples using MCMC ([`monty::monty_sample`](https://mrc-ide.github.io/monty/reference/monty_sample.html))
diff --git a/inst/WORDLIST b/inst/WORDLIST
index 3a3e998b..7611b273 100644
--- a/inst/WORDLIST
+++ b/inst/WORDLIST
@@ -8,6 +8,8 @@ Poisson
 R's
 SEF
 VCV
+WIP
+burnin
 cli's
 codecov
 composable
diff --git a/man/monty_packer.Rd b/man/monty_packer.Rd
index cd192499..0b316665 100644
--- a/man/monty_packer.Rd
+++ b/man/monty_packer.Rd
@@ -67,7 +67,7 @@ Build a packer, which can be used to translate between an
 unstructured vector of numbers (the vector being updated by an
 MCMC for example) and a structured list of named values, which is
 easier to program against.  This is useful for the bridge between
-model parameters and a models's implementation, but it is also
+model parameters and a model's implementation, but it is also
 useful for the state vector in a state-space model.  We refer to
 the process of taking a named list of scalars, vectors and arrays
 and converting into a single vector "packing" and the inverse
diff --git a/man/monty_rng.Rd b/man/monty_rng.Rd
index 16a16425..20155de1 100644
--- a/man/monty_rng.Rd
+++ b/man/monty_rng.Rd
@@ -387,7 +387,7 @@ Generate \code{n} numbers from a beta-binomial distribution
 
 \item{\code{size}}{The number of trials (zero or more, length 1 or n)}
 
-\item{\code{prob}}{The mean probability of sucess on each trial
+\item{\code{prob}}{The mean probability of success on each trial
 (between 0 and 1, length 1 or n)}
 
 \item{\code{rho}}{The dispersion parameter (between 0 and 1, length 1 or n)}
diff --git a/man/monty_runner_callr.Rd b/man/monty_runner_callr.Rd
index c6e96f83..ebe5b470 100644
--- a/man/monty_runner_callr.Rd
+++ b/man/monty_runner_callr.Rd
@@ -36,6 +36,6 @@ worker processes on the same machine.  If you have used \code{mcstate},
 this is the same as "worker" processes.  Unless your chains take a
 few seconds to run, this will be slower than running with the
 default serial runner (\link{monty_runner_serial}), however for long
-running chains, the speedup will typically scale with workers
+running chains, the speed-up will typically scale with workers
 added, so long as your chains divide neatly over workers.
 }
diff --git a/man/monty_runner_parallel.Rd b/man/monty_runner_parallel.Rd
index 209cf25e..f722c817 100644
--- a/man/monty_runner_parallel.Rd
+++ b/man/monty_runner_parallel.Rd
@@ -24,7 +24,7 @@ A runner of class \code{monty_runner} that can be passed to
 Run MCMC chains in parallel (at the same time).  This runner uses
 the \code{parallel} package to distribute your chains over a number of
 worker processes on the same machine.  Compared with
-\link{monty_runner_callr} (Whch is similar to the "worker" support in
+\link{monty_runner_callr} (Which is similar to the "worker" support in
 \code{mcstate} version 1), this is very simple.  In particular we do
 not report back any information about progress while a chain is
 running on a worker or even across chains.  There's also no
diff --git a/vignettes/dsl.Rmd b/vignettes/dsl.Rmd
index 4c77b693..11f99c10 100644
--- a/vignettes/dsl.Rmd
+++ b/vignettes/dsl.Rmd
@@ -52,14 +52,14 @@ We can draw samples from the model if we provide a `monty_rng` object
 
 ```{r}
 rng <- monty_rng$new()
-theta <- prior$direct_sample(rng)
+theta <- monty_model_direct_sample(prior, rng)
 theta
 ```
 
 We can compute the (log) density at a point in parameter space
 
 ```{r}
-prior$density(theta)
+monty_model_density(prior, theta)
 ```
 
 The computed properties for the model are: