diff --git a/R/aaa_multi_predict.R b/R/aaa_multi_predict.R
index f79e8e9e7..e4a7a0cc7 100644
--- a/R/aaa_multi_predict.R
+++ b/R/aaa_multi_predict.R
@@ -3,7 +3,7 @@
 #' Model predictions across many sub-models
 #'
 #' For some models, predictions can be made on sub-models in the model object.
-#' @param object A `model_fit` object.
+#' @param object A [model fit][model_fit].
 #' @param new_data A rectangular data object, such as a data frame.
 #' @param type A single character value or `NULL`. Possible values are
 #' `"numeric"`, `"class"`, `"prob"`, `"conf_int"`, `"pred_int"`, `"quantile"`,
@@ -38,7 +38,7 @@ multi_predict.default <- function(object, ...) {
 #' @export
 predict.model_spec <- function(object, ...) {
   cli::cli_abort(
-    "You must {.fun fit} your model specification
+    "You must {.fun fit} your {.help [model specification](parsnip::model_spec)}
      before you can use {.fun predict}."
   )
 }
diff --git a/R/arguments.R b/R/arguments.R
index 0e62a0938..f3d3198e4 100644
--- a/R/arguments.R
+++ b/R/arguments.R
@@ -35,7 +35,7 @@ check_eng_args <- function(args, obj, core_args) {
 #' `set_args()` can be used to modify the arguments of a model specification while
 #'  `set_mode()` is used to change the model's mode.
 #'
-#' @param object A model specification.
+#' @param object A [model specification][model_spec].
 #' @param ... One or more named model arguments.
 #' @param mode A character string for the model type (e.g. "classification" or
 #'  "regression")
@@ -134,7 +134,7 @@ maybe_eval <- function(x) {
 #' Evaluate parsnip model arguments
 #' @export
 #' @keywords internal
-#' @param spec A model specification
+#' @param spec A [model specification][model_spec].
 #' @param ... Not used.
 eval_args <- function(spec, ...) {
   spec$args   <- purrr::map(spec$args,   maybe_eval)
diff --git a/R/augment.R b/R/augment.R
index 17af1dd78..a825d3730 100644
--- a/R/augment.R
+++ b/R/augment.R
@@ -2,7 +2,7 @@
 #'
 #' `augment()` will add column(s) for predictions to the given data.
 #'
-#' @param x A `model_fit` object produced by [fit.model_spec()] or
+#' @param x A [model fit][model_fit] produced by [fit.model_spec()] or
 #' [fit_xy.model_spec()].
 #' @param eval_time For censored regression models, a vector of time points at
 #' which the survival probability is estimated.
diff --git a/R/case_weights.R b/R/case_weights.R
index 0c9d45e64..3708f5020 100644
--- a/R/case_weights.R
+++ b/R/case_weights.R
@@ -72,7 +72,7 @@ patch_formula_environment_with_case_weights <- function(formula,
 #' Not all modeling engines can incorporate case weights into their
 #' calculations. This function can determine whether they can be used.
 #'
-#' @param spec A parsnip model specification.
+#' @param spec A parsnip [model specification][model_spec].
 #' @return A single logical.
 #' @examples
 #' case_weights_allowed(linear_reg())
diff --git a/R/convert_data.R b/R/convert_data.R
index 48a751a31..e5881fd14 100644
--- a/R/convert_data.R
+++ b/R/convert_data.R
@@ -160,7 +160,7 @@
 }
 
 
-#' @param object An object of class `model_fit`.
+#' @param object A [model fit][model_fit].
 #' @inheritParams predict.model_fit
 #' @rdname convert_helpers
 #' @keywords internal
diff --git a/R/discrim_flexible.R b/R/discrim_flexible.R
index 8b2826b1a..a0bbf5abd 100644
--- a/R/discrim_flexible.R
+++ b/R/discrim_flexible.R
@@ -51,7 +51,7 @@ discrim_flexible <-
 # ------------------------------------------------------------------------------
 
 #' Update a model specification
-#' @param object A model specification.
+#' @param object A [model specification][model_spec].
 #' @param ... Not used for `update()`.
 #' @param fresh A logical for whether the arguments should be
 #'  modified in-place of or replaced wholesale.
@@ -92,7 +92,7 @@ check_args.discrim_flexible <- function(object, call = rlang::caller_env()) {
   check_number_whole(args$prod_degree, min = 1, allow_null = TRUE, call = call, arg = "prod_degree")
   check_number_whole(args$num_terms, min = 1, allow_null = TRUE, call = call, arg = "num_terms")
   check_string(args$prune_method, allow_empty = FALSE, allow_null = TRUE, call = call, arg = "prune_method")
-  
+
   invisible(object)
 }
 
diff --git a/R/engines.R b/R/engines.R
index f90c77ba3..5545e3cf6 100644
--- a/R/engines.R
+++ b/R/engines.R
@@ -82,7 +82,7 @@ load_libs <- function(x, quiet, attach = FALSE) {
 #' `set_engine("ranger", importance = "permutation")`.
 #'
 #'
-#' @param object A model specification.
+#' @param object A [model specification][model_spec].
 #' @param engine A character string for the software that should
 #'  be used to fit the model. This is highly dependent on the type
 #'  of model (e.g. linear regression, random forest, etc.).
diff --git a/R/extract.R b/R/extract.R
index 040682b6c..70e14d75b 100644
--- a/R/extract.R
+++ b/R/extract.R
@@ -4,7 +4,7 @@
 #' These functions extract various elements from a parsnip object. If they do
 #' not exist yet, an error is thrown.
 #'
-#' - `extract_spec_parsnip()` returns the parsnip model specification.
+#' - `extract_spec_parsnip()` returns the parsnip [model specification][model_spec].
 #'
 #' - `extract_fit_engine()` returns the engine specific fit embedded within
 #'   a parsnip model fit. For example, when using [parsnip::linear_reg()]
diff --git a/R/fit.R b/R/fit.R
index 3f9c7a8ee..6f67f2cae 100644
--- a/R/fit.R
+++ b/R/fit.R
@@ -116,7 +116,9 @@ fit.model_spec <-
            ...
   ) {
     if (object$mode == "unknown") {
-      cli::cli_abort("Please set the mode in the model specification.")
+      cli::cli_abort(
+        "Please set the mode in the {.help [model specification](parsnip::model_spec)}."
+      )
     }
     control <- condense_control(control, control_parsnip())
     check_case_weights(case_weights, object)
@@ -249,7 +251,10 @@ fit_xy.model_spec <-
            ...
   ) {
     if (object$mode == "unknown") {
-      cli::cli_abort("Please set the mode in the model specification.")
+      cli::cli_abort(
+        "Please set the mode in the
+        {.help [model specification](parsnip::model_spec)}."
+      )
     }
 
     if (inherits(object, "surv_reg")) {
diff --git a/R/model_object_docs.R b/R/model_object_docs.R
index c4175329d..e3d973d78 100644
--- a/R/model_object_docs.R
+++ b/R/model_object_docs.R
@@ -1,7 +1,32 @@
-#' Model Specification Information
+#' Model Specifications
 #'
+#' @description
 #'
-#' An object with class "model_spec" is a container for
+#' The parsnip package splits the process of fitting models into two steps:
+#'
+#' 1) Specify how a model will be fit using a _model specification_
+#' 2) Fit a model using the model specification
+#'
+#' This is a different approach to many other model interfaces in R, like `lm()`,
+#' where both the specification of the model and the fitting happens in one
+#' function call. Splitting the process into two steps allows users to
+#' iteratively define model specifications throughout the model development
+#' process.
+#'
+#' This intermediate object that defines how the model will be fit is called
+#' a _model specification_ and has class `model_spec`. Model type functions,
+#' like [linear_reg()] or [boost_tree()], return `model_spec` objects.
+#'
+#' Fitted model objects, resulting from passing a `model_spec` to
+#' [fit()][fit.model_spec()] or [fit_xy][fit_xy.model_spec()], have
+#' class `model_fit`, and contain the original `model_spec` objects inside
+#' them. See [?model_fit][model_fit] for more on that object type, and
+#' [?extract_spec_parsnip][extract_spec_parsnip.model_fit] to
+#' extract `model_spec`s from `model_fit`s.
+#'
+#' @details
+#'
+#' An object with class `"model_spec"` is a container for
 #'  information about a model that will be fit.
 #'
 #' The main elements of the object are:
@@ -140,10 +165,18 @@
 #' @name model_spec
 NULL
 
-#' Model Fit Object Information
+#' Model Fit Objects
+#'
+#' @description
+#'
+#' Model fits are trained [model specifications][model_spec] that are
+#' ready to [predict][predict.model_fit] on new data. Model fits have class
+#' `model_fit` and, usually, a subclass referring to the engine
+#' used to fit the model.
 #'
+#' @details
 #'
-#' An object with class "model_fit" is a container for
+#' An object with class `"model_fit"` is a container for
 #'  information about a model that has been fit to the data.
 #'
 #' The main elements of the object are:
diff --git a/R/predict.R b/R/predict.R
index c8e6b5788..4bc22bd42 100644
--- a/R/predict.R
+++ b/R/predict.R
@@ -4,7 +4,7 @@
 #'  `predict()` can be used for all types of models and uses the
 #'  "type" argument for more specificity.
 #'
-#' @param object An object of class `model_fit`.
+#' @param object A [model fit][model_fit].
 #' @param new_data A rectangular data object, such as a data frame.
 #' @param type A single character value or `NULL`. Possible values
 #'   are `"numeric"`, `"class"`, `"prob"`, `"conf_int"`, `"pred_int"`,
diff --git a/R/req_pkgs.R b/R/req_pkgs.R
index 1fbf2c67a..5324b4778 100644
--- a/R/req_pkgs.R
+++ b/R/req_pkgs.R
@@ -3,7 +3,7 @@
 #' @description
 #' `r lifecycle::badge("deprecated")`
 #'
-#' @param x A model specification or fit.
+#' @param x A [model specification][model_spec] or [fit][model_fit].
 #' @param ... Not used.
 #' @return A character string of package names (if any).
 #' @details
diff --git a/R/required_pkgs.R b/R/required_pkgs.R
index 56b709284..5fb4eb4d1 100644
--- a/R/required_pkgs.R
+++ b/R/required_pkgs.R
@@ -1,6 +1,6 @@
 #' Determine required packages for a model
 #'
-#' @param x A model specification or fit.
+#' @param x A [model specification][model_spec] or [fit][model_fit].
 #' @param infra Should parsnip itself be included in the result?
 #' @param ... Not used.
 #' @return A character vector
diff --git a/R/translate.R b/R/translate.R
index 7a43a3827..eb2ef7158 100644
--- a/R/translate.R
+++ b/R/translate.R
@@ -1,10 +1,10 @@
 #' Resolve a Model Specification for a Computational Engine
 #'
-#' `translate()` will translate a model specification into a code
+#' `translate()` will translate a [model specification][model_spec] into a code
 #'  object that is specific to a particular engine (e.g. R package).
 #'  It translates generic parameters to their counterparts.
 #'
-#' @param x A model specification.
+#' @param x A [model specification][model_spec].
 #' @param engine The computational engine for the model (see `?set_engine`).
 #' @param ... Not currently used.
 #' @details
diff --git a/R/update.R b/R/update.R
index 4658a82e3..3dd890fb4 100644
--- a/R/update.R
+++ b/R/update.R
@@ -18,7 +18,7 @@
 #' @inheritParams svm_linear
 #' @inheritParams svm_poly
 #' @inheritParams svm_rbf
-#' @param object A model specification.
+#' @param object A [model specification][model_spec].
 #' @param parameters A 1-row tibble or named list with _main_
 #'  parameters to update. Use **either** `parameters` **or** the main arguments
 #'  directly when updating. If the main arguments are used,
diff --git a/man/augment.Rd b/man/augment.Rd
index 100645abd..ce482cf91 100644
--- a/man/augment.Rd
+++ b/man/augment.Rd
@@ -7,7 +7,7 @@
 \method{augment}{model_fit}(x, new_data, eval_time = NULL, ...)
 }
 \arguments{
-\item{x}{A \code{model_fit} object produced by \code{\link[=fit.model_spec]{fit.model_spec()}} or
+\item{x}{A \link[=model_fit]{model fit} produced by \code{\link[=fit.model_spec]{fit.model_spec()}} or
 \code{\link[=fit_xy.model_spec]{fit_xy.model_spec()}}.}
 
 \item{new_data}{A data frame or matrix.}
diff --git a/man/case_weights_allowed.Rd b/man/case_weights_allowed.Rd
index 1c070b6b5..1a34a79ac 100644
--- a/man/case_weights_allowed.Rd
+++ b/man/case_weights_allowed.Rd
@@ -7,7 +7,7 @@
 case_weights_allowed(spec)
 }
 \arguments{
-\item{spec}{A parsnip model specification.}
+\item{spec}{A parsnip \link[=model_spec]{model specification}.}
 }
 \value{
 A single logical.
diff --git a/man/convert_helpers.Rd b/man/convert_helpers.Rd
index 5b29bacb1..d25f830bd 100644
--- a/man/convert_helpers.Rd
+++ b/man/convert_helpers.Rd
@@ -57,7 +57,7 @@ should be returned as a \code{"matrix"} or a \code{"data.frame"}.}
 \item{remove_intercept}{A logical indicating whether to remove the intercept
 column after \code{model.matrix()} is finished.}
 
-\item{object}{An object of class \code{model_fit}.}
+\item{object}{A \link[=model_fit]{model fit}.}
 
 \item{new_data}{A rectangular data object, such as a data frame.}
 
diff --git a/man/eval_args.Rd b/man/eval_args.Rd
index b51234e95..59938117f 100644
--- a/man/eval_args.Rd
+++ b/man/eval_args.Rd
@@ -7,7 +7,7 @@
 eval_args(spec, ...)
 }
 \arguments{
-\item{spec}{A model specification}
+\item{spec}{A \link[=model_spec]{model specification}.}
 
 \item{...}{Not used.}
 }
diff --git a/man/extract-parsnip.Rd b/man/extract-parsnip.Rd
index 8d893114a..718942842 100644
--- a/man/extract-parsnip.Rd
+++ b/man/extract-parsnip.Rd
@@ -38,7 +38,7 @@ section.
 These functions extract various elements from a parsnip object. If they do
 not exist yet, an error is thrown.
 \itemize{
-\item \code{extract_spec_parsnip()} returns the parsnip model specification.
+\item \code{extract_spec_parsnip()} returns the parsnip \link[=model_spec]{model specification}.
 \item \code{extract_fit_engine()} returns the engine specific fit embedded within
 a parsnip model fit. For example, when using \code{\link[=linear_reg]{linear_reg()}}
 with the \code{"lm"} engine, this returns the underlying \code{lm} object.
diff --git a/man/model_fit.Rd b/man/model_fit.Rd
index 46c89fe44..ffea26452 100644
--- a/man/model_fit.Rd
+++ b/man/model_fit.Rd
@@ -2,12 +2,17 @@
 % Please edit documentation in R/model_object_docs.R
 \name{model_fit}
 \alias{model_fit}
-\title{Model Fit Object Information}
+\title{Model Fit Objects}
 \description{
-An object with class "model_fit" is a container for
-information about a model that has been fit to the data.
+Model fits are trained \link[=model_spec]{model specifications} that are
+ready to \link[=predict.model_fit]{predict} on new data. Model fits have class
+\code{model_fit} and, usually, a subclass referring to the engine
+used to fit the model.
 }
 \details{
+An object with class \code{"model_fit"} is a container for
+information about a model that has been fit to the data.
+
 The main elements of the object are:
 \itemize{
 \item \code{lvl}: A vector of factor levels when the outcome is
diff --git a/man/model_spec.Rd b/man/model_spec.Rd
index 3345eb89e..6d5faeeed 100644
--- a/man/model_spec.Rd
+++ b/man/model_spec.Rd
@@ -2,12 +2,35 @@
 % Please edit documentation in R/model_object_docs.R
 \name{model_spec}
 \alias{model_spec}
-\title{Model Specification Information}
+\title{Model Specifications}
 \description{
-An object with class "model_spec" is a container for
-information about a model that will be fit.
+The parsnip package splits the process of fitting models into two steps:
+\enumerate{
+\item Specify how a model will be fit using a \emph{model specification}
+\item Fit a model using the model specification
+}
+
+This is a different approach to many other model interfaces in R, like \code{lm()},
+where both the specification of the model and the fitting happens in one
+function call. Splitting the process into two steps allows users to
+iteratively define model specifications throughout the model development
+process.
+
+This intermediate object that defines how the model will be fit is called
+a \emph{model specification} and has class \code{model_spec}. Model type functions,
+like \code{\link[=linear_reg]{linear_reg()}} or \code{\link[=boost_tree]{boost_tree()}}, return \code{model_spec} objects.
+
+Fitted model objects, resulting from passing a \code{model_spec} to
+\link[=fit.model_spec]{fit()} or \link[=fit_xy.model_spec]{fit_xy}, have
+class \code{model_fit}, and contain the original \code{model_spec} objects inside
+them. See \link[=model_fit]{?model_fit} for more on that object type, and
+\link[=extract_spec_parsnip.model_fit]{?extract_spec_parsnip} to
+extract \code{model_spec}s from \code{model_fit}s.
 }
 \details{
+An object with class \code{"model_spec"} is a container for
+information about a model that will be fit.
+
 The main elements of the object are:
 \itemize{
 \item \code{args}: A vector of the main arguments for the model. The
diff --git a/man/multi_predict.Rd b/man/multi_predict.Rd
index ccdaad916..34f3856f8 100644
--- a/man/multi_predict.Rd
+++ b/man/multi_predict.Rd
@@ -38,7 +38,7 @@ multi_predict(object, ...)
 \method{multi_predict}{`_train.kknn`}(object, new_data, type = NULL, neighbors = NULL, ...)
 }
 \arguments{
-\item{object}{A \code{model_fit} object.}
+\item{object}{A \link[=model_fit]{model fit}.}
 
 \item{...}{Optional arguments to pass to \code{predict.model_fit(type = "raw")}
 such as \code{type}.}
diff --git a/man/other_predict.Rd b/man/other_predict.Rd
index 6c997e28d..efe0fbdb0 100644
--- a/man/other_predict.Rd
+++ b/man/other_predict.Rd
@@ -72,7 +72,7 @@ predict_survival(object, ...)
 predict_time(object, ...)
 }
 \arguments{
-\item{object}{An object of class \code{model_fit}.}
+\item{object}{A \link[=model_fit]{model fit}.}
 
 \item{new_data}{A rectangular data object, such as a data frame.}
 
diff --git a/man/parsnip_update.Rd b/man/parsnip_update.Rd
index 51961a67f..922e717c2 100644
--- a/man/parsnip_update.Rd
+++ b/man/parsnip_update.Rd
@@ -312,7 +312,7 @@
 )
 }
 \arguments{
-\item{object}{A model specification.}
+\item{object}{A \link[=model_spec]{model specification}.}
 
 \item{parameters}{A 1-row tibble or named list with \emph{main}
 parameters to update. Use \strong{either} \code{parameters} \strong{or} the main arguments
diff --git a/man/predict.model_fit.Rd b/man/predict.model_fit.Rd
index eaf3364ef..1da83bd09 100644
--- a/man/predict.model_fit.Rd
+++ b/man/predict.model_fit.Rd
@@ -13,7 +13,7 @@
 predict_raw(object, ...)
 }
 \arguments{
-\item{object}{An object of class \code{model_fit}.}
+\item{object}{A \link[=model_fit]{model fit}.}
 
 \item{new_data}{A rectangular data object, such as a data frame.}
 
diff --git a/man/req_pkgs.Rd b/man/req_pkgs.Rd
index 9f7f439fa..79c16a8ea 100644
--- a/man/req_pkgs.Rd
+++ b/man/req_pkgs.Rd
@@ -7,7 +7,7 @@
 req_pkgs(x, ...)
 }
 \arguments{
-\item{x}{A model specification or fit.}
+\item{x}{A \link[=model_spec]{model specification} or \link[=model_fit]{fit}.}
 
 \item{...}{Not used.}
 }
diff --git a/man/required_pkgs.model_spec.Rd b/man/required_pkgs.model_spec.Rd
index 5e490b87e..2ef558b8c 100644
--- a/man/required_pkgs.model_spec.Rd
+++ b/man/required_pkgs.model_spec.Rd
@@ -10,7 +10,7 @@
 \method{required_pkgs}{model_fit}(x, infra = TRUE, ...)
 }
 \arguments{
-\item{x}{A model specification or fit.}
+\item{x}{A \link[=model_spec]{model specification} or \link[=model_fit]{fit}.}
 
 \item{infra}{Should parsnip itself be included in the result?}
 
diff --git a/man/set_args.Rd b/man/set_args.Rd
index 7e6c678d6..b8e4620c5 100644
--- a/man/set_args.Rd
+++ b/man/set_args.Rd
@@ -10,7 +10,7 @@ set_args(object, ...)
 set_mode(object, mode)
 }
 \arguments{
-\item{object}{A model specification.}
+\item{object}{A \link[=model_spec]{model specification}.}
 
 \item{...}{One or more named model arguments.}
 
diff --git a/man/set_engine.Rd b/man/set_engine.Rd
index a032316db..07573b12f 100644
--- a/man/set_engine.Rd
+++ b/man/set_engine.Rd
@@ -7,7 +7,7 @@
 set_engine(object, engine, ...)
 }
 \arguments{
-\item{object}{A model specification.}
+\item{object}{A \link[=model_spec]{model specification}.}
 
 \item{engine}{A character string for the software that should
 be used to fit the model. This is highly dependent on the type
diff --git a/man/translate.Rd b/man/translate.Rd
index 7a8c9c61d..b181fe49e 100644
--- a/man/translate.Rd
+++ b/man/translate.Rd
@@ -10,14 +10,14 @@ translate(x, ...)
 \method{translate}{default}(x, engine = x$engine, ...)
 }
 \arguments{
-\item{x}{A model specification.}
+\item{x}{A \link[=model_spec]{model specification}.}
 
 \item{...}{Not currently used.}
 
 \item{engine}{The computational engine for the model (see \code{?set_engine}).}
 }
 \description{
-\code{translate()} will translate a model specification into a code
+\code{translate()} will translate a \link[=model_spec]{model specification} into a code
 object that is specific to a particular engine (e.g. R package).
 It translates generic parameters to their counterparts.
 }
diff --git a/tests/testthat/_snaps/decision_tree.md b/tests/testthat/_snaps/decision_tree.md
index 41bc8ae1a..539dbcbb3 100644
--- a/tests/testthat/_snaps/decision_tree.md
+++ b/tests/testthat/_snaps/decision_tree.md
@@ -21,11 +21,11 @@
 
 ---
 
-    Please set the mode in the model specification.
+    Please set the mode in the model specification (`?parsnip::model_spec()`).
 
 ---
 
-    Please set the mode in the model specification.
+    Please set the mode in the model specification (`?parsnip::model_spec()`).
 
 ---
 
diff --git a/tests/testthat/_snaps/fit_interfaces.md b/tests/testthat/_snaps/fit_interfaces.md
index 41fc0d75f..15f131073 100644
--- a/tests/testthat/_snaps/fit_interfaces.md
+++ b/tests/testthat/_snaps/fit_interfaces.md
@@ -20,7 +20,7 @@
       fit(mars_spec, am ~ ., data = mtcars)
     Condition
       Error in `fit()`:
-      ! Please set the mode in the model specification.
+      ! Please set the mode in the model specification (`?parsnip::model_spec()`).
 
 ---
 
@@ -28,7 +28,7 @@
       fit_xy(mars_spec, x = mtcars[, -1], y = mtcars[, 1])
     Condition
       Error in `fit_xy()`:
-      ! Please set the mode in the model specification.
+      ! Please set the mode in the model specification (`?parsnip::model_spec()`).
 
 ---
 
@@ -36,7 +36,7 @@
       fit_xy(mars_spec, x = lending_club[, 1:2], y = lending_club$Class)
     Condition
       Error in `fit_xy()`:
-      ! Please set the mode in the model specification.
+      ! Please set the mode in the model specification (`?parsnip::model_spec()`).
 
 # misspecified formula argument