diff --git a/docs/source/changes.md b/docs/source/changes.md
index 48c57983..6b13c8ec 100644
--- a/docs/source/changes.md
+++ b/docs/source/changes.md
@@ -7,6 +7,7 @@ releases are available on [PyPI](https://pypi.org/project/pytask) and
 
 ## 0.5.1 - 2024-xx-xx
 
+- {pull}`616` redesigns the guide on "Scaling Tasks".
 - {pull}`617` fixes an interaction with provisional nodes and `@mark.persist`.
 - {pull}`618` ensures that `root_dir` of `DirectoryNode` is created before the task is
   executed.
diff --git a/docs/source/how_to_guides/bp_complex_task_repetitions.md b/docs/source/how_to_guides/bp_complex_task_repetitions.md
new file mode 100644
index 00000000..68e44569
--- /dev/null
+++ b/docs/source/how_to_guides/bp_complex_task_repetitions.md
@@ -0,0 +1,83 @@
+# Complex task repetitions
+
+{doc}`Task repetitions <../tutorials/repeating_tasks_with_different_inputs>` are amazing
+if you want to execute lots of tasks while not repeating yourself in code.
+
+But, in any bigger project, repetitions can become hard to maintain because there are
+multiple layers or dimensions of repetition.
+
+Here you find some tips on how to set up your project such that adding dimensions and
+increasing dimensions becomes much easier.
+
+## Example
+
+You can write multiple loops around a task function where each loop stands for a
+different dimension. A dimension might represent different datasets or model
+specifications to analyze the datasets like in the following example. The task arguments
+are derived from the dimensions.
+
+```{literalinclude} ../../../docs_src/how_to_guides/bp_complex_task_repetitions/example.py
+---
+caption: task_example.py
+---
+```
+
+There is nothing wrong with using nested loops for simpler projects. But, often projects
+are growing over time and you run into these problems.
+
+- When you add a new task, you need to duplicate the nested loops in another module.
+- When you add a dimension, you need to touch multiple files in your project and add
+  another loop and level of indentation.
+
+## Solution
+
+The main idea for the solution is quickly explained. We will, first, formalize
+dimensions into objects and, secondly, combine them in one object such that we only have
+to iterate over instances of this object in a single loop.
+
+We will start by defining the dimensions using {class}`~typing.NamedTuple` or
+{func}`~dataclasses.dataclass`.
+
+Then, we will define the object that holds both pieces of information together and for
+the lack of a better name, we will call it an experiment.
+
+```{literalinclude} ../../../docs_src/how_to_guides/bp_complex_task_repetitions/experiment.py
+---
+caption: config.py
+---
+```
+
+There are some things to be said.
+
+- The names on each dimension need to be unique and ensure that by combining them for
+  the name of the experiment, we get a unique and descriptive id.
+- Dimensions might need more attributes than just a name, like paths, or other arguments
+  for the task. Add them.
+
+Next, we will use these newly defined data structures and see how our tasks change when
+we use them.
+
+```{literalinclude} ../../../docs_src/how_to_guides/bp_complex_task_repetitions/example_improved.py
+---
+caption: task_example.py
+---
+```
+
+As you see, we replaced
+
+## Using the `DataCatalog`
+
+## Adding another dimension
+
+## Adding another level
+
+## Executing a subset
+
+## Grouping and aggregating
+
+## Extending repetitions
+
+Some parametrized tasks are costly to run - costly in terms of computing power, memory,
+or time. Users often extend repetitions triggering all repetitions to be rerun. Thus,
+use the {func}`@pytask.mark.persist <pytask.mark.persist>` decorator, which is explained
+in more detail in this {doc}`tutorial <../tutorials/making_tasks_persist>`.
diff --git a/docs/source/how_to_guides/bp_scaling_tasks.md b/docs/source/how_to_guides/bp_scaling_tasks.md
deleted file mode 100644
index fa7cb5e9..00000000
--- a/docs/source/how_to_guides/bp_scaling_tasks.md
+++ /dev/null
@@ -1,101 +0,0 @@
-# Scaling tasks
-
-In any bigger project you quickly come to the point where you stack multiple repetitions
-of tasks on top of each other.
-
-For example, you have one dataset, four different ways to prepare it, and three
-statistical models to analyze the data. The cartesian product of all steps combined
-comprises twelve differently fitted models.
-
-Here you find some tips on how to set up your tasks such that you can easily modify the
-cartesian product of steps.
-
-## Scalability
-
-Let us dive right into the aforementioned example. We start with one dataset `data.csv`.
-Then, we will create four different specifications of the data and, finally, fit three
-different models to each specification.
-
-This is the structure of the project.
-
-```
-my_project
-├───pyproject.toml
-│
-├───src
-│   └───my_project
-│       ├────config.py
-│       │
-│       ├───data
-│       │   └────data.csv
-│       │
-│       ├───data_preparation
-│       │   ├────__init__.py
-│       │   ├────config.py
-│       │   └────task_prepare_data.py
-│       │
-│       └───estimation
-│           ├────__init__.py
-│           ├────config.py
-│           └────task_estimate_models.py
-│
-├───.pytask
-│   └────...
-│
-└───bld
-```
-
-The folder structure, the main `config.py` which holds `SRC` and `BLD`, and the tasks
-follow the same structure advocated throughout the tutorials.
-
-New are the local configuration files in each subfolder of `my_project`, which contain
-objects shared across tasks. For example, `config.py` holds the paths to the processed
-data and the names of the data sets.
-
-```{literalinclude} ../../../docs_src/how_to_guides/bp_scaling_tasks_1.py
-```
-
-The task file `task_prepare_data.py` uses these objects to build the repetitions.
-
-```{literalinclude} ../../../docs_src/how_to_guides/bp_scaling_tasks_2.py
-```
-
-All arguments for the loop and the {func}`@task <pytask.task>` decorator are built
-within a function to keep the logic in one place and the module's namespace clean.
-
-Ids are used to make the task {ref}`ids <ids>` more descriptive and to simplify their
-selection with {ref}`expressions <expressions>`. Here is an example of the task ids with
-an explicit id.
-
-```
-# With id
-.../my_project/data_preparation/task_prepare_data.py::task_prepare_data[data_0]
-```
-
-Next, we move to the estimation to see how we can build another repetition on top.
-
-```{literalinclude} ../../../docs_src/how_to_guides/bp_scaling_tasks_3.py
-```
-
-In the local configuration, we define `ESTIMATIONS` which combines the information on
-data and model. The dictionary's key can be used as a task id whenever the estimation is
-involved. It allows triggering all tasks related to one estimation - estimation,
-figures, tables - with one command.
-
-```console
-pytask -k linear_probability_data_0
-```
-
-And here is the task file.
-
-```{literalinclude} ../../../docs_src/how_to_guides/bp_scaling_tasks_4.py
-```
-
-Replicating this pattern across a project allows a clean way to define repetitions.
-
-## Extending repetitions
-
-Some parametrized tasks are costly to run - costly in terms of computing power, memory,
-or time. Users often extend repetitions triggering all repetitions to be rerun. Thus,
-use the {func}`@pytask.mark.persist <pytask.mark.persist>` decorator, which is explained
-in more detail in this {doc}`tutorial <../tutorials/making_tasks_persist>`.
diff --git a/docs/source/how_to_guides/bp_structure_of_task_files.md b/docs/source/how_to_guides/bp_structure_of_task_files.md
index 857f6479..84e16789 100644
--- a/docs/source/how_to_guides/bp_structure_of_task_files.md
+++ b/docs/source/how_to_guides/bp_structure_of_task_files.md
@@ -14,7 +14,7 @@ are looking for orientation or inspiration, here are some tips.
   module is for.
 
   ```{seealso}
-  The only exception might be for {doc}`repetitions <bp_scaling_tasks>`.
+  The only exception might be for {doc}`repetitions <bp_complex_task_repetitions>`.
   ```
 
 - The purpose of the task function is to handle IO operations like loading and saving
diff --git a/docs/source/how_to_guides/index.md b/docs/source/how_to_guides/index.md
index 8f0e9f47..53068ee0 100644
--- a/docs/source/how_to_guides/index.md
+++ b/docs/source/how_to_guides/index.md
@@ -42,5 +42,5 @@ maxdepth: 1
 bp_structure_of_a_research_project
 bp_structure_of_task_files
 bp_templates_and_projects
-bp_scaling_tasks
+bp_complex_task_repetitions
 ```
diff --git a/docs/source/tutorials/repeating_tasks_with_different_inputs.md b/docs/source/tutorials/repeating_tasks_with_different_inputs.md
index 750435d6..136152ed 100644
--- a/docs/source/tutorials/repeating_tasks_with_different_inputs.md
+++ b/docs/source/tutorials/repeating_tasks_with_different_inputs.md
@@ -291,7 +291,8 @@ for id_, kwargs in ID_TO_KWARGS.items():
     def task_create_random_data(i, produces): ...
 ```
 
-The {doc}`best-practices guide on parametrizations <../how_to_guides/bp_scaling_tasks>`
+The
+{doc}`best-practices guide on parametrizations <../how_to_guides/bp_complex_task_repetitions>`
 goes into even more detail on how to scale parametrizations.
 
 ## A warning on globals
diff --git a/docs_src/how_to_guides/bp_complex_task_repetitions/example.py b/docs_src/how_to_guides/bp_complex_task_repetitions/example.py
new file mode 100644
index 00000000..3e3bf14e
--- /dev/null
+++ b/docs_src/how_to_guides/bp_complex_task_repetitions/example.py
@@ -0,0 +1,19 @@
+from pathlib import Path
+from typing import Annotated
+
+from pytask import Product
+from pytask import task
+
+SRC = Path(__file__).parent
+BLD = SRC / "bld"
+
+
+for data_name in ("a", "b", "c"):
+    for model_name in ("ols", "logit", "linear_prob"):
+
+        @task(id=f"{model_name}-{data_name}")
+        def task_fit_model(
+            path_to_data: Path = SRC / f"{data_name}.pkl",
+            path_to_model: Annotated[Path, Product] = BLD
+            / f"{data_name}-{model_name}.pkl",
+        ) -> None: ...
diff --git a/docs_src/how_to_guides/bp_complex_task_repetitions/example_improved.py b/docs_src/how_to_guides/bp_complex_task_repetitions/example_improved.py
new file mode 100644
index 00000000..741d2c19
--- /dev/null
+++ b/docs_src/how_to_guides/bp_complex_task_repetitions/example_improved.py
@@ -0,0 +1,14 @@
+from pathlib import Path
+from typing import Annotated
+
+from myproject.config import EXPERIMENTS
+from pytask import Product
+from pytask import task
+
+for experiment in EXPERIMENTS:
+
+    @task(id=experiment.name)
+    def task_fit_model(
+        path_to_data: experiment.dataset.path,
+        path_to_model: Annotated[Path, Product] = experiment.path,
+    ) -> None: ...
diff --git a/docs_src/how_to_guides/bp_complex_task_repetitions/experiment.py b/docs_src/how_to_guides/bp_complex_task_repetitions/experiment.py
new file mode 100644
index 00000000..002c669e
--- /dev/null
+++ b/docs_src/how_to_guides/bp_complex_task_repetitions/experiment.py
@@ -0,0 +1,37 @@
+from pathlib import Path
+from typing import NamedTuple
+
+SRC = Path(__file__).parent
+BLD = SRC / "bld"
+
+
+class Dataset(NamedTuple):
+    name: str
+
+    @property
+    def path(self) -> Path:
+        return SRC / f"{self.name}.pkl"
+
+
+class Model(NamedTuple):
+    name: str
+
+
+DATASETS = [Dataset("a"), Dataset("b"), Dataset("c")]
+MODELS = [Model("ols"), Model("logit"), Model("linear_prob")]
+
+
+class Experiment(NamedTuple):
+    dataset: Dataset
+    model: Model
+
+    @property
+    def name(self) -> str:
+        return f"{self.model.name}-{self.dataset.name}"
+
+    @property
+    def path(self) -> Path:
+        return BLD / f"{self.name}.pkl"
+
+
+EXPERIMENTS = [Experiment(dataset, model) for dataset in DATASETS for model in MODELS]
diff --git a/docs_src/how_to_guides/bp_scaling_tasks_1.py b/docs_src/how_to_guides/bp_scaling_tasks_1.py
deleted file mode 100644
index 52d6ea61..00000000
--- a/docs_src/how_to_guides/bp_scaling_tasks_1.py
+++ /dev/null
@@ -1,20 +0,0 @@
-# Content of config.py
-from pathlib import Path
-
-from my_project.config import BLD
-from my_project.config import SRC
-
-DATA = {
-    "data_0": {"subset": "subset_1"},
-    "data_1": {"subset": "subset_2"},
-    "data_2": {"subset": "subset_3"},
-    "data_3": {"subset": "subset_4"},
-}
-
-
-def path_to_input_data(name: str) -> Path:
-    return SRC / "data" / "data.csv"
-
-
-def path_to_processed_data(name: str) -> Path:
-    return BLD / "data" / f"processed_{name}.pkl"
diff --git a/docs_src/how_to_guides/bp_scaling_tasks_2.py b/docs_src/how_to_guides/bp_scaling_tasks_2.py
deleted file mode 100644
index f31cfc64..00000000
--- a/docs_src/how_to_guides/bp_scaling_tasks_2.py
+++ /dev/null
@@ -1,39 +0,0 @@
-# Content of task_prepare_data.py
-from pathlib import Path
-
-from my_project.data_preparation.config import DATA
-from my_project.data_preparation.config import path_to_input_data
-from my_project.data_preparation.config import path_to_processed_data
-from pandas import pd
-from pytask import Product
-from pytask import task
-from typing_extensions import Annotated
-
-
-def _create_parametrization(data: list[str]) -> dict[str, Path]:
-    id_to_kwargs = {}
-    for data_name, kwargs in data.items():
-        id_to_kwargs[data_name] = {
-            "path_to_input_data": path_to_input_data(data_name),
-            "path_to_processed_data": path_to_processed_data(data_name),
-            **kwargs,
-        }
-
-    return id_to_kwargs
-
-
-_ID_TO_KWARGS = _create_parametrization(DATA)
-
-
-for id_, kwargs in _ID_TO_KWARGS.items():
-
-    @task(id=id_, kwargs=kwargs)
-    def task_prepare_data(
-        path_to_input_data: Path,
-        subset: str,
-        path_to_processed_data: Annotated[Path, Product],
-    ) -> None:
-        df = pd.read_csv(path_to_input_data)
-        # ... transform the data.
-        subset = df.loc[df["subset"].eq(subset)]
-        subset.to_pickle(path_to_processed_data)
diff --git a/docs_src/how_to_guides/bp_scaling_tasks_3.py b/docs_src/how_to_guides/bp_scaling_tasks_3.py
deleted file mode 100644
index 1e2103d4..00000000
--- a/docs_src/how_to_guides/bp_scaling_tasks_3.py
+++ /dev/null
@@ -1,18 +0,0 @@
-# Content of config.py
-from pathlib import Path
-
-from my_project.config import BLD
-from my_project.data_preparation.config import DATA
-
-_MODELS = ["linear_probability", "logistic_model", "decision_tree"]
-
-
-ESTIMATIONS = {
-    f"{data_name}_{model_name}": {"model": model_name, "data": data_name}
-    for model_name in _MODELS
-    for data_name in DATA
-}
-
-
-def path_to_estimation_result(name: str) -> Path:
-    return BLD / "estimation" / f"estimation_{name}.pkl"
diff --git a/docs_src/how_to_guides/bp_scaling_tasks_4.py b/docs_src/how_to_guides/bp_scaling_tasks_4.py
deleted file mode 100644
index a6c66539..00000000
--- a/docs_src/how_to_guides/bp_scaling_tasks_4.py
+++ /dev/null
@@ -1,36 +0,0 @@
-# Content of task_estimate_models.py
-from pathlib import Path
-
-from my_project.data_preparation.config import path_to_processed_data
-from my_project.estimations.config import ESTIMATIONS
-from my_project.estimations.config import path_to_estimation_result
-from pytask import Product
-from pytask import task
-from typing_extensions import Annotated
-
-
-def _create_parametrization(
-    estimations: dict[str, dict[str, str]],
-) -> dict[str, str | Path]:
-    id_to_kwargs = {}
-    for name, config in estimations.items():
-        id_to_kwargs[name] = {
-            "path_to_data": path_to_processed_data(config["data"]),
-            "model": config["model"],
-            "path_to_estimation": path_to_estimation_result(name),
-        }
-
-    return id_to_kwargs
-
-
-_ID_TO_KWARGS = _create_parametrization(ESTIMATIONS)
-
-
-for id_, kwargs in _ID_TO_KWARGS.items():
-
-    @task(id=id_, kwargs=kwargs)
-    def task_estmate_models(
-        path_to_data: Path, model: str, path_to_estimation: Annotated[Path, Product]
-    ) -> None:
-        if model == "linear_probability":
-            ...