diff --git a/docs/docs/index.md b/docs/docs/index.md
index 98fe5c2..2144535 100644
--- a/docs/docs/index.md
+++ b/docs/docs/index.md
@@ -102,6 +102,7 @@ cookiecutter https://github.com/drivendata/cookiecutter-data-science
 ├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
 │                         generated with `pip freeze > requirements.txt`
 │
+├── setup.py           <- Make this project pip installable with `pip install -e`
 ├── src                <- Source code for use in this project.
 │   ├── __init__.py    <- Makes src a Python module
 │   │
@@ -140,25 +141,18 @@ Since notebooks are challenging objects for source control (e.g., diffs of the `
 
  1. Follow a naming convention that shows the owner and the order the analysis was done in. We use the format `<step>-<ghuser>-<description>.ipynb` (e.g., `0.3-bull-visualize-distributions.ipynb`).
 
- 2. Refactor the good parts. Don't write code to do the same task in multiple notebooks. If it's a data preprocessing task, put it in the pipeline at `src/data/make_dataset.py` and load data from `data/interim`. If it's useful utility code, refactor it to `src` and import it into notebooks with a cell like the following. If updating the system path is icky to you, we'd recommend making a Python package (there is a [cookiecutter for that](https://github.com/audreyr/cookiecutter-pypackage) as well) and installing that as an editable package with `pip install -e`.
+ 2. Refactor the good parts. Don't write code to do the same task in multiple notebooks. If it's a data preprocessing task, put it in the pipeline at `src/data/make_dataset.py` and load data from `data/interim`. If it's useful utility code, refactor it to `src`.
+
+ Now by default we turn the project into a Python package (see the `setup.py` file). You can import your code and use it in notebooks with a cell like the following:
 
 ```
-# Load the "autoreload" extension
+# OPTIONAL: Load the "autoreload" extension so that code can change
 %load_ext autoreload
 
-# always reload modules marked with "%aimport"
-%autoreload 1
-
-import os
-import sys
-
-# add the 'src' directory as one where we can import modules
-src_dir = os.path.join(os.getcwd(), os.pardir, 'src')
-sys.path.append(src_dir)
+# OPTIONAL: always reload modules so that as you change code in src, it gets loaded
+%autoreload 2
 
-# import my method from the source code
-%aimport preprocess.build_features
-from preprocess.build_features import remove_invalid_data
+from src.data import make_dataset
 ```
 
 ### Analysis is a DAG
diff --git a/{{ cookiecutter.repo_name }}/README.md b/{{ cookiecutter.repo_name }}/README.md
index bf024ec..010dd62 100644
--- a/{{ cookiecutter.repo_name }}/README.md	
+++ b/{{ cookiecutter.repo_name }}/README.md	
@@ -31,6 +31,7 @@ Project Organization
     ├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
     │                         generated with `pip freeze > requirements.txt`
     │
+    ├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported
     ├── src                <- Source code for use in this project.
     │   ├── __init__.py    <- Makes src a Python module
     │   │