diff --git a/README.md b/README.md
index 3f89b69c..387c8859 100644
--- a/README.md
+++ b/README.md
@@ -15,17 +15,17 @@ pip install prompttools
 You can run a simple example of a `prompttools` with the following
 
 ```
-DEBUG=1 python examples/prompttests/example.py
+DEBUG=1 python examples/prompttests/test_openai_chat.py
 ```
 
 To run the example outside of `DEBUG` mode, you'll need to bring your own OpenAI API key. 
 This is because `prompttools` makes a call to OpenAI from your machine. For example:
 
 ```
-OPENAI_API_KEY=sk-... python examples/prompttests/example.py
+OPENAI_API_KEY=sk-... python examples/prompttests/test_openai_chat.py
 ```
 
-You can see the full example [here](/examples/prompttests/example.py).
+You can see the full example [here](/examples/prompttests/test_openai_chat.py).
 
 
 ## Using `prompttools`
@@ -33,7 +33,7 @@ You can see the full example [here](/examples/prompttests/example.py).
 There are primarily two ways you can use `prompttools` in your LLM workflow:
 
 1. Run experiments in [notebooks](/examples/notebooks/).
-1. Write [unit tests](/examples/prompttests/example.py) and integrate them into your CI/CD workflow [via Github Actions](/.github/workflows/post-commit.yaml).
+1. Write [unit tests](/examples/prompttests/test_openai_chat.py) and integrate them into your CI/CD workflow [via Github Actions](/.github/workflows/post-commit.yaml).
 
 ### Notebooks
 
@@ -83,7 +83,7 @@ You can also manually enter feedback to evaluate prompts, see [HumanFeedback.ipy
 
 ### Unit Tests
 
-Unit tests in `prompttools` are called `prompttests`. They use the `@prompttest` annotation to transform an evaluation function into an efficient unit test. The `prompttest` framework executes and evaluates experiments so you can test prompts over time. You can see an example test [here](/examples/prompttests/example.py) and an example of that test being used as a Github Action [here](/.github/workflows/post-commit.yaml).
+Unit tests in `prompttools` are called `prompttests`. They use the `@prompttest` annotation to transform an evaluation function into an efficient unit test. The `prompttest` framework executes and evaluates experiments so you can test prompts over time. You can see an example test [here](/examples/prompttests/test_openai_chat.py) and an example of that test being used as a Github Action [here](/.github/workflows/post-commit.yaml).
 
 ### Persisting Results
 
diff --git a/docs/source/index.rst b/docs/source/index.rst
index 7e1f6f5b..4d207695 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -3,18 +3,51 @@
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
-Welcome to prompttools's documentation!
+Welcome to PromptTools!
 =======================================
 
 .. toctree::
    :maxdepth: 2
    :caption: Contents:
 
+Welcome to `prompttools` created by [Hegel AI](https://hegel-ai.com/)! 
+This repo offers a set of free, open-source tools for testing and experimenting with prompts. 
+The core idea is to enable developers to evaluate prompts using familiar interfaces 
+like _code_ and _notebooks_.
 
 
-Indices and tables
+To stay in touch with us about issues and future updates, 
+join the [Discord](https://discord.gg/7KeRPNHGdJ).
+
+
+Quickstart
+==================
+
+To install `prompttools`, you can use `pip`:
+
+```
+pip install prompttools
+```
+
+You can run a simple example of a `prompttools` with the following
+
+```
+DEBUG=1 python examples/prompttests/example.py
+```
+
+To run the example outside of `DEBUG` mode, you'll need to bring your own OpenAI API key. 
+This is because `prompttools` makes a call to OpenAI from your machine. For example:
+
+```
+OPENAI_API_KEY=sk-... python examples/prompttests/example.py
+```
+
+You can see the full example [here](https://github.com/hegelai/prompttools/tree/main/examples/prompttests/test_openai_chat.py).
+
+Using `prompttools`
 ==================
 
-* :ref:`genindex`
-* :ref:`modindex`
-* :ref:`search`
+There are primarily two ways you can use `prompttools` in your LLM workflow:
+
+1. Run experiments in [notebooks](https://github.com/hegelai/prompttools/tree/main/examples/notebooks/).
+1. Write [unit tests](https://github.com/hegelai/prompttools/tree/main/examples/prompttests/test_openai_chat.py) and integrate them into your CI/CD workflow [via Github Actions](/.github/workflows/post-commit.yaml).