diff --git a/README.md b/README.md
index 519bf7880..b2bb9767a 100644
--- a/README.md
+++ b/README.md
@@ -65,16 +65,16 @@ ART is an open-source RL framework that improves agent reliability by allowing L
 
 ## 📒 Notebooks
 
-| Agent Task          | Example Notebook                                                                                                                       | Description                                         | Comparative Performance                                                                                                                                                                             |
-| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| **ART•E LangGraph** | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/langgraph/art-e-langgraph.ipynb)   | Qwen 2.5 7B learns to search emails using LangGraph | [Link coming soon]                                                                                                                                                                                  |
-| **MCP•RL**          | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/mcp-rl/mcp-rl.ipynb)               | Qwen 2.5 3B masters the NWS MCP server              | [Link coming soon]                                                                                                                                                                                  |
-| **ART•E [RULER]**   | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/art-e.ipynb)                       | Qwen 2.5 7B learns to search emails using RULER     | <img src="https://github.com/openpipe/art/raw/main/assets/benchmarks/email_agent/accuracy-training-progress.svg" height="72"> [benchmarks](/examples/art-e/art_e/evaluate/display_benchmarks.ipynb) |
-| **2048**            | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/2048/2048.ipynb)                   | Qwen 2.5 3B learns to play 2048                     | <img src="https://github.com/openpipe/art/raw/main/assets/benchmarks/2048/accuracy-training-progress.svg" height="72"> [benchmarks](/examples/2048/benchmark_2048.ipynb)                            |
-| **Temporal Clue**   | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/temporal_clue/temporal-clue.ipynb) | Qwen 2.5 7B learns to solve Temporal Clue           | [Link coming soon]                                                                                                                                                                                  |
-| **Tic Tac Toe**     | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/tic_tac_toe/tic-tac-toe.ipynb)     | Qwen 2.5 3B learns to play Tic Tac Toe              | <img src="https://github.com/openpipe/art/raw/main/assets/benchmarks/tic-tac-toe-local/accuracy-training-progress.svg" height="72"> [benchmarks](/examples/tic_tac_toe/benchmark_tic_tac_toe.ipynb) |
-| **Codenames**       | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/codenames/Codenames_RL.ipynb)      | Qwen 2.5 3B learns to play Codenames                | <img src="https://github.com/openpipe/art/raw/main/assets/benchmarks/codenames/win_rate_over_time.png" height="72"> [benchmarks](/examples/codenames/Codenames_RL.ipynb)                            |
-| **AutoRL [RULER]**  | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/auto_rl.ipynb)                     | Train Qwen 2.5 7B to master any task                | [Link coming soon]                                                                                                                                                                                  |
+| Agent Task          | Example Notebook                                                                                                                       | Description                                         | Comparative Performance                                                                                                                                                                                                     |
+| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| **ART•E LangGraph** | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/langgraph/art-e-langgraph.ipynb)   | Qwen 2.5 7B learns to search emails using LangGraph | [Link coming soon]                                                                                                                                                                                                          |
+| **MCP•RL**          | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/mcp-rl/mcp-rl.ipynb)               | Qwen 2.5 3B masters the NWS MCP server              | [Link coming soon]                                                                                                                                                                                                          |
+| **ART•E [RULER]**   | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/art-e.ipynb)                       | Qwen 2.5 7B learns to search emails using RULER     | <img src="https://github.com/openpipe/art/raw/main/assets/benchmarks/email_agent/accuracy-training-progress.svg" height="72"> [benchmarks](/dev/art-e/art_e/evaluate/display_benchmarks.ipynb)                              |
+| **2048**            | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/2048/2048.ipynb)                   | Qwen 2.5 3B learns to play 2048                     | <img src="https://github.com/openpipe/art/raw/main/assets/benchmarks/2048/accuracy-training-progress.svg" height="72"> [benchmarks](/examples/2048/display_benchmarks.ipynb)                                                |
+| **Temporal Clue**   | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/temporal_clue/temporal-clue.ipynb) | Qwen 2.5 7B learns to solve Temporal Clue           | [Link coming soon]                                                                                                                                                                                                          |
+| **Tic Tac Toe**     | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/tic_tac_toe/tic-tac-toe.ipynb)     | Qwen 2.5 3B learns to play Tic Tac Toe              | <img src="https://github.com/openpipe/art/raw/main/assets/benchmarks/tic-tac-toe-local/accuracy-training-progress.svg" height="72"> [benchmarks](/examples/tic_tac_toe/display-benchmarks.ipynb)                            |
+| **Codenames**       | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/codenames/Codenames_RL.ipynb)      | Qwen 2.5 3B learns to play Codenames                | <img src="https://github.com/openpipe/art/raw/main/assets/benchmarks/codenames/win_rate_over_time.png" height="72"> [benchmarks](https://github.com/OpenPipe/art-notebooks/blob/main/examples/codenames/Codenames_RL.ipynb) |
+| **AutoRL [RULER]**  | [🏋️ Train agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/auto_rl.ipynb)                     | Train Qwen 2.5 7B to master any task                | [Link coming soon]                                                                                                                                                                                                          |
 
 ## 📰 ART News
 
diff --git a/docs/fundamentals/art-backend.mdx b/docs/fundamentals/art-backend.mdx
index 100c0df4d..178b6d399 100644
--- a/docs/fundamentals/art-backend.mdx
+++ b/docs/fundamentals/art-backend.mdx
@@ -141,7 +141,7 @@ To see `LocalBackend` and `SkyPilotBackend` in action, try the examples below.
     <Card
       title="2048 Notebook"
       icon="laptop-code"
-      href="https://colab.research.google.com/github/openpipe/art/blob/main/examples/2048/2048.ipynb"
+      href="https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/2048/2048.ipynb"
       horizontal={true}
       arrow={true}
     >
diff --git a/docs/getting-started/about.mdx b/docs/getting-started/about.mdx
index b076cc603..31e648ba5 100644
--- a/docs/getting-started/about.mdx
+++ b/docs/getting-started/about.mdx
@@ -109,7 +109,7 @@ The ART client can be installed into projects designed to run on any machine tha
 <Card
   title="Train an agent to play 2048"
   icon="robot"
-  href="https://colab.research.google.com/github/openpipe/art/blob/main/examples/2048/2048.ipynb"
+  href="https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/2048/2048.ipynb"
   horizontal={true}
   arrow={true}
 ></Card>
diff --git a/docs/getting-started/notebooks.mdx b/docs/getting-started/notebooks.mdx
index 39b261d02..7e88e89e9 100644
--- a/docs/getting-started/notebooks.mdx
+++ b/docs/getting-started/notebooks.mdx
@@ -7,12 +7,15 @@ icon: "book"
 
 <div className="full-width">
 
-| Agent Task        | Notebook                                                                                                                               | Description                                     | Performance                                                                                                                                                                                                                                                         |
-| ----------------- | -------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| **ART•E [RULER]** | [🏋️&nbsp;Train&nbsp;agent](https://colab.research.google.com/github/openpipe/art/blob/main/examples/art-e.ipynb)                 | Qwen 2.5 7B learns to search emails using RULER | <a href="https://github.com/OpenPipe/ART/blob/main/examples/art-e/art_e/evaluate/display_benchmarks.ipynb"><img src="https://github.com/OpenPipe/ART/raw/main/assets/benchmarks/email_agent/accuracy-training-progress.svg" width="72" style={{margin: "0"}} /></a> |
-| **2048**          | [🏋️&nbsp;Train&nbsp;agent](https://colab.research.google.com/github/openpipe/art/blob/main/examples/2048/2048.ipynb)                   | Qwen 2.5 3B learns to play 2048                 | <a href="https://github.com/OpenPipe/ART/blob/main/examples/2048/benchmark_2048.ipynb"><img src="https://github.com/OpenPipe/ART/raw/main/assets/benchmarks/2048/accuracy-training-progress.svg" width="72" style={{margin: "0"}} /></a>                            |
-| **Temporal Clue** | [🏋️&nbsp;Train&nbsp;agent](https://colab.research.google.com/github/openpipe/art/blob/main/examples/temporal_clue/temporal-clue.ipynb) | Qwen 2.5 7B learns to solve Temporal Clue       | [Link coming soon]                                                                                                                                                                                                                                                  |
-| **Tic Tac Toe**   | [🏋️&nbsp;Train&nbsp;agent](https://colab.research.google.com/github/openpipe/art/blob/main/examples/tic_tac_toe/tic-tac-toe.ipynb)     | Qwen 2.5 3B learns to play Tic Tac Toe          | <a href="https://github.com/OpenPipe/ART/blob/main/examples/tic_tac_toe/benchmark_tic_tac_toe.ipynb"><img src="https://github.com/OpenPipe/ART/raw/main/assets/benchmarks/tic-tac-toe-local/accuracy-training-progress.svg" width="72" style={{margin: "0"}} /></a> |
-| **Codenames**     | [🏋️&nbsp;Train&nbsp;agent](https://colab.research.google.com/github/openpipe/art/blob/main/examples/codenames/Codenames_RL.ipynb)      | Qwen 2.5 3B learns to play Codenames            | <a href="https://github.com/OpenPipe/ART/blob/main/examples/codenames/Codenames_RL.ipynb"><img src="https://github.com/OpenPipe/ART/raw/main/assets/benchmarks/codenames/win_rate_over_time.png" width="72" style={{margin: "0"}} /></a>                            |
+| Agent Task          | Notebook                                                                                                                                         | Description                                         | Performance                                                                                                                                                                                                                                                      |
+| ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| **ART•E LangGraph** | [🏋️&nbsp;Train&nbsp;agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/langgraph/art-e-langgraph.ipynb)   | Qwen 2.5 7B learns to search emails using LangGraph | [Link coming soon]                                                                                                                                                                                                                                               |
+| **MCP•RL**          | [🏋️&nbsp;Train&nbsp;agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/mcp-rl/mcp-rl.ipynb)               | Qwen 2.5 3B masters the NWS MCP server              | [Link coming soon]                                                                                                                                                                                                                                               |
+| **ART•E [RULER]**   | [🏋️&nbsp;Train&nbsp;agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/art-e.ipynb)                       | Qwen 2.5 7B learns to search emails using RULER     | <a href="https://github.com/OpenPipe/ART/blob/main/dev/art-e/art_e/evaluate/display_benchmarks.ipynb"><img src="https://github.com/OpenPipe/ART/raw/main/assets/benchmarks/email_agent/accuracy-training-progress.svg" width="72" style={{margin: "0"}} /></a>   |
+| **2048**            | [🏋️&nbsp;Train&nbsp;agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/2048/2048.ipynb)                   | Qwen 2.5 3B learns to play 2048                     | <a href="https://github.com/OpenPipe/ART/blob/main/examples/2048/display_benchmarks.ipynb"><img src="https://github.com/OpenPipe/ART/raw/main/assets/benchmarks/2048/accuracy-training-progress.svg" width="72" style={{margin: "0"}} /></a>                     |
+| **Temporal Clue**   | [🏋️&nbsp;Train&nbsp;agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/temporal_clue/temporal-clue.ipynb) | Qwen 2.5 7B learns to solve Temporal Clue           | [Link coming soon]                                                                                                                                                                                                                                               |
+| **Tic Tac Toe**     | [🏋️&nbsp;Train&nbsp;agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/tic_tac_toe/tic-tac-toe.ipynb)     | Qwen 2.5 3B learns to play Tic Tac Toe              | <a href="https://github.com/OpenPipe/ART/blob/main/examples/tic_tac_toe/display-benchmarks.ipynb"><img src="https://github.com/OpenPipe/ART/raw/main/assets/benchmarks/tic-tac-toe-local/accuracy-training-progress.svg" width="72" style={{margin: "0"}} /></a> |
+| **Codenames**       | [🏋️&nbsp;Train&nbsp;agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/codenames/Codenames_RL.ipynb)      | Qwen 2.5 3B learns to play Codenames                | <a href="https://github.com/OpenPipe/art-notebooks/blob/main/examples/codenames/Codenames_RL.ipynb"><img src="https://github.com/OpenPipe/ART/raw/main/assets/benchmarks/codenames/win_rate_over_time.png" width="72" style={{margin: "0"}} /></a>               |
+| **AutoRL [RULER]**  | [🏋️&nbsp;Train&nbsp;agent](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/auto_rl.ipynb)                     | Train Qwen 2.5 7B to master any task                | [Link coming soon]                                                                                                                                                                                                                                               |
 
 </div>
diff --git a/docs/getting-started/quick-start.mdx b/docs/getting-started/quick-start.mdx
index 21f51c1ef..f2ab23ee7 100644
--- a/docs/getting-started/quick-start.mdx
+++ b/docs/getting-started/quick-start.mdx
@@ -24,13 +24,13 @@ If you'd like to enable observability while working through this guide, create a
 
 - [Weights & Biases](https://wandb.ai/home)
 
-Once you have your Weights & Biases API key, open the [notebook](https://colab.research.google.com/github/openpipe/art/blob/main/examples/2048/2048.ipynb) in Google Colab and set them in the **Environment Variables** cell.
+Once you have your Weights & Biases API key, open the [notebook](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/2048/2048.ipynb) in Google Colab and set them in the **Environment Variables** cell.
 
 Once your API keys are set, or if you won't need observability while completing this walkthrough, continue on to the next step.
 
 ## Step 2: Prepare your notebook
 
-If you haven't already, open the [notebook](https://colab.research.google.com/github/openpipe/art/blob/main/examples/2048/2048.ipynb) in Google Colab and connect to a T4 runtime environment.
+If you haven't already, open the [notebook](https://colab.research.google.com/github/openpipe/art-notebooks/blob/main/examples/2048/2048.ipynb) in Google Colab and connect to a T4 runtime environment.
 
 <Accordion title="Connecting to a T4 GPU">
   In the top bar of your Google Colab notebook, find *Runtime* > *Change runtime