diff --git a/README.md b/README.md
index ae5aa81..38a3049 100644
--- a/README.md
+++ b/README.md
@@ -72,7 +72,7 @@ jax.grad(vector_sum)(x, y) # 🎉
 
    vector_sum_grad = jax.grad(vector_sum)
    vector_sum_grad(x, y)
-    ```
+   ```
 
 > [!TIP]
 > Now you're ready to jump into our [examples](https://github.com/pasteurlabs/tesseract-jax/tree/main/examples) for more ways to use Tesseract-JAX.
diff --git a/examples/simple/vectoradd_jax/tesseract_api.py b/examples/simple/vectoradd_jax/tesseract_api.py
index 5451902..0552264 100644
--- a/examples/simple/vectoradd_jax/tesseract_api.py
+++ b/examples/simple/vectoradd_jax/tesseract_api.py
@@ -65,16 +65,20 @@ def apply_jit(inputs: dict) -> dict:
     b_scaled = inputs["b"]["s"] * inputs["b"]["v"]
     add_result = a_scaled + b_scaled
     min_result = a_scaled - b_scaled
+
+    def safe_norm(x, ord):
+        # Compute the norm of a vector, adding a small epsilon to ensure
+        # differentiability and avoid division by zero
+        return jnp.power(jnp.power(jnp.abs(x), ord).sum() + 1e-8, 1 / ord)
+
     return {
         "vector_add": {
             "result": add_result,
-            "normed_result": add_result
-            / jnp.linalg.norm(add_result, ord=inputs["norm_ord"]),
+            "normed_result": add_result / safe_norm(add_result, ord=inputs["norm_ord"]),
         },
         "vector_min": {
             "result": min_result,
-            "normed_result": min_result
-            / jnp.linalg.norm(min_result, ord=inputs["norm_ord"]),
+            "normed_result": min_result / safe_norm(min_result, ord=inputs["norm_ord"]),
         },
     }