diff --git a/src/py/flwr/cli/new/templates/app/code/client.tensorflow.py.tpl b/src/py/flwr/cli/new/templates/app/code/client.tensorflow.py.tpl
index cc00f8ff0b8c..4a9448848313 100644
--- a/src/py/flwr/cli/new/templates/app/code/client.tensorflow.py.tpl
+++ b/src/py/flwr/cli/new/templates/app/code/client.tensorflow.py.tpl
@@ -1 +1,57 @@
 """$project_name: A Flower / TensorFlow app."""
+
+import os
+
+import tensorflow as tf
+from flwr.client import ClientApp, NumPyClient
+from flwr_datasets import FederatedDataset
+
+
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
+
+# Define Flower client
+class FlowerClient(NumPyClient):
+    def __init__(self, model, train_data, test_data):
+        self.model = model
+        self.x_train, self.y_train = train_data
+        self.x_test, self.y_test = test_data
+        
+    def get_parameters(self, config):
+        return self.model.get_weights()
+
+    def fit(self, parameters, config):
+        self.model.set_weights(parameters)
+        self.model.fit(self.x_train, self.y_train, epochs=1, batch_size=32, verbose=0)
+        return self.model.get_weights(), len(self.x_train), {}
+
+    def evaluate(self, parameters, config):
+        self.model.set_weights(parameters)
+        loss, accuracy = self.model.evaluate(self.x_test, self.y_test, verbose=0)
+        return loss, len(self.x_test), {"accuracy": accuracy}
+
+
+fds = FederatedDataset(dataset="cifar10", partitioners={"train": 2})
+
+def client_fn(cid: str):
+    """Create and return an instance of Flower `Client`."""
+
+    # Load model and data (MobileNetV2, CIFAR-10)
+    model = tf.keras.applications.MobileNetV2((32, 32, 3), classes=10, weights=None)
+    model.compile("adam", "sparse_categorical_crossentropy", metrics=["accuracy"])
+
+    # Download and partition dataset
+    partition = fds.load_partition(int(cid), "train")
+    partition.set_format("numpy")
+
+    # Divide data on each node: 80% train, 20% test
+    partition = partition.train_test_split(test_size=0.2, seed=42)
+    train_data = partition["train"]["img"] / 255.0, partition["train"]["label"]
+    test_data = partition["test"]["img"] / 255.0, partition["test"]["label"]
+
+    return FlowerClient(model, train_data, test_data).to_client()
+
+
+# Flower ClientApp
+app = ClientApp(
+    client_fn=client_fn,
+)
diff --git a/src/py/flwr/cli/new/templates/app/code/server.tensorflow.py.tpl b/src/py/flwr/cli/new/templates/app/code/server.tensorflow.py.tpl
index cc00f8ff0b8c..98cea74f0c92 100644
--- a/src/py/flwr/cli/new/templates/app/code/server.tensorflow.py.tpl
+++ b/src/py/flwr/cli/new/templates/app/code/server.tensorflow.py.tpl
@@ -1 +1,19 @@
 """$project_name: A Flower / TensorFlow app."""
+
+from flwr.server import ServerApp, ServerConfig
+from flwr.server.strategy import FedAvg
+
+# Define config
+config = ServerConfig(num_rounds=3)
+
+strategy = FedAvg(
+    fraction_fit=1.0,
+    fraction_evaluate=1.0,
+    min_available_clients=2,
+)
+
+# Flower ServerApp
+app = ServerApp(
+    config=config,
+    strategy=strategy,
+)