diff --git a/README.md b/README.md
index 62110a7..356cb5c 100644
--- a/README.md
+++ b/README.md
@@ -18,9 +18,10 @@ pip install py-tes
 
 ### Example
 
-```
+```python
 import tes
 
+# define task
 task = tes.Task(
     executors=[
         tes.Executor(
@@ -30,8 +31,123 @@ task = tes.Task(
     ]
 )
 
-cli = tes.HTTPClient("http://funnel.example.com", timeout=5)
+# create client
+cli = tes.HTTPClient("https://funnel.example.com", timeout=5)
+
+# access endpoints
+service_info = cli.get_service_info()
 task_id = cli.create_task(task)
-res = cli.get_task(task_id)
+task_info = cli.get_task(task_id, view="BASIC")
 cli.cancel_task(task_id)
+tasks_list = cli.list_tasks(view="MINIMAL")  # default view
+```
+
+### How to...
+
+> Makes use of the objects above...
+
+#### ...export a model to a dictionary
+
+```python
+task_dict = task.as_dict(drop_empty=False)
+```
+
+`task_dict` contents:
+
+```console
+{'id': None, 'state': None, 'name': None, 'description': None, 'inputs': None, 'outputs': None, 'resources': None, 'executors': [{'image': 'alpine', 'command': ['echo', 'hello'], 'workdir': None, 'stdin': None, 'stdout': None, 'stderr': None, 'env': None}], 'volumes': None, 'tags': None, 'logs': None, 'creation_time': None}
+```
+
+#### ...export a model to JSON
+
+```python
+task_json = task.as_json()  # also accepts `drop_empty` arg
+```
+
+`task_json` contents:
+
+```console
+{"executors": [{"image": "alpine", "command": ["echo", "hello"]}]}
+```
+
+#### ...pretty print a model
+
+```python
+print(task.as_json(indent=3))  # keyword args are passed to `json.dumps()`
+```
+
+Output:
+
+```json
+{
+   "executors": [
+      {
+         "image": "alpine",
+         "command": [
+            "echo",
+            "hello"
+         ]
+      }
+   ]
+}
+```
+
+#### ...access a specific task from the task list
+
+```python
+specific_task = tasks_list.tasks[5]
+```
+
+`specific_task` contents:
+
+```console
+Task(id='393K43', state='COMPLETE', name=None, description=None, inputs=None, outputs=None, resources=None, executors=None, volumes=None, tags=None, logs=None, creation_time=None)
+```
+
+#### ...iterate over task list items
+
+```python
+for t in tasks_list[:3]:
+    print(t.as_json(indent=3))
+```
+
+Output:
+
+```console
+{
+   "id": "task_A2GFS4",
+   "state": "RUNNING"
+}
+{
+   "id": "task_O8G1PZ",
+   "state": "CANCELED"
+}
+{
+   "id": "task_W246I6",
+   "state": "COMPLETE"
+}
+```
+
+#### ...instantiate a model from a JSON representation
+
+```python
+task_from_json = tes.client.unmarshal(task_json, tes.Task)
+```
+
+`task_from_json` contents:
+
+```console
+Task(id=None, state=None, name=None, description=None, inputs=None, outputs=None, resources=None, executors=[Executor(image='alpine', command=['echo', 'hello'], workdir=None, stdin=None, stdout=None, stderr=None, env=None)], volumes=None, tags=None, logs=None, creation_time=None)
+```
+
+Which is equivalent to `task`:
+
+```python
+print(task_from_json == task)
+```
+
+Output:
+
+```console
+True
 ```