diff --git a/docs/getting_started/watcher-execution-mode.rst b/docs/getting_started/watcher-execution-mode.rst
index 04f7e3082b..803c5d18ed 100644
--- a/docs/getting_started/watcher-execution-mode.rst
+++ b/docs/getting_started/watcher-execution-mode.rst
@@ -87,6 +87,45 @@ Depending on the dbt workflow topology, if your dbt DAG previously took 5 minute
 
 We plan to repeat these benchmarks and share the code with the community in the future.
 
+
+.. note::
+   ``ExecutionMode.WATCHER`` relies on the ``threads`` value defined in your dbt profile. Start with a conservative value that matches the CPU capacity of your Airflow workers, then gradually increase it to find the sweet spot between faster runs and acceptable memory/CPU usage.
+
+When we ran the `astronomer/cosmos-benchmark <https://github.com/astronomer/cosmos-benchmark>`_ project with ``ExecutionMode.WATCHER``, that same ``threads`` setting directly affected runtime: moving from 1 to 8 threads reduced the end-to-end ``dbt build`` duration from roughly 26 seconds to about 4 seconds (see table above), while 16 threads squeezed it to around 2 seconds at the cost of higher CPU usage. Use those numbers as a reference point when evaluating how thread counts scale in your own environment.
+
+To increase the number of threads, edit your dbt ``profiles.yml`` (or Helm values if you manage the profile there) and update the ``threads`` key for the target you use with Cosmos:
+
+.. code-block:: yaml
+
+   your_dbt_project:
+     target: prod
+     outputs:
+       prod:
+         type: postgres
+         host: your-host
+         user: your-user
+         password: your-password
+         schema: analytics
+         threads: 8  # increase or decrease to match available resources
+
+
+If you prefer to manage threads through Cosmos profile mappings instead of editing ``profiles.yml`` directly, pass ``profile_args={"threads": <int>}`` to your ``ProfileConfig``. For example, using the built-in ``PostgresUserPasswordProfileMapping``:
+
+.. code-block:: python
+
+   from cosmos.config import ProfileConfig
+   from cosmos.profiles import PostgresUserPasswordProfileMapping
+
+   profile_config = ProfileConfig(
+       profile_name="jaffle_shop",
+       target_name="prod",
+       profile_mapping=PostgresUserPasswordProfileMapping(
+           conn_id="postgres_connection",
+           profile_args={"threads": 8},
+       ),
+   )
+
+
 -------------------------------------------------------------------------------
 
 Example Usage of ``ExecutionMode.WATCHER``