diff --git a/docs/user_guide/flyte_fundamentals/index.md b/docs/user_guide/flyte_fundamentals/index.md
index a1a08fd187..9ef8a5bd2b 100644
--- a/docs/user_guide/flyte_fundamentals/index.md
+++ b/docs/user_guide/flyte_fundamentals/index.md
@@ -22,6 +22,8 @@ use cases.
   - Develop and deploy workflows to a local Flyte demo cluster.
 * - {doc}`⏱ Running and scheduling workflows <running_and_scheduling_workflows>`
   - Execute workflows programmatically and schedule them as cron jobs.
+* - {doc}`📙 Jupyter notebook interaction <jupyter_notebook_interaction>`
+  - Develop and debug Flyte workflows interactively in Jupyter notebooks.
 * - {doc}`📊 Visualizing task input and output <visualizing_task_input_and_output>`
   - Create rich, customizable static reports for increased visibility into tasks.
 * - {doc}`🏎 Optimizing tasks <optimizing_tasks>`
@@ -45,6 +47,7 @@ cluster, see the {ref}`Deployment Guide <deployment>`.
 tasks_workflows_and_launch_plans
 registering_workflows
 running_and_scheduling_workflows
+jupyter_notebook_interaction
 visualizing_task_input_and_output
 optimizing_tasks
 extending_flyte
diff --git a/docs/user_guide/flyte_fundamentals/jupyter_notebook_interaction.md b/docs/user_guide/flyte_fundamentals/jupyter_notebook_interaction.md
new file mode 100644
index 0000000000..7d11828304
--- /dev/null
+++ b/docs/user_guide/flyte_fundamentals/jupyter_notebook_interaction.md
@@ -0,0 +1,91 @@
+---
+kernelspec:
+  display_name: Python 3
+  language: python
+  name: python3
+---
+
+(getting_started_jupyter_notebook_interaction)=
+
+# Running and developing workflows in Jupyter notebooks
+
+Flyte supports the development, running, and debugging of tasks and workflows in an interactive
+Jupyter notebook environment, which accelerates the iteration speed when building data-
+or machine learning-driven applications.
+
+```{admonition} Attention
+:class: attention
+
+This feature requires the `flytekit` version `1.14.0` or higher.
+```
+
+```{admonition} Prerequisites
+:class: important
+
+This guide assumes that you've completed the previous guides for
+{ref}`Running and Scheduling Workflows <getting_started_run_and_schedule>`.
+The code snippets in this guide are intended to be run in a Jupyter notebook.
+```
+
+The code of this guide can be found in the [flytesnacks](https://github.com/flyteorg/flytesnacks/blob/master/examples/basics/basics/basic_interactive_mode.ipynb)
+
+## Create an interactive `FlyteRemote` object
+
+In {ref}`Running and Scheduling Workflows <getting_started_run_and_schedule>`, you learned
+how to run registered Flyte workflows from a Python runtime using the
+{py:class}`~flytekit.remote.remote.FlyteRemote` client.
+
+When developing workflows in a Jupyter notebook, `FlyteRemote` provides an
+interactive interface to register and run workflows on a Flyte cluster. Let's
+create an interactive `FlyteRemote` object:
+
+```{code-cell} ipython3
+:tags: [remove-output]
+
+from flytekit.configuration import Config
+from flytekit.remote import FlyteRemote
+
+remote = FlyteRemote(
+    config=Config.auto(),
+    default_project="flytesnacks",
+    default_domain="development",
+    interactive_mode_enabled=True,
+)
+```
+
+```{admonition} Note
+:class: Note
+
+The `interactive_mode_enabled` flag is automatically set to `True` when running
+in a Jupyter notebook environment, enabling interactive registration and execution
+of workflows.
+```
+
+## Running a task or a workflow
+
+You can run entities (tasks or workflows) using the `FlyteRemote`
+{py:meth}`~flytekit.remote.remote.FlyteRemote.execute` method.
+During execution, `flytekit` first checks if the entity is registered with the
+Flyte backend, and if not, registers it before execution.
+
+```{code-block} python
+execution = remote.execute(my_task, inputs={"name": "Flyte"})
+execution = remote.execute(my_wf, inputs={"name": "Flyte"})
+```
+
+You can then fetch the inputs and outputs of the execution by following the steps
+in {ref}`getting_started_run_and_schedule_fetch_execution`.
+
+## When Does Interactive `FlyteRemote` Re-register an Entity?
+
+The interactive `FlyteRemote` client re-registers an entity whenever it's
+redefined in the notebook, including when you re-execute a cell containing the
+entity definition, even if the entity remains unchanged. This behavior facilitates
+iterative development and debugging of tasks and workflows in a Jupyter notebook.
+
+## What's next?
+
+In this guide, you learned how to develop and run tasks and workflows in a
+Jupyter Notebook environment using interactive `FlyteRemote`.
+
+In the next guide, you'll learn how to visualize tasks using Flyte Decks.
diff --git a/docs/user_guide/flyte_fundamentals/running_and_scheduling_workflows.md b/docs/user_guide/flyte_fundamentals/running_and_scheduling_workflows.md
index 60bbe98596..4a552a1275 100644
--- a/docs/user_guide/flyte_fundamentals/running_and_scheduling_workflows.md
+++ b/docs/user_guide/flyte_fundamentals/running_and_scheduling_workflows.md
@@ -184,6 +184,8 @@ execution = remote.execute(flyte_task, inputs={"name": "Kermit"})
 You can also launch tasks via `flytectl`, learn more in the {ref}`User Guide <remote_task>`
 ```
 
+(getting_started_run_and_schedule_fetch_execution)=
+
 ## Fetching inputs and outputs of an execution
 
 By default, {py:meth}`FlyteRemote.execute <flytekit.remote.remote.FlyteRemote.execute>`
@@ -342,4 +344,5 @@ In this guide, you learned about how to:
 - Run tasks, workflows, and launch plans using `FlyteRemote`.
 - Create a cron schedule to run a launch plan at a specified time interval.
 
-In the next guide, you'll learn how to visualize tasks using Flyte Decks.
+In the next guide, you'll learn how to develop and run tasks and workflows in
+a Jupyter Notebook environment.