diff --git a/website/docs/topics/prompting-and-reasoning/_category_.json b/website/docs/topics/prompting-and-reasoning/_category_.json
new file mode 100644
index 00000000000..84e08b9ddf9
--- /dev/null
+++ b/website/docs/topics/prompting-and-reasoning/_category_.json
@@ -0,0 +1,4 @@
+{
+    "label": "Prompting and Reasoning",
+    "collapsible": true
+}
diff --git a/website/docs/topics/prompting-and-reasoning/react.ipynb b/website/docs/topics/prompting-and-reasoning/react.ipynb
index 03aa7a86b08..e0ebaf5d113 100644
--- a/website/docs/topics/prompting-and-reasoning/react.ipynb
+++ b/website/docs/topics/prompting-and-reasoning/react.ipynb
@@ -6,16 +6,9 @@
    "id": "9a71fa36",
    "metadata": {},
    "source": [
-    "# ReAct via AutoGen\n",
+    "# ReAct\n",
     "\n",
-    "AutoGen supports different LLM prompting and reasoning strategies, such as ReAct, Reflection/Self-Critique, and more. This notebook demonstrates how to realize ReAct ([Yao et al., 2022](https://arxiv.org/abs/2210.03629)) with AutoGen. \n",
-    "\n",
-    "## Requirements\n",
-    "\n",
-    "AutoGen requires `Python>=3.8`. To run this notebook example, please install `pyautogen`:\n",
-    "```bash\n",
-    "pip install pyautogen\n",
-    "```"
+    "AutoGen supports different LLM prompting and reasoning strategies, such as ReAct, Reflection/Self-Critique, and more. This page demonstrates how to realize ReAct ([Yao et al., 2022](https://arxiv.org/abs/2210.03629)) with AutoGen. "
    ]
   },
   {
diff --git a/website/docs/topics/prompting-and-reasoning/reflection.ipynb b/website/docs/topics/prompting-and-reasoning/reflection.ipynb
index 6bfd1998e4d..a042c45e813 100644
--- a/website/docs/topics/prompting-and-reasoning/reflection.ipynb
+++ b/website/docs/topics/prompting-and-reasoning/reflection.ipynb
@@ -6,26 +6,9 @@
    "id": "9a71fa36",
    "metadata": {},
    "source": [
-    "# LLM Reflection in AutoGen\n",
+    "# LLM Reflection\n",
     "\n",
-    "AutoGen supports different LLM prompting and reasoning strategies, such as ReAct, Reflection/Self-Critique, and more. This notebook demonstrates how to realize general LLM reflection with AutoGen. Reflection is a general prompting strategy which involves having LLMs analyze their own outputs, behaviors, knowledge, or reasoning processes.\n",
-    "\n",
-    "## Requirements\n",
-    "\n",
-    "AutoGen requires `Python>=3.8`. To run this notebook example, please install `pyautogen`:\n",
-    "```bash\n",
-    "pip install pyautogen\n",
-    "```"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "2b803c17",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# %pip install \"pyautogen>=0.2.18\""
+    "AutoGen supports different LLM prompting and reasoning strategies, such as ReAct, Reflection/Self-Critique, and more. This notebook demonstrates how to realize general LLM reflection with AutoGen. Reflection is a general prompting strategy which involves having LLMs analyze their own outputs, behaviors, knowledge, or reasoning processes."
    ]
   },
   {
@@ -37,15 +20,6 @@
    "source": [
     "import autogen\n",
     "\n",
-    "try:\n",
-    "    from termcolor import colored\n",
-    "except ImportError:\n",
-    "\n",
-    "    def colored(x, *args, **kwargs):\n",
-    "        return x\n",
-    "\n",
-    "\n",
-    "# Construct the llm_config\n",
     "config_list = autogen.config_list_from_json(\n",
     "    \"OAI_CONFIG_LIST\",\n",
     ")\n",
@@ -60,7 +34,7 @@
    "id": "dea04741",
    "metadata": {},
    "source": [
-    "### Construct Agents\n",
+    "## Construct Agents\n",
     "Now we create three agents, including `user_proxy` as a user proxy, `writing_assistant` for generating solutions (based on the initial request or critique), and `reflection_assistant` for reflecting and providing critique."
    ]
   },
@@ -100,7 +74,7 @@
    "id": "8d2c77d7",
    "metadata": {},
    "source": [
-    "### Construct Agent Chats with reflection_assistant being a Nested Agent for Reflection"
+    "## Construct Agent Chats with `reflection_assistant` being a Nested Agent for Reflection"
    ]
   },
   {
@@ -368,7 +342,7 @@
    ],
    "source": [
     "def reflection_message(recipient, messages, sender, config):\n",
-    "    print(colored(\"Reflecting...\", \"yellow\"))\n",
+    "    print(\"Reflecting...\", \"yellow\")\n",
     "    return f\"Reflect and provide critique on the following writing. \\n\\n {recipient.chat_messages_for_summary(sender)[-1]['content']}\"\n",
     "\n",
     "\n",
diff --git a/website/docs/topics/task_decomposition.ipynb b/website/docs/topics/task_decomposition.ipynb
index 8c1bae06e0e..23c5dee9159 100644
--- a/website/docs/topics/task_decomposition.ipynb
+++ b/website/docs/topics/task_decomposition.ipynb
@@ -6,26 +6,9 @@
    "id": "9a71fa36",
    "metadata": {},
    "source": [
-    "# Task Decomposition in AutoGen\n",
+    "# Task Decomposition\n",
     "\n",
-    "In this notebook, we demonstrate several different ways to achieve task decomposition in AutoGen.\n",
-    "\n",
-    "## Requirements\n",
-    "\n",
-    "AutoGen requires `Python>=3.8`. To run this notebook example, please install `pyautogen`:\n",
-    "```bash\n",
-    "pip install pyautogen\n",
-    "```"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "2b803c17",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# %pip install \"pyautogen>=0.2.18\""
+    "On this page, we demonstrate several different ways to achieve task decomposition in AutoGen."
    ]
   },
   {
@@ -35,10 +18,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from typing_extensions import Annotated\n",
-    "\n",
     "import autogen\n",
-    "from autogen.cache import Cache\n",
     "\n",
     "config_list = autogen.config_list_from_json(\n",
     "    \"OAI_CONFIG_LIST\",\n",
@@ -51,6 +31,14 @@
     "}"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "11489237",
+   "metadata": {},
+   "source": [
+    "The task to be solved to write a blog post about the stock price performance of Nvidia in the past month."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -85,6 +73,8 @@
     }
    ],
    "source": [
+    "from typing_extensions import Annotated\n",
+    "\n",
     "planner = autogen.AssistantAgent(\n",
     "    name=\"planner\",\n",
     "    llm_config=llm_config,\n",
@@ -120,8 +110,6 @@
     ")\n",
     "\n",
     "# register the function task_decomposition for execution\n",
-    "\n",
-    "\n",
     "@user_proxy.register_for_execution()\n",
     "@assistant.register_for_llm(\n",
     "    name=\"task_decomposition\",\n",