diff --git a/notebook/agentchat_planning.ipynb b/notebook/agentchat_planning.ipynb
index 4f28c3b3195..b0fa24425b3 100644
--- a/notebook/agentchat_planning.ipynb
+++ b/notebook/agentchat_planning.ipynb
@@ -19,10 +19,10 @@
    "source": [
     "# Auto Generated Agent Chat: Collaborative Task Solving with Coding and Planning Agent\n",
     "\n",
-    "AutoGen offers conversable agents powered by LLM, tool or human, which can be used to perform tasks collectively via automated chat. This framework allows tool use and human participation through multi-agent conversation.\n",
+    "AutoGen offers conversable agents powered by LLM, tool, or human, which can be used to perform tasks collectively via automated chat. This framework allows tool use and human participation through multi-agent conversation.\n",
     "Please find documentation about this feature [here](https://microsoft.github.io/autogen/docs/Use-Cases/agent_chat).\n",
     "\n",
-    "In this notebook, we demonstrate how to use multiple agents to work together and accomplish a task which requires finding info from the web and coding. `AssistantAgent` is an LLM-based agent that can write and debug Python code (in a Python coding block) for a user to execute for a given task. `UserProxyAgent` is an agent which serves as a proxy for a user to execute the code written by `AssistantAgent`. We further create a planning agent for the assistant agent to consult. The planning agent is a variation of the LLM-based `AssistantAgent` with a different system message.\n",
+    "In this notebook, we demonstrate how to use multiple agents to work together and accomplish a task that requires finding info from the web and coding. `AssistantAgent` is an LLM-based agent that can write and debug Python code (in a Python coding block) for a user to execute for a given task. `UserProxyAgent` is an agent which serves as a proxy for a user to execute the code written by `AssistantAgent`. We further create a planning agent for the assistant agent to consult. The planning agent is a variation of the LLM-based `AssistantAgent` with a different system message.\n",
     "\n",
     "## Requirements\n",
     "\n",
@@ -59,9 +59,9 @@
     "  - OpenAI API key: os.environ[\"OPENAI_API_KEY\"] or `openai_api_key_file=\"key_openai.txt\"`.\n",
     "  - Azure OpenAI API key: os.environ[\"AZURE_OPENAI_API_KEY\"] or `aoai_api_key_file=\"key_aoai.txt\"`. Multiple keys can be stored, one per line.\n",
     "  - Azure OpenAI API base: os.environ[\"AZURE_OPENAI_API_BASE\"] or `aoai_api_base_file=\"base_aoai.txt\"`. Multiple bases can be stored, one per line.\n",
-    "* The [`config_list_from_json`](https://microsoft.github.io/autogen/docs/reference/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file. It first looks for an environment variable with a specified name. The value of the environment variable needs to be a valid json string. If that variable is not found, it then looks for a json file with the same name. It filters the configs by filter_dict.\n",
+    "* The [`config_list_from_json`](https://microsoft.github.io/autogen/docs/reference/oai/openai_utils#config_list_from_json) function loads a list of configurations from an environment variable or a json file. It first looks for an environment variable with a specified name. The value of the environment variable needs to be a valid json string. If that variable is not found, it looks for a json file with the same name. It filters the configs by filter_dict.\n",
     "\n",
-    "It's OK to have only the OpenAI API key, or only the Azure OpenAI API key + base. If you open this notebook in colab, you can upload your files by clicking the file icon on the left panel and then choose \"upload file\" icon.\n"
+    "It's OK to have only the OpenAI API key, or only the Azure OpenAI API key + base. If you open this notebook in colab, you can upload your files by clicking the file icon on the left panel and then choosing \"upload file\" icon.\n"
    ]
   },
   {
@@ -109,13 +109,13 @@
     "]\n",
     "```\n",
     "\n",
-    "If you open this notebook in colab, you can upload your files by clicking the file icon on the left panel and then choose \"upload file\" icon.\n",
+    "If you open this notebook in colab, you can upload your files by clicking the file icon on the left panel and then choosing \"upload file\" icon.\n",
     "\n",
-    "You can set the value of config_list in other ways you prefer, e.g., loading from a YAML file.\n",
+    "You can set the value of config_list in other ways, e.g., loading from a YAML file.\n",
     "\n",
     "## Construct Agents\n",
     "\n",
-    "We construct the planning agent named \"planner\" and a user proxy agent for the planner named \"planner_user\". We specify `human_input_mode` as \"NEVER\" in the user proxy agent, which will never ask for human feedback. We define `ask_planner` function to send a message to planner and return the suggestion from the planner."
+    "We construct the planning agent named \"planner\" and a user proxy agent for the planner named \"planner_user\". We specify `human_input_mode` as \"NEVER\" in the user proxy agent, which will never ask for human feedback. We define `ask_planner` function to send a message to the planner and return the suggestion from the planner."
    ]
   },
   {
@@ -128,7 +128,7 @@
     "    name=\"planner\",\n",
     "    llm_config={\"config_list\": config_list},\n",
     "    # the default system message of the AssistantAgent is overwritten here\n",
-    "    system_message=\"You are a helpful AI assistant. You suggest coding and reasoning steps for another AI assistant to accomplish a task. Do not suggest concrete code. For any action beyond writing code or reasoning, convert it to a step which can be implemented by writing code. For example, the action of browsing the web can be implemented by writing code which reads and prints the content of a web page. Finally, inspect the execution result. If the plan is not good, suggest a better plan. If the execution is wrong, analyze the error and suggest a fix.\"\n",
+    "    system_message=\"You are a helpful AI assistant. You suggest coding and reasoning steps for another AI assistant to accomplish a task. Do not suggest concrete code. For any action beyond writing code or reasoning, convert it to a step that can be implemented by writing code. For example, browsing the web can be implemented by writing code that reads and prints the content of a web page. Finally, inspect the execution result. If the plan is not good, suggest a better plan. If the execution is wrong, analyze the error and suggest a fix.\"\n",
     ")\n",
     "planner_user = autogen.UserProxyAgent(\n",
     "    name=\"planner_user\",\n",
@@ -202,7 +202,7 @@
    "source": [
     "## Perform a task\n",
     "\n",
-    "We invoke the `initiate_chat()` method of the user proxy agent to start the conversation. When you run the cell below, you will be prompted to provide feedback after the assistant agent sends a \"TERMINATE\" signal in the end of the message. If you don't provide any feedback (by pressing Enter directly), the conversation will finish. Before the \"TERMINATE\" signal, the user proxy agent will try to execute the code suggested by the assistant agent on behalf of the user."
+    "We invoke the `initiate_chat()` method of the user proxy agent to start the conversation. When you run the cell below, you will be prompted to provide feedback after the assistant agent sends a \"TERMINATE\" signal at the end of the message. If you don't provide any feedback (by pressing Enter directly), the conversation will finish. Before the \"TERMINATE\" signal, the user proxy agent will try to execute the code suggested by the assistant agent on behalf of the user."
    ]
   },
   {