diff --git a/learn/generation/langchain/handbook/06-langchain-agents.ipynb b/learn/generation/langchain/handbook/06-langchain-agents.ipynb
index 4acd1e01..ae1dd36e 100644
--- a/learn/generation/langchain/handbook/06-langchain-agents.ipynb
+++ b/learn/generation/langchain/handbook/06-langchain-agents.ipynb
@@ -377,7 +377,7 @@
         "from langchain_experimental.sql import SQLDatabaseChain\n",
         "\n",
         "db = SQLDatabase(engine)\n",
-        "sql_chain = SQLDatabaseChain(llm=llm, database=db, verbose=True)"
+        "sql_chain = SQLDatabaseChain.from_llm(llm=llm, db=db, verbose=True)"
       ]
     },
     {
@@ -428,9 +428,9 @@
     {
       "cell_type": "markdown",
       "source": [
-        "In this first example we will use slightly different type of agent - SQL Agent which can be instantiated with it's own method `create_sql_agent`. Other agents will be instantiated in more generic way as we will see below in other examples.\n",
+        "In this first example we will use a slightly different type of agent - SQL Agent which can be instantiated with its own method `create_sql_agent`. Other agents will be instantiated more generically as we will see below in other examples.\n",
         "<br><br>\n",
-        "This method uses *toolkit* instead of simple list of `tools`. You can read more about them in the [documentation](https://python.langchain.com/docs/modules/agents/toolkits/). For this use case, we will use `SQLDatabaseToolkit`."
+        "This method uses *toolkit* instead of a simple list of `tools`. You can read more about them in the [documentation](https://python.langchain.com/docs/modules/agents/toolkits/). For this use case, we will use `SQLDatabaseToolkit`."
       ],
       "metadata": {
         "id": "Tgn6dRLEcxli"
@@ -1249,4 +1249,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 5
-}
\ No newline at end of file
+}