Apply suggestions from code review

Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

units/en/unit2/introduction.mdx

@@ -28,6 +28,7 @@ Considering these ideas, we can already identify the need for some features:
 * A *system prompt* synced with the parser.
 * A *memory system*.
 * *Error logging and retry mechanisms* to control LLM mistakes.
+We'll explore how these topics are resolved in various frameworks, including `smolagents`, `LlamaIndex`, and `LangGraph`.
 
 ## Agentic Frameworks Units
 

units/en/unit2/smolagents/quiz2.mdx

@@ -44,7 +44,7 @@ choices={[
   },
   {
     text: "It stores every action in JSON for easy parsing before executing them all at once",
-    explain: "That behavior matches ToolCallingAgent's JSON-based approach, not CodeAgent.",
+    explain: "This behavior matches ToolCallingAgent's JSON-based approach, not CodeAgent.",
   },
   {
     text: "It cycles through writing internal thoughts, generating Python code, executing the code, and logging the results until it arrives at a final answer",