diff --git a/backend/src/agents/generalist_agent.py b/backend/src/agents/generalist_agent.py
index afa72e5f..db6fa286 100644
--- a/backend/src/agents/generalist_agent.py
+++ b/backend/src/agents/generalist_agent.py
@@ -17,39 +17,6 @@
 )
 class GeneralistAgent(ChatAgent):
     async def invoke(self, utterance) -> str:
-        try:
-            answer_to_user = await answer_user_question(utterance, self.llm, self.model)
-            answer_result = json.loads(answer_to_user)
-            final_answer = json.loads(answer_result["response"]).get("answer", "")
-            if not final_answer:
-                response = {"content": "Error in answer format.", "ignore_validation": "false"}
-                return json.dumps(response, indent=4)
-            logger.info(f"Answer found successfully {final_answer}")
-            response = {"content": final_answer, "ignore_validation": "false"}
-            return json.dumps(response, indent=4)
-
-        except Exception as e:
-            logger.error(f"Error in web_general_search_core: {e}")
-            return "An error occurred while processing the search query."
-
-
-async def answer_user_question(search_query, llm, model) -> str:
-    try:
-        summariser_prompt = engine.load_prompt("generalist-answer", question=search_query)
-        response = await llm.chat(model, summariser_prompt, "")
-        return json.dumps(
-            {
-                "status": "success",
-                "response": response,
-                "error": None,
-            }
-        )
-    except Exception as e:
-        logger.error(f"Error during create search term: {e}")
-        return json.dumps(
-            {
-                "status": "error",
-                "response": None,
-                "error": str(e),
-            }
-        )
+        summariser_prompt = engine.load_prompt("generalist-answer", question=utterance)
+        response = await self.llm.chat(self.model, summariser_prompt, "")
+        return json.dumps({"content": response, "ignore_validation": "false"}, indent=4)
diff --git a/backend/src/agents/materiality_agent.py b/backend/src/agents/materiality_agent.py
index 8d4c7195..2b277e81 100644
--- a/backend/src/agents/materiality_agent.py
+++ b/backend/src/agents/materiality_agent.py
@@ -27,14 +27,15 @@ def create_llm_files(filenames: list[str]) -> list[LLMFile]:
 class MaterialityAgent(ChatAgent):
     async def invoke(self, utterance: str) -> str:
         materiality_files = await self.select_material_files(utterance)
-        if not materiality_files:
-            return f"Materiality Agent cannot find suitable reference documents to answer the question: {utterance}"
-        answer = await self.llm.chat_with_file(
-            self.model,
-            system_prompt=engine.load_prompt("answer-materiality-question"),
-            user_prompt=utterance,
-            files=create_llm_files(materiality_files)
-        )
+        if materiality_files:
+            answer = await self.llm.chat_with_file(
+                self.model,
+                system_prompt=engine.load_prompt("answer-materiality-question"),
+                user_prompt=utterance,
+                files=create_llm_files(materiality_files)
+            )
+        else:
+            answer = f"Materiality Agent cannot find suitable reference documents to answer the question: {utterance}"
         return json.dumps({"content": answer, "ignore_validation": False})
 
     async def list_material_topics_for_company(self, company_name: str) -> dict[str, str]:
diff --git a/backend/src/directors/report_director.py b/backend/src/directors/report_director.py
index 776c5e02..5ada9a87 100644
--- a/backend/src/directors/report_director.py
+++ b/backend/src/directors/report_director.py
@@ -47,8 +47,8 @@ def create_report_chat_message(filename: str, company_name: str, topics: dict[st
     if topics:
         topics_with_markdown = [f"{key}\n{value}" for key, value in topics.items()]
         report_chat_message += f"""
-        
-The following materiality topics were identified for {company_name} which the report focuses on:
+
+The following materiality topics were identified for {company_name}:
 
 {"\n\n".join(topics_with_markdown)}"""
     return report_chat_message