diff --git a/src/documentation/classification.ipynb b/src/documentation/classification.ipynb
index ccfb20bb4..b64750213 100644
--- a/src/documentation/classification.ipynb
+++ b/src/documentation/classification.ipynb
@@ -32,7 +32,14 @@
     "LLMs, on the other hand, can swiftly process and categorize enormous datasets with minimal human intervention.\n",
     "By leveraging LLMs for classification tasks, organizations can unlock insights from their data more efficiently, streamline their workflows, and harness the full potential of their information assets.\n",
     "\n",
-    "In this notebook, we present two alternative ways for classifying text using Aleph Alpha's Luminous models.\n",
+    "\n",
+    "<div class=\"alert alert-warning\">\n",
+    "\n",
+    "This notebook is designed to showcase two different approaches and ways of classifying text using Aleph Alpha's Luminous models.\n",
+    "To make proper use of the classification task, it is necessary to evaluate the results in an iterative way, to ensure it satisfies your requirements.\n",
+    "For an example of how such an evaluation can look like, refer to [evaluation.ipynb](./evaluation.ipynb).\n",
+    "</div>\n",
+    "\n",
     "First, let's have a look at single-label classification using prompting.\n",
     "\n",
     "### Prompt-based single-label classification\n",
diff --git a/src/documentation/document_index.ipynb b/src/documentation/document_index.ipynb
index f95bc5f74..e3ea71c9b 100644
--- a/src/documentation/document_index.ipynb
+++ b/src/documentation/document_index.ipynb
@@ -42,7 +42,13 @@
     "To find segments that closely match your query, the system identifies chunks with embedding vectors that best align semantically with your question.\n",
     "The DI seamlessly manages document updates (using document names), determines the ideal chunk size, and optimizes the vector space search process.\n",
     "\n",
-    "In this notebook, we will show you how to upload your own documents to the DI, how to search through your documents, and how to build a question-answering system based on your DI-knowledge base."
+    "\n",
+    "<div class=\"alert alert-warning\">\n",
+    "\n",
+    "In this notebook, we will show you how to upload your own documents to the DI, how to search through your documents, and how to build a question-answering system based on your DI-knowledge base.\n",
+    "To make proper use of the search and question-answering task, it is necessary to evaluate the results in an iterative way, to ensure it satisfies your requirements.\n",
+    "For an example of how such an evaluation can look like, refer to [evaluation.ipynb](./evaluation.ipynb).\n",
+    "</div>\n"
    ]
   },
   {
diff --git a/src/documentation/qa.ipynb b/src/documentation/qa.ipynb
index e0ca82129..37955bc52 100644
--- a/src/documentation/qa.ipynb
+++ b/src/documentation/qa.ipynb
@@ -36,7 +36,13 @@
     "# Question and Answer\n",
     "\n",
     "A common use case for using large language models is to generate answers to questions based on a given piece of text.\n",
-    "We will be focusing on the open-book Q&A use case, where we provide the model with a piece of text we think is relevant to the question and ask the model to answer the question based on the given text."
+    "\n",
+    "<div class=\"alert alert-warning\">\n",
+    "\n",
+    "This notebook we will be focusing on the open-book Q&A use case, where we provide the model with a piece of text we think is relevant to the question and ask the model to answer the question based on the given text.\n",
+    "To make proper use of the classification task, it is necessary to evaluate the results in an iterative way, to ensure it satisfies your requirements.\n",
+    "For an example of how such an evaluation can look like, refer to [evaluation.ipynb](./evaluation.ipynb).\n",
+    "</div>\n"
    ]
   },
   {
diff --git a/src/documentation/summarization.ipynb b/src/documentation/summarization.ipynb
index 0695614a4..96f6d59f0 100644
--- a/src/documentation/summarization.ipynb
+++ b/src/documentation/summarization.ipynb
@@ -36,6 +36,13 @@
     "Summarizing and compressing information, whether from a text, a book or freely from previous experience, is something that is inherently useful for many different types of knowledge work.\n",
     "Large language models are adept at summarizing due to their sophisticated understanding of language structure, semantics, and context derived from the vast amounts of text they have been trained on.\n",
     "\n",
+    "<div class=\"alert alert-warning\">\n",
+    "\n",
+    "This notebook is designed to showcase a summarization task.\n",
+    "To make proper use of such a summarization example, it is necessary to evaluate the results in an iterative way, to ensure it satisfies your requirements.\n",
+    "For an example of how such an evaluation can look like, refer to [evaluation.ipynb](./evaluation.ipynb).\n",
+    "</div>\n",
+    "\n",
     "Let's take a Luminous model and try this out!\n"
    ]
   },