diff --git a/website/docs/Use-Cases/agent_chat.md b/website/docs/Use-Cases/agent_chat.md
index 25664656cbc2..921af166f7b9 100644
--- a/website/docs/Use-Cases/agent_chat.md
+++ b/website/docs/Use-Cases/agent_chat.md
@@ -327,56 +327,6 @@ With the pluggable auto-reply function, one can choose to invoke conversations w
 
 Another approach involves LLM-based function calls, where LLM decides if a specific function should be invoked based on the conversation's status during each inference. This approach enables dynamic multi-agent conversations, as seen in scenarios like [multi-user math problem solving scenario](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_two_users.ipynb), where a student assistant automatically seeks expertise via function calls.
 
-### LLM Caching
-
-Since version 0.2.8, a configurable context manager allows you to easily
-configure LLM cache, using either DiskCache or Redis. All agents inside the
-context manager will use the same cache.
-
-```python
-from autogen import Cache
-
-# Use Redis as cache
-with Cache.redis(redis_url="redis://localhost:6379/0") as cache:
-    user.initiate_chat(assistant, message=coding_task, cache=cache)
-
-# Use DiskCache as cache
-with Cache.disk() as cache:
-    user.initiate_chat(assistant, message=coding_task, cache=cache)
-```
-
-You can vary the `cache_seed` parameter to get different LLM output while
-still using cache.
-
-```python
-# Setting the cache_seed to 1 will use a different cache from the default one
-# and you will see different output.
-with Cache.disk(cache_seed=1) as cache:
-    user.initiate_chat(assistant, message=coding_task, cache=cache)
-```
-
-By default DiskCache uses `.cache` for storage. To change the cache directory,
-set `cache_path_root`:
-
-```python
-with Cache.disk(cache_path_root="/tmp/autogen_cache") as cache:
-    user.initiate_chat(assistant, message=coding_task, cache=cache)
-```
-
-For backward compatibility, DiskCache is on by default with `cache_seed` set to 41.
-To disable caching completely, set `cache_seed` to `None` in the `llm_config` of the agent.
-
-```python
-assistant = AssistantAgent(
-    "coding_agent",
-    llm_config={
-        "cache_seed": None,
-        "config_list": OAI_CONFIG_LIST,
-        "max_tokens": 1024,
-    },
-)
-```
-
 ### Diverse Applications Implemented with AutoGen
 
 The figure below shows six examples of applications built using AutoGen.
diff --git a/website/docs/topics/llm-caching.md b/website/docs/topics/llm-caching.md
new file mode 100644
index 000000000000..c7a80133a27d
--- /dev/null
+++ b/website/docs/topics/llm-caching.md
@@ -0,0 +1,49 @@
+# LLM Caching
+
+Since version [`0.2.8`](https://github.com/microsoft/autogen/releases/tag/v0.2.8), a configurable context manager allows you to easily
+configure LLM cache, using either [`DiskCache`](/docs/reference/cache/disk_cache#diskcache) or [`RedisCache`](/docs/reference/cache/redis_cache#rediscache). All agents inside the
+context manager will use the same cache.
+
+```python
+from autogen import Cache
+
+# Use Redis as cache
+with Cache.redis(redis_url="redis://localhost:6379/0") as cache:
+    user.initiate_chat(assistant, message=coding_task, cache=cache)
+
+# Use DiskCache as cache
+with Cache.disk() as cache:
+    user.initiate_chat(assistant, message=coding_task, cache=cache)
+```
+
+You can vary the `cache_seed` parameter to get different LLM output while
+still using cache.
+
+```python
+# Setting the cache_seed to 1 will use a different cache from the default one
+# and you will see different output.
+with Cache.disk(cache_seed=1) as cache:
+    user.initiate_chat(assistant, message=coding_task, cache=cache)
+```
+
+By default [`DiskCache`](/docs/reference/cache/disk_cache#diskcache) uses `.cache` for storage. To change the cache directory,
+set `cache_path_root`:
+
+```python
+with Cache.disk(cache_path_root="/tmp/autogen_cache") as cache:
+    user.initiate_chat(assistant, message=coding_task, cache=cache)
+```
+
+For backward compatibility, [`DiskCache`](/docs/reference/cache/disk_cache#diskcache) is on by default with `cache_seed` set to 41.
+To disable caching completely, set `cache_seed` to `None` in the `llm_config` of the agent.
+
+```python
+assistant = AssistantAgent(
+    "coding_agent",
+    llm_config={
+        "cache_seed": None,
+        "config_list": OAI_CONFIG_LIST,
+        "max_tokens": 1024,
+    },
+)
+```