diff --git a/docs/agents/_includes/query_agent.mts b/docs/agents/_includes/query_agent.mts
index a671d652..e3011085 100644
--- a/docs/agents/_includes/query_agent.mts
+++ b/docs/agents/_includes/query_agent.mts
@@ -389,6 +389,18 @@ for (const obj of basicSearchResponse.searchResults.objects) {
 }
 // END BasicSearchQuery
 
+// START RetrievalStrategyExample
+const strategyResponse = await qa.search("Find me some vintage shoes under $70", {
+    filtering: "recall",
+    limit: 10,
+})
+
+for (const obj of strategyResponse.searchResults.objects) {
+    console.log(`Product: ${obj.properties['name']} - ${obj.properties['price']}`)
+}
+// END RetrievalStrategyExample
+
+
 // START DiversityRanking
 const diversitySearchResponse = await qa.search("summer shoes", {
     limit: 10,
diff --git a/docs/agents/_includes/query_agent.py b/docs/agents/_includes/query_agent.py
index d76ef630..0c07ccc3 100644
--- a/docs/agents/_includes/query_agent.py
+++ b/docs/agents/_includes/query_agent.py
@@ -409,6 +409,18 @@ def populate_weaviate(client, overwrite_existing=False):
     print(f"Product: {obj.properties['name']} - ${obj.properties['price']}")
 # END BasicSearchQuery
 
+# START RetrievalStrategyExample
+search_response = qa.search(
+    "Find me some vintage shoes under $70",
+    filtering="recall",
+    limit=10,
+)
+
+for obj in search_response.search_results.objects:
+    print(f"Product: {obj.properties['name']} - ${obj.properties['price']}")
+# END RetrievalStrategyExample
+
+
 # START SearchModeResponseStructure
 # SearchModeResponse structure for Python
 search_response = qa.search("winter boots for under $100", limit=5)
diff --git a/docs/agents/query/usage.md b/docs/agents/query/usage.md
index 9d6bbe8e..d2db165f 100644
--- a/docs/agents/query/usage.md
+++ b/docs/agents/query/usage.md
@@ -282,6 +282,36 @@ Metadata: {'creation_time': None, 'last_update_time': None, 'distance': None, 'c
 
 </details>
 
+#### `Search` with customized filtering
+
+Search Mode uses query rewriting to transform your original query into one or multiple Weaviate queries, each with either a search query, metadata filters, or both. The `filtering` parameter controls how many Weaviate queries are generated.
+
+ **`"recall"`** (default): Generates multiple Weaviate queries spanning different filters and interpretations of the user query.
+You should use these when you prefer to get results, even if they don't match every criteria in your query.
+
+- **`"precision"`**: Generates a single Weaviate query targeting the most likely interpretation of the user query.
+You should use this when you want the results to follow your query intent closely, even if that means potentially receiving no results.
+
+<Tabs className="code" groupId="languages">
+    <TabItem value="py_agents" label="Python">
+        <FilteredTextBlock
+            text={PyCode}
+            startMarker="# START RetrievalStrategyExample"
+            endMarker="# END RetrievalStrategyExample"
+            language="py"
+        />
+    </TabItem>
+    <TabItem value="ts_agents" label="JavaScript/TypeScript">
+        <FilteredTextBlock
+            text={TSCode}
+            startMarker="// START RetrievalStrategyExample"
+            endMarker="// END RetrievalStrategyExample"
+            language="ts"
+        />
+    </TabItem>
+
+</Tabs>
+
 #### `Search` with pagination
 
 `Search` supports pagination to handle large result sets efficiently: