diff --git a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/vectordbs/redis.adoc b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/vectordbs/redis.adoc
index d198385e5..9db2e8c35 100644
--- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/vectordbs/redis.adoc
+++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/vectordbs/redis.adoc
@@ -100,6 +100,10 @@ public VectorStore vectorStore(EmbeddingClient embeddingClient) {
 }
 ----
 
+> [NOTE]
+> It is more convenient and preferred to create the `RedisVectorStore` as a Bean.
+> But if you decide to create it manually, then you must call the `RedisVectorStore#afterPropertiesSet()` after setting the properties and before using the client.
+
 > [NOTE]
 > You must list explicitly all metadata field names and types (`TAG`, `TEXT`, or `NUMERIC`) for any metadata field used in filter expression.
 > The `withMetadataFields` above registers filterable metadata fields: `country` of type `TAG`, `year` of type `NUMERIC`.