diff --git a/website/src/pages/en/subgraphs/cookbook/timeseries.mdx b/website/src/pages/en/subgraphs/cookbook/timeseries.mdx
index 2c721a9cef23..ea6040d1931d 100644
--- a/website/src/pages/en/subgraphs/cookbook/timeseries.mdx
+++ b/website/src/pages/en/subgraphs/cookbook/timeseries.mdx
@@ -36,6 +36,10 @@ Timeseries and aggregations reduce data processing overhead and accelerate queri
 
 ## How to Implement Timeseries and Aggregations
 
+### Prerequisites
+
+You need `spec version 1.1.0` for this feature.
+
 ### Defining Timeseries Entities
 
 A timeseries entity represents raw data points collected over time. It is defined with the `@entity(timeseries: true)` annotation. Key requirements:
@@ -51,7 +55,7 @@ Example:
 type Data @entity(timeseries: true) {
   id: Int8!
   timestamp: Timestamp!
-  price: BigDecimal!
+  amount: BigDecimal!
 }
 ```
 
@@ -68,11 +72,11 @@ Example:
 type Stats @aggregation(intervals: ["hour", "day"], source: "Data") {
   id: Int8!
   timestamp: Timestamp!
-  sum: BigDecimal! @aggregate(fn: "sum", arg: "price")
+  sum: BigDecimal! @aggregate(fn: "sum", arg: "amount")
 }
 ```
 
-In this example, Stats aggregates the price field from Data over hourly and daily intervals, computing the sum.
+In this example, Stats aggregates the amount field from Data over hourly and daily intervals, computing the sum.
 
 ### Querying Aggregated Data