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diff --git a/content/posts/postgres-aggregates/index.md b/content/posts/postgres-aggregates/index.md
index a2ff276..cf7a977 100644
--- a/content/posts/postgres-aggregates/index.md
+++ b/content/posts/postgres-aggregates/index.md
@@ -2,12 +2,14 @@
 title: "Efficient PostgreSQL Aggregations"
 draft: false
 date: 2023-10-04
-lastmod: 2024-07-15
+lastmod: 2026-03-29
 description: "Diving into PostgreSQL query plans to improve our tooling"
 categories:
   - PostgreSQL
 ---
 
+> This article [has a follow-up](/posts/postgres-aggregates-correction/), where I fix a mistake in the subquery benchmarks and explore disk usage under production-like constraints.
+
 I recently stumbled upon a problem while crafting queries for PostgreSQL at work. We had a query with several correlated subqueries that was becoming too slow for the intended use (a search). I thought that using aggregations would solve it, but in fact it slowed it down, and even added bugs from counting duplicate rows.
 
 I couldn't find easily accessible knowledge about how to improve it on the Internet, so I decided to simplify the problem to its core and to investigate. This article is the walkthrough of my findings.