diff --git a/docs/panduan_integrasi_existing_airflow.md b/docs/panduan_integrasi_existing_airflow.md
index 63801d2..eea3eaf 100644
--- a/docs/panduan_integrasi_existing_airflow.md
+++ b/docs/panduan_integrasi_existing_airflow.md
@@ -237,17 +237,15 @@ docker ps --filter "name=airflow" --format "table {{.Names}}\t{{.Image}}\t{{.Sta
 *Catat nama kontainer scheduler dan dag processor serta port host webserver (misal: `0.0.0.0:12082->8080/tcp`).*
 
 #### 2. Injeksi Pustaka Engine ke Kontainer Berjalan (Tanpa Restart)
-Gunakan `docker exec` untuk memasang dependensi engine (`astronomer-cosmos`, `dbt-postgres`, `apache-airflow-providers-git`, dan `dlt`) langsung ke worker/scheduler tanpa mematikan layanan. *(Catatan: Pustaka `duckdb` dan `pyiceberg` sudah tersedia bawaan image)*:
+Gunakan `docker exec` untuk memasang pustaka yang belum ada (`astronomer-cosmos` dan `dlt`) langsung ke worker/scheduler tanpa mematikan layanan. *(Catatan: Pustaka `apache-airflow-providers-git`, `dbt-postgres`, `duckdb`, `pyiceberg`, dan `sling` sudah tersedia bawaan (*built-in*) di image resmi)*:
 ```bash
 # Injeksi ke Scheduler
 docker exec -u airflow <nama_kontainer_scheduler> pip install --no-cache-dir \
-  astronomer-cosmos==1.15.1 dbt-postgres==1.11.0 apache-airflow-providers-git==1.0.0 \
-  dlt[duckdb,filesystem]==1.6.1
+  astronomer-cosmos==1.15.1 dlt[duckdb,filesystem]==1.6.1
 
 # Injeksi ke DAG Processor
 docker exec -u airflow <nama_kontainer_dag_processor> pip install --no-cache-dir \
-  astronomer-cosmos==1.15.1 dbt-postgres==1.11.0 apache-airflow-providers-git==1.0.0 \
-  dlt[duckdb,filesystem]==1.6.1
+  astronomer-cosmos==1.15.1 dlt[duckdb,filesystem]==1.6.1
 
 # Verifikasi instalasi berhasil
 docker exec <nama_kontainer_scheduler> python -c "import cosmos, duckdb, pyiceberg; print('✅ Airflow Engine Ready!')"