diff --git a/scenarios/06-rag-vector-classified-docs/README.md b/scenarios/06-rag-vector-classified-docs/README.md
index db02c97..879a023 100755
--- a/scenarios/06-rag-vector-classified-docs/README.md
+++ b/scenarios/06-rag-vector-classified-docs/README.md
@@ -17,35 +17,32 @@ Before Oracle Deep Data Security, vector search can retrieve confidential HR, le
 
 ## Where To Run The Commands
 
-Run commands from the repository root:
-
-```powershell
-cd C:\Users\rodrigo\Documents\Codex\oracle-deep-data-security-lab
-```
-
-Connect to the database with SQLcl or SQL*Plus:
+Run SQL scripts from the repository root. On Linux/macOS/WSL:
 
 ```bash
-sql "<connect_string>"
+cd ~/DEEP-DATA-SECURITY/oracle-deep-data-security-lab
+export TNS_ADMIN=~/DEEP-DATA-SECURITY/wallet-ddslab
+```
+
+Connect as the lab administrator:
+
+```bash
+sql admin@ddslab_tunnel
 ```
 
 This scenario uses the `VECTOR` type, `TO_VECTOR`, and `VECTOR_DISTANCE`. Use a database version with Oracle AI Vector Search support.
 
+SQLcl note: when running a script with `@file.sql`, press Enter once and wait for the output. Do not type `/` afterward, because `/` reruns the last command in the SQLcl buffer.
+
 ## Step By Step - Before, Vulnerable Environment
 
-1. Connect to the database:
-
-   ```bash
-   sql "<connect_string>"
-   ```
-
-2. Reset the scenario:
+1. Reset the scenario as `ADMIN`:
 
    ```sql
    @scenarios/06-rag-vector-classified-docs/sql/99_reset.sql
    ```
 
-3. Create the chunk table, simple embeddings, and personas:
+2. Create the chunk table, seed classified documents, and create personas:
 
    ```sql
    @scenarios/06-rag-vector-classified-docs/sql/00_schema.sql
@@ -53,35 +50,53 @@ This scenario uses the `VECTOR` type, `TO_VECTOR`, and `VECTOR_DISTANCE`. Use a
    @scenarios/06-rag-vector-classified-docs/sql/02_identities.sql
    ```
 
+3. Show all available chunks as `ADMIN`:
+
+   ```sql
+   SELECT chunk_id, document_title, department, classification, chunk_text
+   FROM dds_rag_chunks
+   ORDER BY chunk_id;
+   ```
+
 4. Simulate the RAG question:
 
    ```text
    Summarize critical documents about renewals, people, and legal risks.
    ```
 
-5. Run the vector search:
+5. Connect as `nina`, a regular employee:
+
+   ```bash
+   sql 'nina/Welcome1_DDS!@ddslab_tunnel'
+   ```
+
+6. Run the vector search before DDS:
 
    ```sql
    @scenarios/06-rag-vector-classified-docs/sql/04_test_queries.sql
    ```
 
-Expected result before protection: retrieval may return `HR_CONFIDENTIAL`, `LEGAL_CONFIDENTIAL`, and `EXECUTIVE_CONFIDENTIAL` chunks.
+Expected result before protection: the retrieval may return `HR_CONFIDENTIAL`, `LEGAL_CONFIDENTIAL`, and `EXECUTIVE_CONFIDENTIAL` chunks to a regular employee because the legacy retrieval role is broad.
 
 ## Step By Step - After, With Deep Data Security
 
-1. Apply data grants by classification:
+1. Reconnect as `ADMIN` and apply data grants by classification:
 
    ```sql
    @scenarios/06-rag-vector-classified-docs/sql/03_data_grants.sql
    ```
 
-2. Run the same vector search again:
+2. Connect as `nina` and run the same vector search:
+
+   ```bash
+   sql 'nina/Welcome1_DDS!@ddslab_tunnel'
+   ```
 
    ```sql
    @scenarios/06-rag-vector-classified-docs/sql/04_test_queries.sql
    ```
 
-3. Repeat the demo by simulating `nina`, `heitor`, `sofia`, and `carlos`.
+3. Repeat the same test as `heitor`, `sofia`, and `carlos`.
 
 Expected result after protection:
 
@@ -108,4 +123,3 @@ Linux/macOS:
 ## Demo Details
 
 See the complete walkthrough, evidence, and official references in [RUNBOOK.md](RUNBOOK.md).
-
diff --git a/scenarios/06-rag-vector-classified-docs/RUNBOOK.md b/scenarios/06-rag-vector-classified-docs/RUNBOOK.md
index 259b379..33b128a 100755
--- a/scenarios/06-rag-vector-classified-docs/RUNBOOK.md
+++ b/scenarios/06-rag-vector-classified-docs/RUNBOOK.md
@@ -18,13 +18,27 @@ Show that a RAG agent retrieves only authorized chunks/documents before sending
 
 ## Before - Vulnerable Environment
 
-1. Reset the scenario:
+1. From the repository root, connect as `ADMIN`:
+
+   ```bash
+   cd ~/DEEP-DATA-SECURITY/oracle-deep-data-security-lab
+   export TNS_ADMIN=~/DEEP-DATA-SECURITY/wallet-ddslab
+   sql admin@ddslab_tunnel
+   ```
+
+   Presenter note: `ADMIN` prepares the classified chunks and security personas.
+
+   SQLcl note: after running a script with `@file.sql`, do not type `/`. The slash reruns the last command in the SQLcl buffer and can make a successful command look like an error.
+
+2. Reset the scenario:
 
    ```sql
    @scenarios/06-rag-vector-classified-docs/sql/99_reset.sql
    ```
 
-2. Create chunks and personas without applying data grants:
+   Presenter note: this removes prior Data Grants, roles, users, and test data.
+
+3. Create chunks and personas without applying data grants:
 
    ```sql
    @scenarios/06-rag-vector-classified-docs/sql/00_schema.sql
@@ -32,18 +46,44 @@ Show that a RAG agent retrieves only authorized chunks/documents before sending
    @scenarios/06-rag-vector-classified-docs/sql/02_identities.sql
    ```
 
-3. Simulate the RAG question:
+   Presenter note: `rag_legacy_retrieval_role` simulates a broad RAG retrieval layer before DDS is enforced.
+
+4. Show every chunk and its classification:
+
+   ```sql
+   SELECT chunk_id, document_title, department, classification, chunk_text
+   FROM dds_rag_chunks
+   ORDER BY chunk_id;
+   ```
+
+   Presenter note: explain that confidential chunks should not be sent to the LLM for every user.
+
+5. Simulate the RAG question:
 
    ```text
    Summarize critical documents about renewals, people, and legal risks.
    ```
 
-4. Run the vector search:
+6. Exit and connect as Nina, a regular employee:
+
+   ```sql
+   exit
+   ```
+
+   ```bash
+   sql 'nina/Welcome1_DDS!@ddslab_tunnel'
+   ```
+
+   Presenter note: Nina represents a regular employee using an internal copilot.
+
+7. Run the vector search before DDS:
 
    ```sql
    @scenarios/06-rag-vector-classified-docs/sql/04_test_queries.sql
    ```
 
+   Presenter note: before DDS, a broad retrieval path can place HR, legal, or executive confidential chunks in the LLM context.
+
 ## Expected Result Before
 
 - The search may retrieve `HR_CONFIDENTIAL`, `LEGAL_CONFIDENTIAL`, and `EXECUTIVE_CONFIDENTIAL` chunks.
@@ -51,18 +91,50 @@ Show that a RAG agent retrieves only authorized chunks/documents before sending
 
 ## After - Applying Deep Data Security
 
-1. Apply data grants by classification:
+1. Exit and reconnect as `ADMIN`:
+
+   ```sql
+   exit
+   ```
+
+   ```bash
+   sql admin@ddslab_tunnel
+   ```
+
+2. Apply data grants by classification:
 
    ```sql
    @scenarios/06-rag-vector-classified-docs/sql/03_data_grants.sql
    ```
 
-2. Run the same search as `nina`, `heitor`, `sofia`, and `carlos`:
+   Presenter note: the database now filters chunks before the LLM receives any context.
+
+3. Test Nina after DDS:
+
+   ```sql
+   exit
+   ```
+
+   ```bash
+   sql 'nina/Welcome1_DDS!@ddslab_tunnel'
+   ```
 
    ```sql
    @scenarios/06-rag-vector-classified-docs/sql/04_test_queries.sql
    ```
 
+   Presenter note: Nina should retrieve only `PUBLIC` and `INTERNAL` chunks.
+
+4. Repeat the same search as HR, legal, and executive personas:
+
+   ```bash
+   sql 'heitor/Welcome1_DDS!@ddslab_tunnel'
+   sql 'sofia/Welcome1_DDS!@ddslab_tunnel'
+   sql 'carlos/Welcome1_DDS!@ddslab_tunnel'
+   ```
+
+   Presenter note: each persona receives only the chunk classifications authorized for that business role.
+
 ## Expected Result After
 
 - `nina` retrieves only `PUBLIC` and `INTERNAL` chunks.
@@ -83,4 +155,3 @@ Show that a RAG agent retrieves only authorized chunks/documents before sending
 - Create Data Grants: https://docs.oracle.com/en/database/oracle/oracle-database/26/ddscg/create-data-grants.html
 - TO_VECTOR SQL Reference: https://docs.oracle.com/en/database/oracle/oracle-database/26/sqlrf/to_vector.html
 - VECTOR operations in PL/SQL: https://docs.oracle.com/en/database/oracle/oracle-database/26/lnpls/sql-data-types.html
-
diff --git a/scenarios/06-rag-vector-classified-docs/evidence/expected-results.md b/scenarios/06-rag-vector-classified-docs/evidence/expected-results.md
index dd75caa..3c5db77 100755
--- a/scenarios/06-rag-vector-classified-docs/evidence/expected-results.md
+++ b/scenarios/06-rag-vector-classified-docs/evidence/expected-results.md
@@ -1,8 +1,14 @@
 # Expected Results
 
+## Before Oracle Deep Data Security
+
+- A broad legacy retrieval role can return `HR_CONFIDENTIAL`, `LEGAL_CONFIDENTIAL`, and `EXECUTIVE_CONFIDENTIAL` chunks.
+- A regular employee such as `nina` may receive sensitive chunks in the RAG context before the LLM generates an answer.
+
+## After Oracle Deep Data Security
+
 - `nina` retrieves only `PUBLIC` and `INTERNAL` chunks.
 - `heitor` retrieves `HR_CONFIDENTIAL` plus public/internal chunks.
 - `sofia` retrieves `LEGAL_CONFIDENTIAL` plus public/internal chunks.
-- `carlos` retrieves all classifications.
+- `carlos` retrieves all classifications through the executive role.
 - The RAG layer receives only chunks authorized by the database policy.
-
diff --git a/scenarios/06-rag-vector-classified-docs/sql/00_schema.sql b/scenarios/06-rag-vector-classified-docs/sql/00_schema.sql
index fe3b226..bfc0e99 100755
--- a/scenarios/06-rag-vector-classified-docs/sql/00_schema.sql
+++ b/scenarios/06-rag-vector-classified-docs/sql/00_schema.sql
@@ -1,11 +1,20 @@
 WHENEVER SQLERROR EXIT SQL.SQLCODE
 
-CREATE TABLE dds_rag_chunks (
-  chunk_id        NUMBER GENERATED BY DEFAULT AS IDENTITY PRIMARY KEY,
-  document_title VARCHAR2(160) NOT NULL,
-  department     VARCHAR2(40) NOT NULL,
-  classification VARCHAR2(30) NOT NULL,
-  chunk_text     VARCHAR2(1000) NOT NULL,
-  embedding      VECTOR(3, FLOAT32)
-);
-
+BEGIN
+  EXECUTE IMMEDIATE q'[
+    CREATE TABLE dds_rag_chunks (
+      chunk_id        NUMBER GENERATED BY DEFAULT AS IDENTITY PRIMARY KEY,
+      document_title VARCHAR2(160) NOT NULL,
+      department     VARCHAR2(40) NOT NULL,
+      classification VARCHAR2(30) NOT NULL,
+      chunk_text     VARCHAR2(1000) NOT NULL,
+      embedding      VECTOR(3, FLOAT32)
+    )
+  ]';
+EXCEPTION
+  WHEN OTHERS THEN
+    IF SQLCODE != -955 THEN
+      RAISE;
+    END IF;
+END;
+/
diff --git a/scenarios/06-rag-vector-classified-docs/sql/01_seed_data.sql b/scenarios/06-rag-vector-classified-docs/sql/01_seed_data.sql
index 5008c46..37d784c 100755
--- a/scenarios/06-rag-vector-classified-docs/sql/01_seed_data.sql
+++ b/scenarios/06-rag-vector-classified-docs/sql/01_seed_data.sql
@@ -1,19 +1,22 @@
 WHENEVER SQLERROR EXIT SQL.SQLCODE
+SET DEFINE OFF
 
-INSERT INTO dds_rag_chunks (document_title, department, classification, chunk_text, embedding)
-VALUES ('Benefits Policy', 'HR', 'INTERNAL', 'General benefits policy available to employees.', TO_VECTOR('[0.10,0.20,0.30]'));
+DELETE FROM dds_rag_chunks;
 
-INSERT INTO dds_rag_chunks (document_title, department, classification, chunk_text, embedding)
-VALUES ('Executive Compensation Plan', 'HR', 'HR_CONFIDENTIAL', 'Compensation calibration for executives and retention risks.', TO_VECTOR('[0.11,0.21,0.31]'));
+INSERT INTO dds_rag_chunks (chunk_id, document_title, department, classification, chunk_text, embedding)
+VALUES (1, 'Benefits Policy', 'HR', 'INTERNAL', 'General benefits policy available to employees.', TO_VECTOR('[0.10,0.20,0.30]'));
 
-INSERT INTO dds_rag_chunks (document_title, department, classification, chunk_text, embedding)
-VALUES ('Contract Renewal Risk', 'LEGAL', 'LEGAL_CONFIDENTIAL', 'Legal risk on renewal clauses for strategic accounts.', TO_VECTOR('[0.80,0.10,0.20]'));
+INSERT INTO dds_rag_chunks (chunk_id, document_title, department, classification, chunk_text, embedding)
+VALUES (2, 'Executive Compensation Plan', 'HR', 'HR_CONFIDENTIAL', 'Compensation calibration for executives and retention risks.', TO_VECTOR('[0.11,0.21,0.31]'));
 
-INSERT INTO dds_rag_chunks (document_title, department, classification, chunk_text, embedding)
-VALUES ('Company Travel Guide', 'GENERAL', 'PUBLIC', 'Public travel and expense guidance for all employees.', TO_VECTOR('[0.20,0.70,0.10]'));
+INSERT INTO dds_rag_chunks (chunk_id, document_title, department, classification, chunk_text, embedding)
+VALUES (3, 'Contract Renewal Risk', 'LEGAL', 'LEGAL_CONFIDENTIAL', 'Legal risk on renewal clauses for strategic accounts.', TO_VECTOR('[0.80,0.10,0.20]'));
 
-INSERT INTO dds_rag_chunks (document_title, department, classification, chunk_text, embedding)
-VALUES ('Board M&A Briefing', 'EXEC', 'EXECUTIVE_CONFIDENTIAL', 'Potential acquisition targets and board-level financial exposure.', TO_VECTOR('[0.90,0.20,0.40]'));
+INSERT INTO dds_rag_chunks (chunk_id, document_title, department, classification, chunk_text, embedding)
+VALUES (4, 'Company Travel Guide', 'GENERAL', 'PUBLIC', 'Public travel and expense guidance for all employees.', TO_VECTOR('[0.20,0.70,0.10]'));
+
+INSERT INTO dds_rag_chunks (chunk_id, document_title, department, classification, chunk_text, embedding)
+VALUES (5, 'Board M&A Briefing', 'EXEC', 'EXECUTIVE_CONFIDENTIAL', 'Potential acquisition targets and board-level financial exposure.', TO_VECTOR('[0.90,0.20,0.40]'));
 
 COMMIT;
-
+SET DEFINE ON
diff --git a/scenarios/06-rag-vector-classified-docs/sql/02_identities.sql b/scenarios/06-rag-vector-classified-docs/sql/02_identities.sql
index 7fd9e46..b80a631 100755
--- a/scenarios/06-rag-vector-classified-docs/sql/02_identities.sql
+++ b/scenarios/06-rag-vector-classified-docs/sql/02_identities.sql
@@ -17,6 +17,15 @@ GRANT rag_session_role TO rag_hr_role;
 GRANT rag_session_role TO rag_legal_role;
 GRANT rag_session_role TO rag_exec_role;
 
+-- Vulnerable baseline: this broad role simulates a RAG retrieval layer that can
+-- query every chunk before DDS is enforced.
+CREATE ROLE rag_legacy_retrieval_role;
+GRANT SELECT ON dds_rag_chunks TO rag_legacy_retrieval_role;
+GRANT rag_legacy_retrieval_role TO rag_employee_role;
+GRANT rag_legacy_retrieval_role TO rag_hr_role;
+GRANT rag_legacy_retrieval_role TO rag_legal_role;
+GRANT rag_legacy_retrieval_role TO rag_exec_role;
+
 GRANT DATA ROLE rag_employee_role TO nina;
 GRANT DATA ROLE rag_hr_role TO heitor;
 GRANT DATA ROLE rag_legal_role TO sofia;
diff --git a/scenarios/06-rag-vector-classified-docs/sql/99_reset.sql b/scenarios/06-rag-vector-classified-docs/sql/99_reset.sql
index 38d619b..9e8626d 100755
--- a/scenarios/06-rag-vector-classified-docs/sql/99_reset.sql
+++ b/scenarios/06-rag-vector-classified-docs/sql/99_reset.sql
@@ -20,6 +20,8 @@ BEGIN EXECUTE IMMEDIATE 'DROP DATA ROLE rag_exec_role'; EXCEPTION WHEN OTHERS TH
 /
 BEGIN EXECUTE IMMEDIATE 'DROP ROLE rag_session_role'; EXCEPTION WHEN OTHERS THEN NULL; END;
 /
+BEGIN EXECUTE IMMEDIATE 'DROP ROLE rag_legacy_retrieval_role'; EXCEPTION WHEN OTHERS THEN NULL; END;
+/
 BEGIN EXECUTE IMMEDIATE 'DROP END USER nina'; EXCEPTION WHEN OTHERS THEN NULL; END;
 /
 BEGIN EXECUTE IMMEDIATE 'DROP END USER heitor'; EXCEPTION WHEN OTHERS THEN NULL; END;