SEO: Step 2 — lowercase DAGs folder to dags

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Author: fmercadop

docs/getting-started/admin/configure-repository.md

@@ -14,7 +14,7 @@ Now that you have configured your Airflow settings you must ensure that your rep
 
 **Step 3:** **This step is optional** if you would like to make use of the [dbt-coves](https://github.com/datacoves/dbt-coves?tab=readme-ov-file#airflow-dags-generation-arguments) `dbt-coves generate airflow-dags` command. Create the `dags_yml_definitions` folder inside of your newly created `orchestrate` folder. This will leave you with two folders inside `orchestrate`- `orchestrate/dags` and `orchestrate/dags_yml_definitions`.
 
-**Step 4:** **This step is optional** if you would like to make use of the dbt-coves' extension `dbt-coves generate airflow-dags` command. You must create a config file for dbt-coves. Please follow the [generate DAGs from yml](/docs/how-tos/airflow/DAGs/generate-dags-from-yml) docs.
+**Step 4:** **This step is optional** if you would like to make use of the dbt-coves' extension `dbt-coves generate airflow-dags` command. You must create a config file for dbt-coves. Please follow the [generate DAGs from yml](/docs/how-tos/airflow/dags/generate-dags-from-yml) docs.
 
 ## Create a profiles.yml
 

docs/getting-started/admin/creating-airflow-dags.md

@@ -21,12 +21,12 @@ During the Airflow configuration step you added the `orchestrate` folder and the
 ## DAG 101 in Datacoves
 1. If you are eager to see Airflow and dbt in action within Datacoves, here is the simplest way to run dbt with Airflow.
 
-   [Run dbt](/docs/how-tos/airflow/DAGs/run-dbt)
+   [Run dbt](/docs/how-tos/airflow/dags/run-dbt)
 
 2. You have 2 options when it comes to writing DAGs in Datacoves. You can write them out using Python and place them in the `orchestrate/dags` directory, or you can generate your DAGs with `dbt-coves` from a YML definition. 
 
-   [Generate DAGs from yml definitions](/docs/how-tos/airflow/DAGs/generate-dags-from-yml) this is simpler for users not accustomed to using Python
+   [Generate DAGs from yml definitions](/docs/how-tos/airflow/dags/generate-dags-from-yml) this is simpler for users not accustomed to using Python
 
 3. You may also wish to use external libraries in your DAGs such as Pandas. In order to do that effectively, you can create custom Python scripts in a separate directory such as `orchestrate/python_scripts` and use the `DatacovesBashOperator` to handle all the behind the scenes work as well as run your custom script.**You will need to contact us beforehand to pre-configure any python libraries you need.**
 
-   [External Python DAG](/docs/how-tos/airflow/DAGs/external-python-dag)
+   [External Python DAG](/docs/how-tos/airflow/dags/external-python-dag)