# Production Pipelines

Paradime's [Bolt](https://docs.paradime.io/app-help/documentation/bolt) is a comprehensive orchestration solution for deploying dbt™ models in production. Within Bolt, you can leverage DinoAI to quickly identify and resolve issues that may arise during your dbt™ production runs.

### Troubleshooting dbt™ Production Runs

When reviewing the [Run Logs](https://docs.paradime.io/app-help/bolt/managing-schedules/analyzing-run-details#run-logs) for a specific Bolt schedule, DinoAI provides a detailed summary of each command execution. This summary breaks down the overall execution, highlights any warnings or errors, and offers recommendations to improve the reliability and performance of your production pipelines.

<figure><img src="https://2337193041-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FHET0AD04uHMgdeLAjptq%2Fuploads%2F7a8aWStg5kUJuXaCsqqE%2Fimage.png?alt=media&#x26;token=3449145c-7d43-4c6e-b3af-dc22bfc5ded3" alt=""><figcaption><p>Example: DinoAI Summary</p></figcaption></figure>

#### How to use

1. From the Bolt UI, select a specific schedule
2. Scroll down to [Run History](https://docs.paradime.io/app-help/bolt/managing-schedules/viewing-run-log-history#run-history) where you'll find a list individual executions of your bolt schedule.
3. Click on a specific Bolt run to discover additional[ run details](https://docs.paradime.io/app-help/documentation/bolt/managing-schedules/analyzing-run-details).
4. Scroll down to [Logs and Artifacts](https://docs.paradime.io/app-help/bolt/managing-schedules/analyzing-run-details#logs-and-artifacts) for a detailed record of each command executed during a scheduled run.
5. Select an executed command (ex. `dbt run`) that has an error/warning.
6. Select the "Summary" tab to discover a DinoAI generated message about your command's execution, warnings, and potential fixes.

{% @arcade/embed flowId="3vfnYgc3uEYepUvSn2H9" url="<https://app.arcade.software/share/3vfnYgc3uEYepUvSn2H9>" %}

By surfacing these insights, DinoAI helps you quickly troubleshoot and address issues that may arise during your dbt™ production runs, ensuring reliable and efficient deployment of your data models.