The tutorial explains how to quickly deploy a dbt project as a scheduled and monitored pipeline using Prefect Cloud, a simple Python script, and GitHub, bypassing the usual lengthy infrastructure setup. By creating a Prefect flow with the PrefectDbtRunner, users can execute dbt commands such as `dbt deps` and `dbt build`, and handle retries if necessary. The guide details the steps to set up a dbt project with Prefect Cloud, including installing necessary software, creating a GitHub repository, and configuring Prefect for deployment. Once set up, the dbt pipeline runs in the cloud, offering real-time monitoring, scheduled runs, and automatic updates with GitHub changes. The process is designed to be scalable from prototype to production without altering existing workflows, enabling users to manage their data transformations efficiently.