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Starter Guide: How to get the most out of your AI copilot

Hands-on guide on how to use AI to improve code quality, automate repetitive tasks, and optimize queries - with code and prompt examples.

Emelie Holgersson

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Jul 16, 2024

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2

min read

Integrating an AI copilot like DinoAI into your daily workflow, you can significantly boost productivity, enhance code quality, and streamline collaboration. This hands-on guide offers practical examples on how to automate repetitive tasks, and optimize queries.

By leveraging an AI copilot, you can focus on more strategic (and fun!) tasks, ultimately making your work more efficient and enjoyable.

1. Automate repetitive tasks

Automating repetitive tasks is essential for improving productivity and reducing errors. Using SQL and an AI copilot, you can streamline data cleaning processes, ensuring data quality and consistency.

Example: Automating data cleaning with SQL

Step 1: Loading data


Step 2: Data cleaning with AI suggestions


AI prompt example for extra support


2. Improve code quality

Improving code quality involves optimizing SQL queries and dbt™ models to ensure they are efficient and maintainable. AI copilots can suggest enhancements that make your code more robust and performant.

Example: Code review and optimization

Step 1: Initial dbt™ model


Step 2: AI copilot optimization suggestion


AI prompt example for extra support


3. Facilitate collaboration

Encouraging team collaboration involves documenting your dbt™ models and SQL scripts to make them understandable and maintainable by all team members. AI copilots can assist in generating comprehensive documentation.

Example: Using AI to document dbt™ models automatically

Step 1: Initial dbt™ model without documentation


Step 2: AI copilot generated documentation


AI prompt example for extra support


4. Enhance efficiency metrics

Tracking productivity metrics helps in measuring the effectiveness of your workflow and identifying areas for improvement. AI copilots can assist in monitoring these metrics accurately.

Example: Tracking productivity metrics with SQL integration

Step 1: Define metrics in your SQL workflow


Step 2: AI Copilot enhanced monitoring


AI prompt example for extra support


5. Continuous learning and adaptation

Continuous learning and adaptation are critical for staying updated with the latest techniques and tools. AI copilots can assist in training and evaluating machine learning models using dbt™.

Example: Training and evaluating models

Step 1: Define and train a model


Step 2: AI copilot enhanced model training and evaluation


AI prompt example for extra support


How are you using your copilot? Tell us! We’d love to know and learn from all of out users.

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Copyright © 2025 Paradime Labs, Inc.

Made with ❤️ in San Francisco ・ London

*dbt® and dbt Core® are federally registered trademarks of dbt Labs, Inc. in the United States and various jurisdictions around the world. Paradime is not a partner of dbt Labs. All rights therein are reserved to dbt Labs. Paradime is not a product or service of or endorsed by dbt Labs, Inc.

Copyright © 2025 Paradime Labs, Inc.

Made with ❤️ in San Francisco ・ London

*dbt® and dbt Core® are federally registered trademarks of dbt Labs, Inc. in the United States and various jurisdictions around the world. Paradime is not a partner of dbt Labs. All rights therein are reserved to dbt Labs. Paradime is not a product or service of or endorsed by dbt Labs, Inc.

Copyright © 2025 Paradime Labs, Inc.

Made with ❤️ in San Francisco ・ London

*dbt® and dbt Core® are federally registered trademarks of dbt Labs, Inc. in the United States and various jurisdictions around the world. Paradime is not a partner of dbt Labs. All rights therein are reserved to dbt Labs. Paradime is not a product or service of or endorsed by dbt Labs, Inc.