Hey everybody, Chris St John here, senior architect and developer, bringing you some AI tips. Today, we’ll be exploring how to convert natural language into basic database queries using Chat GBT and AI. In just minutes, you’ll learn how to leverage AI tooling techniques to improve developer productivity.
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In this video, we’ll start by recapping what we’ve covered in previous videos, specifically how to obtain a schema from Chat GBT. Then, we’ll walk through various product scenarios and demonstrate how to create prompts and generate output using ChatGPT. We’ll then take these queries and try them out in a database.
Next, we’ll delve deeper into the scenarios, providing more detailed examples and tips for improvement. Throughout the video, we’ll be using the pg-sql.com tool to execute the queries and validate the results.
But first, let’s take a moment to introduce AI Dev Tips, a new tutorial series aimed at maximizing developer talent and minimizing tedious tasks. By utilizing Chat GBT and other AI tooling techniques, developers can streamline their workflow and boost productivity.
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Now, let’s recap what we’ve covered in previous videos. We started by developing a schema using ChatGPT, which provided us with a set of create table statements. We then used the pg-sql.com tool to execute these statements and create a fake dataset for testing.
Moving on to the product scenarios, we were presented with various queries, such as retrieving a complete list of registered users, finding available products priced below a certain amount, and retrieving all orders made by specific users. We input these scenarios into Chat GBT and generated select statements for each one.
To validate these queries, we executed them in our database using pg-sql.com. We also explored additional features, like grouping orders by user ID, to gain more insights from the data.
Finally, we shared some last-minute tips and improvements. We learned that scenarios can be entered one by one or together, but it’s important to keep them concise to ensure Chat GBT can process them effectively. Additionally, involving product managers, product owners, or UX teammates in writing Gherkin scenarios can speed up the development process.
That’s it for this video! Thank you for watching, and don’t forget to like, subscribe, and share. And remember to check out instantiate.io for a wide range of AI-driven tools to help bring your startup ideas to life. Sign up for free today!
