AI-Assisted Database Design

In this lesson, you'll learn how to turn ER diagram concepts into actual PostgreSQL table schemas with the help of ChatGPT. You'll get familiar with the importance of ensuring data integrity and learn how to effectively validate and test the AI-generated SQL code.

This lesson teaches you how to create safe database migrations using the AI assistant Cursor. You'll learn what a migration is, how to write an effective prompt, and how to verify and deploy changes without data loss or production downtime.

This lesson covers the concept of Row Level Security (RLS) in PostgreSQL and Supabase, its importance for client-side applications, and how to use AI to generate RLS policies. You'll also learn how to validate AI-created policies and detect security gaps.

In this lesson, you'll learn how to use ChatGPT to generate seed data for a database. You'll learn what seed data is, why it matters for testing, and how to create diverse, deterministic, and repeatable SQL scripts that include realistic edge cases.

In this lesson, you'll learn how to use Claude AI to build complex JOIN queries that return aggregated data views, such as dashboards. We'll discuss methods for writing effective prompts for AI, avoiding common mistakes, and validating the resulting SQL code.

In this lesson, you'll learn how to use a database view to simplify complex JOIN queries and optimize data access in an application. With AI's help, you'll create views, learn about their security aspects, their interaction with RLS, and best practices for managing them in a production environment.

In this lesson, you'll learn how to synchronize a Drizzle ORM schema with the actual state of the database using SQL migrations. We'll discuss the concept of 'schema drift' and how the AI tool Cursor can help identify and fix this problem, in order to prevent runtime errors and ensure the application's data integrity.

In this lesson, you'll learn how to use AI to review the relations in a Prisma schema. We'll discuss common mistakes in `onDelete` behavior, optional relations, and composite unique constraints, in order to ensure the Prisma model fully matches the actual behavior of the PostgreSQL database.

This lesson covers how to plan an effective indexing strategy for PostgreSQL databases using ChatGPT. We'll discuss identifying query patterns, the pros and cons of indexing, and creating a production-safe indexing strategy with AI's help.

In this lesson, you'll learn to analyze PostgreSQL's EXPLAIN plan to understand how your queries are executed. We'll discuss how AI (specifically Claude) can simplify this process and help you optimize database performance.

This lesson covers the concept of data backfill, its risks, and how to use the AI tool Cursor to create production-safe backfill scripts. You'll learn how to write, verify, and confirm backfill scripts that are restartable and idempotent.

In this lesson, you'll learn how to design an Audit Log table using ChatGPT. You'll get familiar with the purpose of an audit log, the key design decisions behind it, implementation strategies, and its security implications.

This lesson covers how to use AI (specifically Claude) to convert a PostgreSQL schema into a SQLite prototype. We'll explore SQLite's specific characteristics, differences in the type system, and the requirements you need to keep in mind when working with AI to ensure the data model remains portable and functional.

In this lesson, you'll learn how to use AI to build a production-reliable database backup and restore checklist in a Supabase/PostgreSQL environment. You'll learn about the critical importance not only of storing data, but of successfully restoring it.

This lesson shows you how to use AI tools, specifically Cursor, to create a comprehensive database review report. You'll learn how to combine the various artifacts created throughout the course into a single, actionable document that assesses database readiness and identifies potential risks.