Prisma ORM

You write one `schema.prisma` file. Prisma generates a TypeScript client whose types match exactly. Renaming a column is safe because everything that touches it fails to compile.

// schema.prisma datasource db { provider = "postgresql" url = env("DATABASE_URL") } generator client { provider = "prisma-client-js" } model User { id String @id @default(cuid()) email String @unique createdAt DateTime @default(now()) posts Post[] } model Post { id String @id @default(cuid()) title String body String author User @relation(fields: [authorId], references: [id]) authorId String }

import { PrismaClient } from "@prisma/client"; const prisma = new PrismaClient(); export async function createPost(authorEmail: string, title: string, body: string) { try { return await prisma.post.create({ data: { title, body, author: { connect: { email: authorEmail } }, }, include: { author: true }, }); } catch (e) { console.error("createPost failed", e); throw e; } } export async function recentPosts() { return prisma.post.findMany({ orderBy: { id: "desc" }, take: 20, include: { author: { select: { email: true } } }, }); }

Understanding "Prisma ORM" in practice: AI-assisted coding shifts work from syntax recall to design thinking — models handle boilerplate so you focus on architecture. Prisma gives TypeScript a type-safe database client generated from your schema. Model once, get autocomplete everywhere — and knowing how to apply this gives you a concrete advantage.

• Apply schema in your ai-coding workflow to get better results
• Apply migration in your ai-coding workflow to get better results
• Apply client in your ai-coding workflow to get better results
• Apply relation in your ai-coding workflow to get better results

1. 1Use AI to generate unit tests for an existing function
2. 2Ask AI to refactor a messy function and explain the changes
3. 3Have AI suggest a code review for a recent pull request

The big idea: schema is truth, the client is type-safe, and a good ORM makes wrong queries fail at compile time.