Welcome, Type Theorist 🔨

You just made one of the best investments in your engineering career. This workshop will fundamentally change how you think about data modeling.

What You'll Walk Away With

• A Haskell-informed mental model for designing Prisma schemas that catch bugs at compile time instead of production

• Branded types, phantom types, and smart constructors — patterns that eliminate entire categories of runtime errors

• Two production-ready case studies (e-commerce + multi-tenant SaaS) you can adapt immediately

• A certificate of completion to add to your portfolio

How This Workshop Works

1. Go through the lessons in order. Each one builds on the last. Sequential completion is required.

2. Do the exercises. Reading about types is not the same as implementing them.

3. Post in Workshop Discussion. Share solutions, ask questions, debate approaches.

4. Take your time. Deeply understanding one pattern is worth more than skimming ten.

Your First Action

Open Chapter 1, Lesson 1: "Why Types Matter" and start reading. By the end of that first lesson, you'll already see your Prisma schemas differently.

See you in the discussion. Let's forge some types. ⚒️

Your Prisma schema compiles. Your migrations run. Your queries return data.

And somewhere in production, a user just received a SHIPPED order with a null tracking number. A payment processed against the wrong account. An admin accidentally queried across tenant boundaries.

The schema didn't prevent any of it.

The Problem: Schemas Describe Structure, Not Rules

Prisma tells the database what shape your data has. It says nothing about what states are valid.

The Fix: Think Like a Haskell Developer

Haskell's type system doesn't just describe data — it constrains it. Invalid states are literally unrepresentable. You can bring this exact thinking to Prisma + TypeScript using branded types, phantom types, and smart constructors.

Three Patterns That Change Everything

1. Branded Types — prevent mixing up UserId and AccountId even though both are strings

2. Phantom Types — encode state machines at the type level so invalid transitions don't compile

3. Smart Constructors — guarantee every value in your system has been validated by construction

These aren't academic exercises. They're production patterns used at companies processing millions of transactions.

If a business rule can be expressed as a type constraint, it should be. Runtime validation is a fallback, not a strategy.

I teach all three patterns — with full Prisma integration, real-world case studies, and hands-on exercises — in the Prisma ORM × Haskell Types Workshop. No prior Haskell experience required.

Your Prisma schema compiles. Your migrations run. Your queries return data.

And somewhere in production, a user just received a SHIPPED order with a null tracking number. A payment processed against the wrong account. An admin accidentally queried across tenant boundaries.

The schema didn't prevent any of it.

The Problem: Schemas Describe Structure, Not Rules

model Order {
  id             String  @id
  status         String  // "pending"? "PENDING"? "shipped"? anything goes
  trackingNumber String? // null when shipped? data bug waiting to happen
}

Prisma tells the database what shape your data has. It says nothing about what states are valid.

The Fix: Think Like a Haskell Developer

Haskell's type system doesn't just describe data — it constrains it. Invalid states are literally unrepresentable:

data OrderStatus
  = Pending
  | Shipped { trackingNumber :: Text }  -- can't be Shipped without tracking
  | Delivered { deliveredAt :: UTCTime }

You can bring this exact thinking to Prisma + TypeScript:

type ValidOrder =
  | { status: 'PENDING' }
  | { status: 'SHIPPED'; trackingNumber: string }  // required, not optional
  | { status: 'DELIVERED'; deliveredAt: Date }

Three Patterns That Change Everything

1. Branded Types — prevent mixing up UserId and AccountId even though both are strings

2. Phantom Types — encode state machines at the type level so invalid transitions don't compile

3. Smart Constructors — guarantee every value in your system has been validated by construction

These aren't academic exercises. They're production patterns used at companies processing millions of transactions.

The Bottom Line

If a business rule can be expressed as a type constraint, it should be. Runtime validation is a fallback, not a strategy.

I teach all three patterns — with full Prisma integration, real-world case studies, and hands-on exercises — in the Prisma ORM × Haskell Types Workshop. No prior Haskell experience required.

Your Prisma schema compiles. Your migrations run. Your queries return data.

And somewhere in production, a user just received a SHIPPED order with a null tracking number. A payment processed against the wrong account. An admin accidentally queried across tenant boundaries.

The schema didn't prevent any of it.

The Problem: Schemas Describe Structure, Not Rules

model Order {
  id             String  @id
  status         String  // "pending"? "PENDING"? "shipped"? anything goes
  trackingNumber String? // null when shipped? that's a data bug waiting to happen
}

Prisma tells the database what shape your data has. It says nothing about what states are valid.

The Fix: Think Like a Haskell Developer

Haskell's type system doesn't just describe data — it constrains it. Invalid states are literally unrepresentable:

data OrderStatus
  = Pending
  | Shipped { trackingNumber :: Text }  -- can't be Shipped without tracking
  | Delivered { deliveredAt :: UTCTime }

You can bring this exact thinking to Prisma + TypeScript:

type ValidOrder =
  | { status: 'PENDING' }
  | { status: 'SHIPPED'; trackingNumber: string }  // required, not optional
  | { status: 'DELIVERED'; deliveredAt: Date }

// This function literally cannot return a Shipped order without tracking
function parseOrder(raw: PrismaOrder): ValidOrder { ... }

Three Patterns That Change Everything

1. Branded Types — prevent mixing up UserId and AccountId even though both are strings

2. Phantom Types — encode state machines at the type level so invalid transitions don't compile

3. Smart Constructors — guarantee every value in your system has been validated by construction

These aren't academic exercises. They're production patterns used at companies processing millions of transactions.

The Bottom Line

If a business rule can be expressed as a type constraint, it should be. Runtime validation is a fallback, not a strategy.

I teach all three patterns — with full Prisma integration, real-world case studies, and hands-on exercises — in the Prisma ORM × Haskell Types Workshop.

No prior Haskell experience required. Just a willingness to think differently about your schemas.