A tech stack isn’t a religious choice — it’s a delivery decision. The stack you pick determines how fast you ship, how many bugs reach production, and how cheaply the next engineer can pick up the code. We build most products on an end-to-end TypeScript stack, and it’s a deliberate choice for client outcomes, not developer fashion. Here’s what we use and why each piece earns its place.
One language, end to end
The foundation is TypeScript everywhere — database layer, API, and frontend. A single language across the whole stack means one set of skills, shared code and types between client and server, and no costly context-switching between, say, a Python backend and a JavaScript frontend.
The bigger win is type safety that flows from the database to the UI. When the shape of your data is defined once and enforced all the way to the button that displays it, a whole category of bugs — the “the API returned a field the frontend didn’t expect” class — simply can’t happen. That’s fewer production incidents and faster, safer refactors as the product grows.
The pieces
- Runtime & tooling: Bun. A fast all-in-one runtime and toolchain. Quicker installs, test runs, and builds mean a tighter feedback loop — which compounds across a whole project into real delivery speed.
- Frontend: Nuxt (Vue) or Next.js (React). Both are mature, server-rendering frameworks with excellent performance and SEO out of the box. We pick per project — Vue/Nuxt or React/Next — based on the team and the product, not dogma.
- API: tRPC. End-to-end typed APIs with no code generation and no hand-written client. The frontend calls the backend like a local function, fully typed. We go deeper in Type-Safe APIs with tRPC and Drizzle.
- Database: Drizzle ORM + PostgreSQL. A typed query layer over the most capable open-source database. Your schema is TypeScript, your queries are checked at compile time, and Postgres handles far more scale than most products ever need — including vector search with pgvector for AI features.
- Validation: Zod. One schema definition that validates input at the edge and produces types used everywhere else.
Why this ships faster
The theme across every choice is catching mistakes at compile time instead of in production, and sharing one definition instead of maintaining several. Concretely, that means:
- A change to the database schema surfaces as a type error in the exact frontend components that need updating — before anything ships.
- New engineers onboard faster because the types document the system and the same language runs everywhere.
- Refactoring is safe, so the codebase stays healthy instead of ossifying — which keeps future features cheap, not just the first one.
For a client, that translates into the things that actually matter: fewer bugs, faster iterations, and a codebase that’s cheap to maintain and hand over.
When we’d choose differently
No stack is universal. Heavy data-engineering or scientific-computing workloads, an existing team with deep expertise elsewhere, or a hard requirement for a specific ecosystem can all point another way — and we’re stack-agnostic enough to extend what you already have. But for building new web products and SaaS from scratch, end-to-end TypeScript is, in our experience, the fastest reliable path from idea to production.
If you’re choosing a stack for a new build — or wondering whether your current one is slowing you down — we’re happy to talk through the trade-offs for your specific product.
