In modern software development circles, the 'Minimum Viable Product' is treated like holy scripture. Launch fast, break things, and fix them once you have users. But there is a massive difference between launching a simplified scope and launching a poorly engineered core.
When we build AI platforms, the complexity is heavily centered on low-latency state orchestration, embedding database integrations, and token pricing management. Putting a quick wrappers layer over an unoptimized database, skipping indexing, and ignoring request concurrency is not 'leaving scope for later'—it is building an architecture that will collapse under minor user testing.
At Mehrium, our engineering manual rejects the MVP. Instead, we advocate for shipping a 'SLC'—Simple, Lovable, and Complete product. A complete product includes schema safety, E2E regression pipelines, and secure payment webhooks from the first commit.
Engineering for scale on day one does not mean setting up massive multi-zone clusters or burning venture capital on large database instances. It means making correct architectural decisions that carry zero extra run cost but preserve long-term velocity.
model Tenant {
id String @id @default(uuid())
name String
slug String @unique
createdAt DateTime @default(now())
users User[]
// Enforce index on tenant mapping for sub-millisecond route resolution
@@index([slug])
}