Every founder asks the same question: "What tech stack should we use?" The answer is less exciting than they hope: the one that lets you ship fast and scale later.
Our Default Stack
For most SaaS products, we reach for the same tools:
Frontend: Next.js with TypeScript. Server components for performance, app router for flexibility, and the React ecosystem for everything else.
Backend: Node.js for CRUD-heavy apps, Python for AI-heavy apps. Sometimes both, with Node handling the API layer and Python running the ML pipelines.
Database: PostgreSQL for structured data (it's not even close). MongoDB when you genuinely need flexible schemas. Redis for caching, queues, and session state.
Infrastructure: Vercel for frontend, AWS for everything else. Docker for consistency. GitHub Actions for CI/CD.
When to Deviate
Break from the defaults when you have a genuine reason:
- →Real-time features? Add WebSockets via Socket.io or use Supabase Realtime
- →Mobile app? React Native for cross-platform, Swift/Kotlin for native performance
- →Heavy computation? Go or Rust for specific services, not the whole stack
- →AI-heavy? Python is non-negotiable for the ML layer
The Anti-Patterns
Don't use microservices for your MVP. A monolith is fine until you have real scaling problems. Premature decomposition creates operational complexity you don't need.
Don't chase trends. That new framework with 500 GitHub stars is not production-ready. Use boring technology that has proven itself over years.
Don't optimize early. Ship first, measure, then optimize the bottlenecks. Most performance "problems" in early-stage products are imaginary.
The best tech stack is the one your team knows, that has good documentation, and that lets you focus on your product instead of your infrastructure.
Written by
Hari — Devi AI Solutions