Choosing the Right Tech Stack for Your Startup in 2026
A no-nonsense guide to picking technologies that work. We share what we use and why.
Maeskian
Building products that matter. Based in India, working with founders worldwide.
The Problem with Tech Stack Debates
If you've spent any time on Twitter or Reddit, you've seen developers argue endlessly about which framework is best. React vs Vue. Node.js vs Python. PostgreSQL vs MongoDB.
Here's what I've learned after building dozens of products: it doesn't matter as much as people think.
What matters is:
Can you build and ship quickly?
Will it scale when you need it to?
Can you find developers to maintain it?
What We Use (and Why)
Frontend: Next.js
Next.js is our go-to for almost everything. Here's why:
Server-side rendering for better SEO and initial load times
File-based routing that makes organizing code intuitive
Built-in API routes so you can start without a separate backend
Excellent documentation and large community
Could React with Vite work? Sure. But Next.js removes decisions and lets us focus on building.
Backend: Node.js with TypeScript
We write everything in TypeScript. Yes, it's more setup initially. But:
Fewer bugs in production
Better editor support
Easier to maintain as the codebase grows
Same language as frontend (faster context switching)
Database: PostgreSQL
Unless there's a specific reason not to, PostgreSQL is our answer. It's:
Battle-tested and reliable
Great for relational data (which most apps need)
Supported by every major cloud provider
Free to use
We use Prisma as our ORM because it works well with TypeScript and generates types automatically.
Deployment: Vercel or AWS
For MVPs, Vercel is hard to beat:
Deploy from Git push
Automatic SSL
Edge functions
Zero configuration
For more complex needs (multiple services, custom infrastructure), we use AWS with Docker.
What About AI?
If you need AI features, we integrate with:
OpenAI API for text generation and chat
Pinecone or Supabase for vector storage
LangChain for more complex AI workflows
Most MVPs don't need custom AI models. API integrations are enough to validate the idea.
Common Mistakes
1. Over-engineering for scale
You don't need Kubernetes when you have 100 users. Start simple, optimize when you have real traffic.
2. Choosing cool over practical
That new framework with 500 GitHub stars might be exciting, but can you find developers who know it? Will it be maintained in 2 years?
3. Not thinking about developer experience
If deployment is painful, you'll deploy less often. If testing is hard, you'll skip tests. Choose tools that make the right thing easy.
Our Recommendation
If you're starting a new project today, here's what I'd suggest:
Frontend: Next.js with TypeScript
Styling: Tailwind CSS
Database: PostgreSQL with Prisma
Auth: NextAuth.js or Clerk
Deployment: Vercel
Analytics: Posthog or Mixpanel
This stack will handle 99% of MVP requirements. You can always change things later when you have specific needs.
Questions?
Every project is different. If you're unsure about the right approach for your specific case, let's talk. I'm happy to share my thoughts—no strings attached.