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Tech Stack Recommender

Tell us about your product and get a recommended tech stack — frontend, backend, database, hosting, and AI tools — with reasoning for each choice.

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What are you building?

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How We Choose Your Stack

We evaluate five factors: product type (SaaS needs SSR for SEO, mobile needs cross-platform), expected scale (100 users vs 100K users require different database strategies), budget (managed services vs self-hosted trade cost for complexity), team skills (the best stack is the one you ship fastest with), and AI requirements (Python ecosystem is non-negotiable for ML workloads).

Ship Speed

We prioritize frameworks with large ecosystems, extensive documentation, and pre-built components. Time-to-market matters more than theoretical performance for MVPs.

Scalability Path

The recommended stack handles 10x your expected load without rearchitecting. We don't over-engineer for scale, but we ensure you won't hit a wall at 10K users.

Hiring & Community

Exotic tech stacks make hiring hard. We favor technologies with large developer communities, active maintenance, and strong job markets.

Common Stack Mistakes to Avoid

Premature Microservices

Splitting into microservices before you have product-market fit adds 3-5x deployment complexity for zero user benefit. Start monolith, split later when you have a clear reason (different scaling needs, separate team ownership).

Chasing New Frameworks

That new JavaScript framework with 2K GitHub stars isn't production-ready. Stick with frameworks that have been battle-tested for 3+ years, have corporate backing, and 50K+ Stack Overflow answers. Innovation in your product, not your toolchain.

Over-investing in Infrastructure

Kubernetes, Terraform, and multi-region deployments are overkill for MVPs. Use managed platforms (Vercel, Railway, Supabase) that handle infrastructure so you focus on product. You can migrate to custom infrastructure when you have 100K+ users and a DevOps hire.

Frequently Asked Questions

How do you decide which tech stack to recommend?+
We match your product type, expected scale, budget, team skills, and AI needs against a matrix of proven technology combinations. The recommendations prioritize: developer productivity (ship fast), ecosystem maturity (fewer bugs), scalability (grow without rewriting), and hiring ease (find developers). We don't recommend bleeding-edge tech for MVPs — proven and boring wins.
Should I always follow the recommended stack?+
Use it as a starting point, not gospel. If your team has deep expertise in a different framework that covers the same needs, go with what you know. The best tech stack is the one your team ships fastest with. Our recommendations optimize for the common case — your specific situation may warrant exceptions.
Why do you recommend Next.js so often?+
Next.js handles 80% of web product needs out of the box: server-side rendering (SEO), API routes (backend), static generation (performance), and React (ecosystem). It eliminates the need to choose separate frontend/backend frameworks for most MVPs. When you need separate services (Python for AI, Go for performance), we recommend splitting — but for most products, Next.js is the pragmatic choice.
What about no-code or low-code platforms?+
We don't recommend them for products you intend to scale. They're great for internal tools and prototypes, but create significant technical debt when you outgrow them. If you're validating an idea, a Typeform + Zapier + Airtable combo costs $0 and ships in a day. If you're building a real product, invest in code from the start.
How much does the tech stack affect development cost?+
The stack itself has minimal cost impact — most modern frameworks are free and open source. What matters is developer productivity: a team experienced in React + Node.js ships 2-3x faster than the same team learning a new framework. Exotic stacks also increase hiring costs and reduce your talent pool. Boring tech = cheaper development.
When should I use a microservices architecture?+
Almost never for an MVP. Start with a monolith (single codebase). Microservices add complexity in deployment, debugging, and data consistency that's not justified until you have 10+ developers and millions of users. The vast majority of startups never need microservices. You can always split later — you can't easily merge later.
What database should I choose — SQL or NoSQL?+
PostgreSQL (SQL) for 90% of products. It handles relational data, JSON documents, full-text search, and geospatial queries in one database. Use MongoDB only if your data is genuinely unstructured and schema-less. Use Redis for caching and real-time features. Use a vector database (Pinecone, pgvector) only if you're building RAG or semantic search.
Can HouseofMVPs build with my recommended stack?+
Yes. Our core stack (Next.js, PostgreSQL, Tailwind, Hono) covers most recommendations. For AI products, we add Python services. For mobile, React Native. For enterprise, we can work with your existing infrastructure. Book a scope review to discuss your specific requirements.

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