What are the key considerations when choosing a tech stack for custom software development?

Tech stack selection should be driven by project requirements, not trends. Evaluation framework: performance requirements (response time, throughput, concurrent users), team expertise (existing skills reduce ramp-up time and bugs), ecosystem maturity (library availability, community support, long-term viability), scalability needs (vertical vs horizontal, read vs write heavy), and total cost of ownership (licensing, hosting, talent availability). Frontend: React for complex SPAs with large ecosystems, Next.js for SEO-critical applications with server-side rendering, Vue for progressive adoption and simpler learning curve, and SvelteKit for performance-critical applications. Backend: Node.js/TypeScript for JavaScript-native teams and real-time applications, Python/FastAPI for AI/ML-heavy applications, Go for high-concurrency microservices, and Rust for performance-critical systems. Database: PostgreSQL for general purpose with rich extensions (pgvector, PostGIS), MongoDB for schema-flexible document stores, Redis for caching and real-time features, and TimescaleDB for time-series data. Infrastructure: Supabase for rapid development with built-in auth and real-time, AWS for maximum flexibility and scale, Vercel/Cloudflare for edge-first deployment. Anti-patterns: choosing bleeding-edge tech for production systems, over-engineering for hypothetical scale, and ignoring team capabilities.