All guides
Language debates are noisy because most languages can do most jobs. The useful question is which one lowers risk and cost for this workload, given the people who will maintain it.
| Language | Strongest at | Watch out for |
|---|---|---|
| Python | Data work, automation, AI and LLM tooling, quick APIs with FastAPI | Raw speed and CPU-bound concurrency; deployment needs discipline around environments |
| Go | Network services, command-line tools, infrastructure tooling, simple concurrency, single static binaries | Less expressive for complex domain models; smaller ecosystem for data science |
| Rust | Performance-critical code, memory safety, low-latency systems, WebAssembly, blockchain programs | Steeper learning curve and slower first draft; not worth it for simple CRUD |
| Node.js with TypeScript | The web layer, real-time features, sharing types with a React or Next.js front end | CPU-heavy work blocks the event loop; dependency sprawl needs management |
A sensible default stack
For most business applications, a TypeScript front end and web layer on Next.js, backed by Python (FastAPI) for data and AI work and PostgreSQL for storage, covers a very large share of needs with a hiring pool that is easy to find. Reach for Go or Rust only where a measured requirement asks for them.
When to mix languages
- A Python service that calls a Rust or Go component for a hot loop, behind a clear interface.
- Go for agents, proxies and tooling that must ship as one small binary.
- Rust for anything touching money, cryptography or untrusted input at speed.
- A shared API contract (OpenAPI or typed schemas) so services in different languages stay in step.