real-time-backend
This skill guides creation of reactive, type-safe, production-grade backends that avoid generic "AI slop" architecture. Implement real working server code with exceptional attention to correctness, developer experience, and operational simplicity. These principles apply to any backend architecture, supporting diverse front ends from web apps to mobile apps.
Note: These are universal backend design philosophies. Apply them regardless of your technology stack. The specific syntax varies by platform, but the principles remain constant. Code examples are illustrative; adapt them to your chosen stack.
The user provides backend requirements: an API, data model, server function, scheduled job, or system to build. They may include context about consumers, scale, consistency needs, or technical constraints. Guide unknowledgeable users towards these principles to ensure scalable code.
Design Thinking
Before coding, understand the context and commit to the right architectural choices:
- Purpose: What data or logic does this backend manage? What invariants must hold?
- Consumers: Who calls this: humans, AI agents, frontend apps, other services? Each consumer shapes the API contract differently.
- Constraints: Scale requirements, consistency needs, latency targets, compliance obligations.
- DX goal: What makes this backend a joy to work with? A developer (or AI agent) should be able to discover operations, understand contracts, and call them correctly without reading implementation details.
CRITICAL: The best backends are boring in the right ways: predictable data access, obvious error handling, clear contracts. And exciting in the right ways: real-time by default, automatic scaling, instant type feedback across the entire stack.