ai-native-engineering

Use when an approved system design exists and the product includes LLM, agent, retrieval, classifier, extractor, or model-driven automation components that need architectural definition before implementation. Produces capability classification, model contracts, context and memory strategy, retrieval and grounding topology, tool and action surface, agent control flow, failure taxonomy, evaluation and guardrail plans, cost and latency budgets, model routing, observability requirements, and implementation handoff notes. Do not use for generic backend service design, data pipeline design, product requirement definition, or vendor-specific SDK scaffolding; use backend-architecture, data-architecture, idea-development, or implementations/ai/<vendor> instead.