Du prototype à la prod : ce qu'on ne te dit pas sur la construction d'une solution IA solide
Summary
French article analyzing the journey from prototype to production for AI solutions, emphasizing that production-readiness requires engineering beyond a successful demo. It covers evaluation strategies, guardrails, observability, cost management, and three feedback loops, illustrated with concrete examples and code snippets. The piece cites tools and frameworks like Spring AI Evaluators, Langfuse, Arize Phoenix, and Neo4j GraphAcademy, and argues for a structured, measurable approach to building reliable AI systems.