The AI Stack You've Been Building All Along

Engineers have spent the last two years building production-grade AI systems using established engineering practices—prompt management, input normalization, output contracts—but without formal vocabulary to describe the layer they've created. As with JAMstack and Serverless before it, the naming of the AI stack matters not because it creates new work, but because it legitimizes existing practices and gives organizations permission to treat it as real infrastructure. This recognition unlocks proper hiring, tooling, and architectural design, transforming ad-hoc LLM implementations into intentional engineering.