While debates rage about model capabilities, a quieter battle determines AI’s practical value: the context layer. This infrastructure—sitting between raw data and AI models—determines whether AI outputs are generically impressive or specifically useful.
The context layer manages what AI knows about users, situations, and history. It handles retrieval, relevance ranking, privacy controls, and real-time updates. Without it, AI models operate blind to the specifics that make outputs valuable.
Consider the difference: “Write an email” produces generic output. “Write an email to my colleague Sarah about the budget meeting, knowing our previous discussions and her communication preferences” produces something useful. The gap is context.
The context layer is becoming as important as the model layer. This represents a fundamental shift in AI architecture—from model-centric to context-centric systems.
The Emerging Stack
AI stacks are evolving: compute infrastructure at the bottom, models in the middle, and context layers on top. Companies controlling context layers will capture disproportionate value as models commoditize.
Gennaro is the creator of FourWeekMBA, which reached about four million business people, comprising C-level executives, investors, analysts, product managers, and aspiring digital entrepreneurs in 2022 alone | He is also Director of Sales for a high-tech scaleup in the AI Industry | In 2012, Gennaro earned an International MBA with emphasis on Corporate Finance and Business Strategy.
