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AI Paradigm Shifts

We outline three major AI paradigm shifts facing the vertical software industry: user experience, economics, and autonomy, emphasizing that companies must pursue a multi-vector strategy rather than a single large project. Regarding user experience, interfaces are transitioning from explicit chat windows to invisible, ambient systems that use a Model Context Protocol (MCP) to access data. Economically, the source stresses that seat-based pricing models are failing due to AI-driven productivity gains, necessitating a shift to hybrid or usage-based pricing models that account for variable computational costs (token economics). Strategically, companies must build a defensible "middle layer" based on proprietary data and domain expertise, shielded by the MCP, while deploying a portfolio of AI agents with multiple autonomy levels (L0 to L6); furthermore, internal deployment must precede external customer-facing rollouts to build expertise and de-risk the technology.