Summary

Joe Reis argues that data modeling is experiencing a renaissance not because its fundamentals have changed, but because the world around the model has — technology convergence, AI agents, and falling implementation costs are dissolving the old specialization silos. His 'Mixed Model Arts' manifesto proposes a pragmatic, multi-disciplinary approach borrowing from all modeling traditions, analogous to how mixed martial arts superseded single-style dogma. As AI agents require explicit semantics to function and implementation becomes cheap, the judgment-intensive work of defining entities, grain, and meaning becomes more critical, not less.

Key Insight

AI agents are exposing the hidden cost of neglected semantics, and as implementation becomes cheap, data modeling judgment — not execution — becomes the scarcest and most valuable resource in the stack.

Spicy Quotes (click to share)

• 8

  Technologies became methodologies. Methodologies became camps, and camps became identities. In some cases, identities became cults.

• 5

  As implementation costs fall, modeling becomes more important, not less. The scarce resource shifts from production to judgment, and the question moves from 'Can we build this?' to 'What exactly should we build?'

• 4

  Agents don't just need access to data. They need enough context to understand what the data represents, how concepts relate, when facts are true, what actions are permitted, and what the organization means by the words it uses.

• 7

  We aren't rediscovering semantics; we're discovering the cost of not having them, which is essentially a data modeling problem.

• 4

  For most of computing history, humans were the ultimate semantic integration layer.

Tone

visionary, manifesto-driven, analytical