Field notes for leaders connecting MarTech, data, AI, product, and engineering inside the constraints of a real enterprise.
Read the field notesEach article starts with a production tension, makes the architecture or operating decision visible, and leaves the reader with a usable frame.
Before adding a platform or an AI model, make one customer decision inspectable: its purpose, inputs, permissions, owner, measurement, and fallback.
A working demo is a starting point. Production readiness requires a bounded task, representative evaluation, controlled access, operational ownership, and a tested way to stop.
Read articleAI can accelerate a marketing system, but it cannot resolve unclear ownership, disconnected decisions, weak measurement, or an architecture nobody can explain.
Read articleA useful prototype proves that a model can contribute. A production system must prove that the whole workflow can be observed, evaluated, controlled, and owned.
Read articleWhen definitions, instrumentation, identity, experiments, and reporting are designed separately, performance debates become data debates.
Read articleModularity creates options. Without contracts, ownership, observability, and release discipline, it can also multiply seams and slow the enterprise down.
Read articleBring the system you are trying to make legible. We will begin with the decision and the evidence around it.
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