AI industry builder / agent workflows

Brad Zhang

Longform AI writing, forum-grade X thinking, and open-source proof for founders, operators, and early AI teams.

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Inference as a Publishing Problem

Every production model is also a publishing decision about what deserves to become visible fast.

February 2026 / 9 min read / Inference

Inference infrastructure is often described in the language of throughput and cost. Those metrics matter, but they only become meaningful when tied back to visibility: what the user sees, how quickly they see it, and what level of certainty the system is willing to attach to it.

Seen this way, serving is not just distribution of compute. It is a form of editorial prioritization. Some results deserve fast publication. Others deserve delay, review, or suppression.

Evaluation then stops being an afterthought and becomes the discipline that defines what may be published automatically at all.

Inference as a Publishing Problem