The mistake

Most AI adoption starts too late in the process. Teams ask, “What should we prompt?” before asking, “What kind of work is this?” That creates impressive drafts but fragile operating models.

A better starting point is allocation: what must remain human-owned, what should be handled by deterministic tools, and where AI can usefully support synthesis, framing, and translation.

Human

Humans own judgment, stakes, ethics, stakeholder context, and final recommendations. AI can surface options, but accountability should not be outsourced to a model.

Tool

Deterministic systems should handle repeatable operations: calculations, joins, validation checks, retrieval, formatting, and scheduled alerts. If the answer should be identical every time, do not make it probabilistic.

AI

AI earns its place when the task involves synthesis: turning messy source material into candidate narratives, finding gaps, translating technical analysis into business language, or pressure-testing a recommendation.

The rule

Automate the repeatable parts, assist the interpretive parts, and keep accountability human.

That is workflow design. Prompt engineering is just one small part of it.