Your AI roadmap is already out of date
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An engineering leader shares a framework for setting technical direction in AI product development, where best practices shift roughly every quarter. The approach centers on three practices: sorting decisions into costly-to-reverse commitments (like architecture and interfaces) versus reversible experiments (like model choice and prompts); presenting roadmaps to leadership as explicit assumptions rather than firm conclusions so plans can be revised without losing credibility; and building the thinnest possible end-to-end slice of a feature before committing to a full architecture. Examples are drawn from a personal AI agent project involving calendar and email automation.
