Topic

AI Strategy
Articles and playbooks.

Every Zrevick article tagged AI Strategy — how founders turn AI-built products into companies that sell, market and support at scale.

Most AI strategy advice starts with the technology and works backward to a problem nobody has. These articles work the other way around: start from where the business loses time or revenue, then decide whether AI — and which shape of it — actually moves that number. You will find the framework for choosing where AI pays off first, the sequencing that turns early wins into compounding ones, and the honest accounting of what AI makes cheaper without making it better. The guides are deliberately short on hype and long on order of operations: which tasks go to agents first, which stay human permanently, and how to tell the difference before the budget is spent. Each one ends with a measurement plan, because an AI initiative that cannot name its metric is a hobby, not a strategy. Start with the pay-off-first guide before your next tool purchase, then use its task framework to build your automation queue one role at a time. Revisit the queue every quarter: the frontier of what agents handle well moves, and last quarter's impossible task is often this quarter's Tuesday job. Strategy is not a stack of tools — it is the order in which you apply them, and the discipline to stop when a workflow stops paying for itself.

Every article in this section is written for the same reader: a technical founder running sales, marketing and support with a team of one to ten, usually while Claude Code or Codex ships the product. New guides are filed under their topic as they publish, so this page grows rather than ages. If you are mid-decision, start with the most recent article; if you are new to the topic, start with the overview and work forward. Skim the summaries first, then commit to the pieces that match the workflow you are fixing this quarter.