Hype vs help: an entrepreneur's filter for AI tools

The hype cycle is optimized for founders with FOMO. Social proof ('10 million users!') substitutes for evidence. Feature demos show best-case outputs, not your messy inputs. VC-backed pricing masks true cost. Without a filter, you accumulate subscriptions that fragment workflows and complicate governance.

Question one: What specific outcome does this improve, measurable in two weeks? If the vendor can't articulate outcomes — only features — pass. Question two: What data does it require, and where is it processed? META founders need clear answers on residency and subprocessors, not hand-waving about 'enterprise plans.'

Question three: Does it integrate with how we already work, or demand a parallel process? Tools that require copy-paste marathons create shadow workflows. Question four: What happens when it's wrong? Look for editability, audit trails, and human override — not magic-box black boxes on high-stakes tasks.

Question five: Can we exit in thirty days without losing critical data or disrupting customers? Adaptation favors reversible commitments. Long contracts for unproven tools are anti-adaptive.

Keep a shared 'tool decision log' — date, evaluator, scores on the five questions, decision, review date. Six months of disciplined filtering beats a sprawling AI stack that nobody owns. When a tool passes all five, pilot in one team before company-wide rollout.