Building AI Products That Earn Their Keep

Most AI products die in the pilot. They demo beautifully, the champion is excited, and then nothing changes in the customer's P&L. Building Sally AI taught me that the difference between a demo and a business is whether the product replaces a cost line someone is already paying.

Start from the staffing gap, not the model. Sally exists because businesses cannot hire enough people to answer every call, chase every lead and follow up on every quote. That is a measurable, painful, budgeted problem. The model is an implementation detail; the promise is coverage.

Design for the failure case first. An AI teammate that handles ninety percent of conversations and hands the rest to a human cleanly is far more valuable than one that attempts everything and fails silently. Escalation is a feature, not an admission of weakness.

Instrument everything a buyer will be asked to defend. Resolution rate, time to first response, cost per conversation, revenue influenced. If your customer's boss asks why they pay you, the answer should already be on a dashboard.

Finally: charge like software, deploy like a service. The first fifty customers of any applied AI product need hands-on onboarding. That is not unscalable — that is how you learn what to automate next.