5 Moats That Make AI Wrappers Defensible (Without a Data Team)

If you're running an AI wrapper or automation service without real moats, you're one model update away from losing half your MRR. This episode breaks down five practical defensibility strategies nomad founders can build without a data team: distribution control, workflow lock-in, small-data capture loops, switching costs, and SLA commitments. Santi and Kira walk through real examples from TypingMind, HeadshotPro, and Superhuman, then score different wrapper archetypes using their Defensibility Scorecard. You'll get a 14-day sprint plan to add at least 20 points to your defensibility score, plus templates for HubSpot/Slack integrations and SLA snippets. The episode includes the "Lisbon Test" for reliability and addresses the counterargument about model parity making all wrappers obsolete.