Day-90 is where vertical SMB agents die - context drift, not model quality. How are you handling it?

Building voice/booking agents for SMB verticals (home services, grooming, salons, that kind of thing) and the pattern I keep hitting isn’t a launch problem, it’s a survival problem. Agent demos great, works week one, then quietly degrades until the client churns. Almost never because the model got worse. The real killer is context drift. The business changes underneath the agent: hours shift, pricing updates, “we don’t service that area anymore,” a service gets dropped, a regular’s preferences change. The model is still fine. The context is stale. And the moment the agent confidently states something that’s no longer true, trust is gone. What I’ve landed on so far: Context isn’t a setup task, it’s a sync problem. If keeping the agent current requires the owner to manually re-prompt or update it, you’ve just built them an intern they have to babysit. The deployments that survive pull context from a system the business already updates anyway (scheduling tool, CRM, POS) so freshness is automatic. “What it should never guess” matters as much as what it knows. An agent that says “let me confirm and get back to you” on an edge case beats one that invents an answer. Owners forgive “I don’t know” far more than a wrong booking. Single high-value loop beats breadth. Agents that try to do everything drift in more places. Nailing one countable workflow (e.g. capturing missed calls into booked jobs) keeps the surface area small enough to stay correct. Questions for people running agents in production: • How do you keep agent context in sync with a business that changes daily, without constant manual updates? • Where do you draw the human-review line, and do you loosen it over time as trust builds? • What’s your biggest single cause of post-launch degradation?