When AI Breaks in Production
What happens when your AI product fails in front of real users, and how you rebuild trust.
VibeFlow is an AI-powered music collaboration platform backed by Y Combinator. Founded in 2024, they're building the future of real-time creative tools for musicians.
The demo worked perfectly. The first ten users were impressed. Then user eleven hit a case the model had never seen — and everything fell apart in front of a paying customer.
In this episode, the team from VibeFlow (YC S24) breaks down exactly what happened when their AI music collaboration tool started hallucinating chord progressions on live sessions. They talk through the incident response, the humbling conversation with their first enterprise customer, and the architectural changes that followed.
Key themes: AI reliability in production, incident response without a playbook, customer trust after failure, and building guardrails that don't kill the product.
- Ship an AI kill switch before you ship the AI. A hard fallback to deterministic behavior saved VibeFlow from a complete enterprise churn.
- Your incident response process is only as good as your monitoring. They had no observability into what the model was actually returning — and found out from a customer.
- Transparency beats spin. The customer who stayed did so because the founders called immediately and explained exactly what went wrong, not what they wished had happened.
- Production is a different distribution than your eval set. Every founder who ships AI learns this. The question is whether you learn it before or after a customer does.
Ready to listen?
Find Founders in Motion on your platform of choice.