Give Your On-Call Its Own AI Teammate - Swaapnika Motapothula, Chinmay Gandhi & Vlad Tsvang, Meta

Twelve alerts fire at 2 a.m., and a useful assistant can still leave the engineer coordinating every step. Meta's on call team uses that illustrative scenario to explain a different design: one AI teammate per rotation, with shared context, its own identity, persistent memory and explicit limits on what it can do. Swaapnika Motapothula, Chinmay Gandhi and Vlad Tsvang describe a system that connects alerts, tickets, incident history and code changes instead of leaving each automation with its own isolated view. The goal is to bring a human a decision with supporting evidence and a proposed action. Their autonomy ladder starts with investigation, advances to drafting fixes for approval, and permits selected lower criticality work only when mistakes are cheap to detect and the agent has earned trust on that action. Critical production decisions stay with people, and code changes still go through normal review and continuous integration. The team explains the automation loops for triage, recovery from stuck runs, and shift handoffs, plus how team specific skills and memory carry expertise between engineers. Corrections reopen work and become new evidence, while memory entries can be promoted or retired. The examples show the intended experience rather than a measured time savings result: the speakers explicitly reserve that claim for a rigorous study. Their next steps focus on accepted mitigations, better feedback and earning further autonomy. Speaker info: Swaapnika Motapothula, Meta - https://www.linkedin.com/in/swaapnika-motapothula Chinmay Gandhi, Meta - https://www.linkedin.com/in/cvgandhi Vlad Tsvang, Meta - https://tsvang.com/ Timestamps: 0:00 - From faster coding to production operations 1:21 - An illustrative 2 a.m. incident 3:18 - One AI teammate per rotation 5:08 - The three levels of autonomy 7:15 - A smaller human decision queue 9:31 - Triage, recovery and handoff automation 11:44 - Shared identity and memory across shifts 13:24 - Feedback, customization and team adoption 14:11 - What changed and what still needs measurement