EP. 004: Four Talks, One Pattern. Rehearsal Room Stories #1

"We are trying to govern a stream with a snapshot." That's a practitioner story heard in a FinOpsX rehearsal last week, and it's the line that frames this episode. Over the past two weeks the team has been sitting in on rehearsals back-to-back. Five practitioners. Five completely different topics. One pattern emerging underneath all of them. AI is now in everything, even the talks that aren't ostensibly about AI, and this episode is what that convergence actually looks like.J.R. walks through four of the rehearsals in detail. Abhinav Lad and Kuntal Patel from Palo Alto Networks on what AI cost actually behaves like up close, including the surprise that RAG memory costs as much as the LLM itself, the growth in spend from agentic AI, and why "failed request now carries a cost." Aishwarya Korde on why annual budgets break in an AI-defined era and the living-forecast discipline that replaces them. Anastassia Storozhev on persona-aligned unit economics and why cost per token, cost per agent, and cost per AI use case are all the same shape of metric. And Rohit Mishra from Avaloq on why FOCUS as the data foundation is the layer that makes every other AI cost practice possible.Five takeaways close the episode, including the action item every team should take Monday morning. FinOpsX is June 8 in San Diego. Come hear all the practitioners tell it themselves.