The Principle Every RevOps Team Skips
Most companies buy a tool, connect it to their CRM, and ask it to do something vague. That's not a system — it's a procurement decision dressed up as a strategy.
Jordan Crawford's framework in All AI in Go-To-Market Is Just This collapses the entire GTM-AI landscape into a single constraint: imagination. If you can articulate the most valuable message for a specific customer situation, you can engineer a system to deliver it at scale. If you can't, no stack will save you.
This is not a motivational reframe. It's a diagnostic. The reason most AI GTM initiatives stall isn't data quality or model capability — it's that no one has written the message worth sending. The system is waiting on human judgment that was never supplied.
What the Flip Means for Operators
Traditional RevOps runs reactive: sales requests a sequence, ops builds it, marketing supplies assets. The whole motion is downstream of someone else's intuition.
Crawford's frame reverses the sequence. You start with the desired outcome — the exact message you'd pay to receive if you were the buyer — and reverse-engineer backward: what data do you need to identify this situation? What signals make it timely? What infrastructure delivers the message without a human touching it each time?
That sequence — outcome → data requirements → automation layer — is the entire system design. The playbook becomes the competitive moat, not the tool. Tools are commoditized in months. A precisely articulated customer situation with matching data infrastructure takes real work to replicate.
The One Action This Week
Crawford offers a concrete exercise, and it's worth taking literally:
- Pick one high-specificity customer situation. Not