In Breaking Analysis 322, we shared with you that our forecast of a $1T silicon business arrived 2 years earlier than we had forecast. The reason for our twenty-four month miss was the bottleneck had moved from GPUs to memory. Micron gave us a remarkable datapoint in its FY Q3: DRAM prices rose by more than sixty percent sequentially in the quarter, while the number of bits shipped barely grew. Today we address what that means. The key questions are: Is this temporary scarcity or a structural change in the economics of memory? We believe both forces are at work. This week we participated in a Webcast with Micron President and Chief Technology and Products Officer, Scott DeBoer. The roadmap he showed us underscores the importance of memory with respect to AI performance. New customer take or pay agreements change how risk is shared. At the same time, customers are being forced to adapt to higher costs. Qualitate’s proprietary research gives us a window into those decisions. Our question is whether these changes can make memory less cyclical, and what evidence would tell us that the familiar cycle is returning.

ServiceNow is making one of the more consequential and visible bets in enterprise AI. The company says AI Control Tower can discover and govern any agent, work across models and clouds, track cost and value, and shut down behavior that violates policy.

That sales pitch plays directly to ServiceNow's greatest asset – its installed base. ITSM, CMDB, risk workflows, security operations and years of operating context give the company a distribution and data advantage most AI governance vendors do not have.

Our research suggests that moat is real. But proprietary customer data shows a more nuanced picture. Control Tower is already strong as a governance workflow and system of action. It can inventory AI assets, connect risks to owners, route approvals and remediation, and preserve an audit trail.

What the field has not broadly validated is the claim that Control Tower is a complete technical governance and runtime enforcement plane across the heterogeneous enterprise.

In this week’s episode, we explore the AI control gap and the starting point for addressing AI safety, namely alignment. We question prevailing narratives and propose a public policy regime that has more teeth than what has been put forth thus far.