We are entering an era where your dashboard might lie to you. As AI agents become standard, they start handling the repetitive, high-frequency tasks that used to define your active user base. When you see a spike in event volume, it is easy to assume your product is becoming more essential to your human users. In reality, you might just be witnessing a surge in automated API calls that mask a quiet withdrawal of human engagement.
This matters because human engagement is the primary driver of long-term product loyalty and expansion revenue. If you optimize your roadmap based on raw event counts, you risk building a product that serves machines perfectly while losing the emotional and strategic connection with the people who actually sign the checks. You need to distinguish between human-initiated workflows and agent-executed tasks to understand where your true value resides.
Industry case01
The Phantom Growth Mirage
Fintech · CPO
A major expense management platform saw a 40 percent increase in transaction categorization events. The team initially celebrated this as a massive win for user engagement. Upon closer inspection, they realized 90 percent of these actions were triggered by a new AI auto-categorization agent, while manual user logins to the dashboard had dropped by 15 percent.
Takeaway: Always segment your event streams by actor type to ensure you are measuring human value, not just machine throughput.
Executive perspective02
Reframing the North Star
SaaS Productivity · CxO
As a leader, you must shift your focus from total active users to human-intent-driven sessions. When I look at our product health, I now demand a split view that separates agentic background tasks from deliberate human workflows. This allows us to see if our users are still finding value in the interface or if they are simply letting our agents run the show in the background.
Takeaway: Prioritize human-intent metrics to ensure your product remains a destination for users, not just a utility for their bots.
Before and after03
From Manual to Automated
E-commerce Logistics · PMO
Before implementing agentic tracking, the team tracked 'shipment updates' as a single metric, which looked like a steady upward trend. After implementing agentic-usage-dilution tracking, they discovered that human users had stopped checking the portal entirely because the AI agent was handling all status updates. This led the team to pivot the portal from a status-checking tool to a strategic supply chain planning hub.
Takeaway: Move toward evolving your product's purpose when automation renders your original features obsolete for human users.
Cautionary tale04
The Engagement Trap
Healthcare Software · CAiO
A clinical documentation tool pushed an AI update that automated 80 percent of note-taking. The product team saw record-breaking usage numbers and doubled down on the feature. They missed the fact that doctors were no longer reviewing the notes, leading to a spike in minor errors that went unnoticed because the human-in-the-loop engagement had effectively vanished.
Takeaway: Build for resilience by ensuring that automation does not replace the critical human oversight required for high-stakes outcomes.
