AMA: StrongDM Sr. Director, Product Management, Ashka Vakil on AI Product Management

At StrongDM, we approach safety, security, and compliance for autonomous agents by treating them like any other privileged actor in the system. The core principle is simple. AI agents should operate with a clear identity, least privilege, and full auditability. Without that, enterprise adoption does not happen. Here are the key frameworks we are putting in place: Strong identity and scoped access Every agent has a clear identity, not a shared or implicit one. We use mechanisms like StrongID and ...Read More

I evaluate agentic AI opportunities by focusing on high-value workflows where an agent can meaningfully reduce manual effort or improve consistency at scale. It is not about adding AI to features. It is about removing real operational pain in a way that customers can trust. Here is the criteria I use to prioritize: Volume of manual toil: We look closely at where security, IAM, and engineering teams are spending hours on repetitive, low-value tasks. If a workflow, like routine access reviews or i ...Read More

Most customers I speak with are excited about adopting autonomous AI agents, and many have already started experimenting. The interest is not theoretical anymore. Customers that I have spoken to are actively building or piloting agents to automate parts of their workflows. The hesitation is not about value; it is about trust, control, and risk. I have listed below the feedback I have seen so far: Strong pull from teams to adopt now: Engineering and DevOps teams are already building internal agen ...Read More

The core skill for PMs in AI is not learning how to build models. It is having enough depth to make strong product and tradeoff decisions. If PMs rely entirely on technical teams, you often end up with impressive technology looking for a use case. When product leads, you get solutions that customers actually trust and adopt. The biggest shift is moving from feature thinking to system thinking, where you understand how data, models, and workflows interact. Here are the critical skills that matter ...Read More

The biggest shift AI brings to user feedback is moving product teams from human-constrained, periodic research to continuous, autonomous discovery at scale. We are transitioning to a world where the product itself becomes a self-correcting software factory that observes its own use and heals friction points in real time. Here is how this architecture changes the reality for product teams: Scaling discovery to infinity: Right now, a product team's validation bandwidth is strictly limited by their ...Read More