Inna Weiner

Most agentic AI initiatives stall at the same point: production. Not because the models underperform, but because the organization cannot confidently answer a simple question: why did the agent do that, and can we prove it. We encountered this directly while scaling to over 1,000 customers running more than 10,000 autonomous agents. The real constraint was trust: the ability to explain agent behavior, audit its decisions, and govern it in real time. This workshop presents the architecture we built to address that gap, centered on what we call Dynamic Context - a governed, real-time intelligence layer. We move past the term "AI-Ready" as a slogan and unpack what it really means: metadata treated as core infrastructure. Attendees will leave with a working framework to assess where their own organization sits on the path from experimentation to enterprise-scale autonomy, and what specifically needs to change at each stage. Three Key Takeaways: What trust in agentic systems actually means, and how to use it to diagnose where your own program is breaking down. A concrete definition of AI-Readiness that you can bring back to your team and act on, not a framework to file away. An honest assessment of where your organization sits on the path to production-grade autonomous AI, and one thing you can change next to bring it further along.