Executive Guide to Successfully Innovating with AI Agents
Agents are the ultimate expression of AI in the real world - taking the reasoning ability of Generative AI and turning it loose to directly interact with the systems and people that drive our enterprises. Join us for a session with our CEO, Adam Wenchel, as he shares successful patterns gleaned from his career and directly working with dozens of AI teams at some of the top companies in the world.
In this webinar, we'll cover:
1. How to identify high value opportunities to innovate with Agents
2. Understanding the different components of an Agentic AI system including prompts, orchestration, vectorized data, tools, agents, guardrails, and evals.
3. Overcoming ‘Pilot Purgatory’ and taking AI from demo all the way into production
4. Common pitfalls and proper risk management
5. When to get excited (and when not to)
By the end of the webinar you will be equipped to lead Agentic AI projects to success and in the process create significant value for your business.
Webinar | Wed July 23, 2025 | 12pm ET | 9am PT
Your Host
Adam Wenchel
Adam Wenchel is the co-founder and CEO of Arthur AI, a company that enables organizations to monitor and improve the performance of AI/ML models in production.
Before founding Arthur, Adam served as Vice President of AI and Data Innovation at Capital One, where he built and led the Center for Machine Learning. There, he helped the company navigate the challenges of deploying AI in a highly regulated financial environment, following Capital One’s acquisition of his cybersecurity startup.
With deep technical roots and a pragmatic understanding of enterprise constraints, Adam is known for tackling the “last mile” problem in AI and for taking bold approaches to make AI work reliably at scale.
Leading companies rely on Arthur AI for AI that works in production
About Arthur
Arthur helps organizations monitor and improve AI performance with continuous evaluations across the model lifecycle. From development to deployment, we provide built-in guardrails, flexible deployment options, and support for any model or use case, so teams can trust, scale, and secure their AI systems with confidence.
