Managing cost in the age of AI

AI applications need to be performant, secure, observable, and cost-effective. How do you implement and fund new AI initiatives without risking performance, going over your budget, or leaking sensitive data? Balancing cost and performance is even harder when AI agents are doing the work. Compute spikes are no longer bound by how many humans are at keyboards; they’re driven by how many agents are running in parallel, how much context each one loads, how many retries it takes to produce code worth keeping, and how often a rollback sends the whole loop back to the start. You may not have full visibility into what you’re spending on AI, how to forecast it, or whether the ROI justifies the investment. You may be uncertain about your security posture around the data you’re feeding into your AI models. Join us for an open conversation. As a group, we’ll work through funding AI initiatives, scope of AI spend, tools and processes, AI-driven KPIs, governance.