Everyone's talking about AI agents - vendors are promising revolution, your competitors claim they're already using them, and your team is asking for budget. But what's actually delivering value today versus what's still marketing hype? In this session, I'll share our honest experience deploying AI agents in production environments - including the wins, the failures, and the uncomfortable truths nobody mentions in sales pitches. No vendor slides, no theoretical promises - just real results from real implementations. Drawing from our work at run.events, we'll examine where AI agents are genuinely transforming operations: **Where agents are actually delivering ROI:** - Intelligent matching and recommendations that increase engagement (and revenue) - Workflow automation that handles complexity, not just repetitive tasks - Dynamic personalization that scales without scaling headcount - Resource optimization that adapts faster than any manual process **What we'll cover:** - The real cost of implementation - time, talent, and infrastructure (it's more than the license fee) - How to evaluate agent solutions: questions your vendors hope you won't ask - Change management realities: why the technology is often the easy part - Where agents fail spectacularly - and how to avoid expensive lessons we've already learned **You'll leave knowing:** - Which use cases justify investment today vs. which need more maturity - How to set realistic expectations with stakeholders - Red flags that signal an agent project is heading toward failure - A practical framework for evaluating AI agent opportunities in your organization Whether you're approving budgets, leading digital transformation, or simply trying to separate signal from noise - this session will give you the clarity to make informed decisions about AI agents. No hype, no hand-waving, just what it really takes to deploy AI that your organization will thank you for.

Everyone's talking about AI agents these days - but what are they actually good for? In this architecture and development session, I'll cut through the hype and show you how we're building intelligent agents that solve real business problems (not just generate fancy demos 😉). I'll take you through our journey implementing Microsoft Semantic Kernel and LLMs to develop autonomous agents that actually deliver value. No theoretical hand-waving - we'll dive deep into practical scenarios where agents excel: understanding context, making intelligent decisions, and adapting to user needs in real-time. Through concrete examples from various domains (including our work in event tech with run.events), we'll explore where agents truly shine: * Context-aware recommendation systems that users actually appreciate * Intelligent workflow automation that goes beyond simple if-then rules * Dynamic personalization that adapts to individual patterns * Smart scheduling and resource allocation We'll cover: * The tech stack we chose and why (including spectacular failures along the way) * Architecture patterns for building maintainable agent systems * When to use agents vs. traditional approaches (spoiler: agents aren't always the answer) * Live coding examples - because theory is nice, but seeing is believing You'll learn the difference between "AI agents" as a buzzword and agents as practical problem-solvers. Whether you're writing code, designing systems, or evaluating AI solutions for your organization, you'll walk away knowing exactly when agents make sense - and more importantly, when they don't. Join me for a no-nonsense exploration of what it really takes to build AI agents that users will thank you for, not just tolerate.