AI Con USA 2026 - IT Technology Leader

"We love AI and use it for everything we do!" "We hate AI and will NEVER use it for anything ever, I swear to god!" Which camp are you in? This will be a question that will come up over and over in 2026 and beyond. If you use AI for EVERYTHING and think you can be mistaken for AI…has AI not already taken your job? We all need to get INTENTIONAL about our stance in the AI-verse. Have you thought deeply about what is a good activity for AI to lead on and what should be uniquely human? We are already seeing a premium price tag on in-person, uniquely human-to-human experiences, and this will...

Tired of staring at the chat box of an AI assistant wishing it could actually do a task for you rather than just telling you what to do? Model Context Protocol (MCP) is the glue between an AI agent and your data and tools. With MCP, AI assistants can read your documents, conversations, and other context and take action for you by sending emails, submitting tickets and more. But what really is MCP and how do you use MCP servers safely in practice as part of your day-to-day workflow? This half-day course introduces MCP and dives into practical use cases. Laurel will walk you through how to...

Tired of sifting through endless news sources and missing the topics you care about? This hands-on workshop empowers you to build a personalized AI news assistant using Redis and LangGraph.js. You’ll learn to ingest articles from RSS feeds, summarize and analyze them, extract structured data, and generate embeddings—all stored in Redis for powerful hybrid (vector + structured) search. Your agent will provide a web interface for browsing and semantic search, and even chat with you about current events, retrieving relevant articles and metadata using RAG techniques. LangGraph.js orchestrates...

Theory is great, but what about getting your hands dirty with some real problem-solving? Lets build your own AI Operating System that you'll take home and use immediately. Join Melissa Benua and Ryan Lee for a hands-on session where you'll construct a personalized AI toolkit that solves YOUR specific testing problems, regardless of your coding background. We'll start by deconstructing the modern software development lifecycle used by all tech companies to safely ship software solutions to their customers, and show you exactly where AI accelerates each phase. Then we'll prove a critical...

Testing Artificial Intelligence (AI) agents presents a paradigm shift from traditional software quality assurance. Unlike deterministic, rule-based applications, AI agents exhibit emergent behaviors, learn from their environments, and make autonomous decisions, making conventional test case design and execution insufficient. This tutorial will provide a comprehensive understanding of the unique challenges and advanced strategies required to effectively test single and multi-agent AI systems. Participants will learn how testing agents differ significantly from testing traditional software....

AI agents have existed for decades, but generative AI has fundamentally changed what agents can do and how they are designed and built. Come and explore the evolution of AI agents across two major waves. First, learn the foundations of Agentic AI through agents built using rules, heuristics, and traditional machine learning, examining where these approaches excel and why they struggle with complexity, ambiguity, and scale. Then dive into the second wave of agents powered by generative AI and multimodal large language models. These modern agents can reason, plan, use tools, and interact...

The era of single-turn AI prompting is over, giving way to the sophisticated "digital assembly line." This session guides technical leaders, CTOs, and AI product managers through the critical leap from isolated AI tools to coordinated, multi-agent constellations capable of autonomously executing complex enterprise workflows. Marshall will dissect the four levels of agentic evolution, focusing on today's epicenter of innovation: cross-system orchestration. Because the risk of cumulative failure multiplies with every automated handoff, he will unpack the architectural strategies required to...

Enterprise containerized applications face a critical reliability crisis with complex failure modes including memory leaks, cascading failures, network partitions, and resource contention that traditional monitoring tools cannot predict or resolve fast enough. Organizations typically experience multiple production incidents monthly with multi-hour resolution times that consume significant engineering resources while causing customer-facing outages and revenue loss. Traditional approaches rely on reactive monitoring, manual troubleshooting across distributed container environments, and time...

Scientific discovery faces a major bottleneck: while generative AI has transformed information processing, it has not yet unlocked comparable acceleration in understanding the physical world. Traditional computational chemistry and materials modeling remain too slow, expensive, and limited to power large-scale innovation. SandboxAQ tackled this challenge by developing Large Quantitative Models (LQMs) — a new class of AI models that merge machine learning, physics-based simulation, and quantum-inspired algorithms to model molecular and material interactions at unprecedented speed and...

Shipping AI into regulated, safety-critical mobile apps is more than “just call an LLM.” In automotive and medical contexts, we must meet strict privacy, latency, and auditability requirements while working with flaky connectivity and device constraints. In this talk, Ronak will share a field-tested architecture for agentic AI on the edge: a hybrid edge–cloud agent that uses tool-calling plugins, a policy engine for pre/post-prompt guardrails, offline fallbacks, and structured telemetry for audits. He will walk through how his team bounds agent behavior with capability cards, redacts PHI/...

We are entering a defining chapter for bioscience—one where AI is no longer an accessory, but a core engine of discovery. At the Allen Institute, AI is being woven throughout the scientific process empowering research teams to analyze complex biological systems at scale. Their teams are collaborating to develop frontier AI applications like advanced computer vision to interpret high-resolution imaging data, multimodal models that integrate complex molecular, cellular, and physiological signals, as well as intelligent systems to assist researchers as they navigate and synthesize vast...

AI strategy has focused on intelligence—better models, stronger reasoning, and higher benchmark performance. That advantage is rapidly commoditizing. As AI becomes embedded across products and operations, the next source of durable value is personalization; systems that adapt to individual customers, employees, and contexts over time. Generic AI delivers diminishing returns; relevance, trust, and perceived quality increasingly determine adoption and impact. This talk explains why personalization is emerging as the decisive competitive frontier in AI, how it reshapes product strategy and...

As AI models grow in complexity and scale, inference efficiency has emerged as a critical engineering challenge for enterprise deployment. Traditional infrastructure built for training workloads often fails to meet the latency, throughput, and cost demands of large-scale inference operations. In this session, Sandeep will be sharing practical insights from engineering AI infrastructure at Broadcom, focusing on the end-to-end optimization of compute, networking, and storage subsystems. The talk explores techniques such as dynamic workload placement, adaptive batching, model quantization,...

AI can now generate code, tests, documentation, and even entire applications in minutes. Yet many organizations are discovering that faster code generation has not translated into faster delivery, higher quality, or greater business impact. Instead, teams are often facing more code churn, more technical debt, and more production incidents. The challenge is no longer getting AI to write code. The challenge is building systems that consistently deliver value to end users. Drawing on real-world experience building AI products, agent-based systems, evaluation frameworks, and production...

Modern AI systems fail not only because of flawed models but because evaluation is often treated as a one-time task rather than an ongoing discipline. This session addresses the challenge of scaling evaluation across teams and pipelines to ensure model reliability, fairness, and performance. Drawing from real-world experience in large-scale financial analytics, Anusha Dwivedula will examine how product and data teams can collaborate to design a continuous evaluation framework that integrates precision, recall, and drift metrics with observability, lineage, and quality controls. She will...

Successful AI adoption is 10% technology and 90% organizational change—and most organizations are failing at the 90%. In this dynamic, experience-driven session, we will cut through the hype and get honest about what it actually takes to move AI from promising pilot to measurable business impact. Drawing on nearly three decades of technology leadership and his background as a U.S. Army Ranger, Shawn brings a battle-tested perspective to the modern boardroom: the same principles that forge elite units into high-performing teams are exactly what today's organizations need to win the AI...