The AI Con USA Virtual Attendee Experience

K1

Dona Sarkar
Microsoft

KEYNOTE | Will the Real Autonomous Agent Please Stand Up: What’s Real, What’s Not, and What You Actually SHOULD Be Investing in in the AI-Verse

If you’ve seen the news lately, the tech bros will have you believe that AI is both here to take your job and also your soul. On the other side, people are saying that we are in an AI-bubble, it’s all hype, and we don’t need to worry about it at all. Which is it? The truth is…it’s a little of BOTH. Dona will demystify what the latest buzzwords in AI (what is OpenClaw all about) and show you a roadmap for how you can AND SHOULD be using AI in your day-to-day life. You’ll learn how to set up an experiment framework for yourself, identify the workflows AI is actually good for, how to run the tests, and how to decide if an experiment is a win or a learn. Join us!

K2

Marshall Belcher
Google

KEYNOTE | Architecting the Digital Work System: The Shift to Multi-Agent Enterprise Workflows

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 build resilient, fault-tolerant systems. Attendees will discover emerging interoperability standards designed to dismantle silos and enable seamless cross-platform communication. Finally, the keynote will explore the profound shift in enterprise human capital, preparing organizations for a future where employees evolve from task executors into strategic "AI managers."

K3

David Colwell
Tricentis

KEYNOTE | Why Your Agentic PR Never Gets Approved—Going from Vibe Coding to Agentic Engineering

You can write 100% of your code with AI, and only be 15% more productive. Want to know why? Solving the problem of moving faster as an engineer is about way more than code. You design, you problem solve, you discuss and communicate, you test, you shepherd the PR through review, you deploy, and you observe. So why are you being told you should be 10x faster now that AI can write code? David will discuss practical solutions for safely accelerating your entire workflow with AI. He will look at how to collaborate with PM, how to use AI planning, how to ensure validations are solid and builds are green, and most importantly, how to help your teams unblock those insane PR times. David will walk through practical lessons learned at Tricentis, examine real examples of valuable code that got stuck in the process due to a lack of certainty, and discover how to unblock AI engineering by remembering the fundamentals of good software architecture, among other actions.

K4

Ken Johnston
Envorso
Bob Rapp
GM
Ravi Vedula
Microsoft
Rebecca Norlander
Verific

KEYNOTE | Show Me the ROI: What Enterprise AI Actually Delivers in Year 4

The hype cycle is over. The pilot graveyard is full. MIT research suggests that 95% of Generative AI implementations have little to no measurable impact on P&L. So what separates the 5% that actually deliver? In this no-fluff panel, practitioners from the front lines of enterprise AI — spanning automotive, cloud platforms, and the messy middle of real-world deployment — will have a candid conversation about what's working, what consistently stalls, and what it actually takes to move from experimentation to results.

K5

Kat Styons
Yahoo

KEYNOTE | Building Agentic Engineering Teams

Agentic engineering has quietly inverted the fundamental bottleneck of software development. For decades, the hard part was building, so we optimized teams for execution speed, hired specialists to cover capability gaps, and treated wasted work as a cost to be managed through careful planning and consensus. Now an engineer with the right tools can scaffold major features in hours, often faster than they can get a meeting on the calendar to discuss it. This talk is a field guide for leading teams through that inversion. It reexamines the hiring calculus, what makes an early career engineer successful now, and what makes a veteran indispensable (and it's not what it used to be). It confronts the consensus crisis that emerges when anyone at the table can have a working prototype before the discussion concludes. It makes the case that diverse skill sets matter more than ever, even as the skills themselves shift from implementation specialties to differences in judgment and taste.

K6

Jessie Thomas
Allen Institute

KEYNOTE | The Next Era of Biological Discovery

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 scientific knowledge. These capabilities are not isolated experiments—they are production-grade tools embedded across the research lifecycle. What makes this work powerful is the mindset behind it. AI solutions designed to amplify human expertise, support open science, and continuously improve as new data types and modalities emerge. The lesson is clear: when AI is applied with clarity of purpose and scientific rigor, it becomes a force multiplier—transforming complexity into understanding and turning ambitious questions into achievable outcomes.

K7

Brittany Wilson
Nelnet

KEYNOTE | Proven, Not Promised: Real-World Insights from Nelnet’s AI Transformation

Engineering leaders are under constant pressure to deliver faster, improve quality, and reduce costs despite fixed resources. At Nelnet, this challenge was compounded by ongoing acquisitions, a complex application landscape, and competing team priorities. Brittany Wilson will discuss how they evaluated the impact of Generative AI (GenAI) on the software development lifecycle without disrupting critical delivery work and how Nelnet adopted a measured pilot approach. Over 12 weeks, a side-by-side experiment compared a GenAI-enabled team with a business-as-usual team working on similar codebases. The initiative focused on integrating AI tools into existing workflows, establishing a custom metrics framework, and capturing best practices through hands-on development and coaching. This strategy allowed for experimentation while safeguarding essential initiatives, demonstrating how to run low-risk AI pilots, measure their impact, and balance innovation with delivery commitments. The results showed a 31% increase in productivity, providing a proven model for scaling AI initiatives responsibly. Brittany will give you insights into maintaining this balance, applying proven methods to pilot programs, and responsibly expanding AI’s role in software development, all while managing limited engineering capacity and competing priorities.