I currently lead AI product and strategy at Confluent, where my team is responsible for Confluent Intelligence: a platform for building real-time, context-aware AI systems. That work spans streaming-native ML, event-driven agents (including the open-source Flink Agents project), and the Real-Time Context Engine which connects live data, stream processing, and low-latency serving so AI systems can reason over what’s happening now, not what happened yesterday.

My career has lived at the intersection of engineering, product, and storytelling. I’ve led organizations at multiple stages: from founding and scaling a startup from zero to acquisition, to building and running teams inside global companies like Google. I’ve managed managers, built new teams from scratch, navigated ambiguity, aligned stakeholders across engineering, design, legal, security, and GTM, and taken products from concept to launch to sustained adoption. I’m most energized by situations where the path isn’t obvious and the tradeoffs matter.

Earlier in my career, I was a hands-on engineer and researcher: competing in the ACM ICPC world programming finals, publishing academic research in AI and data-intensive systems, teaching computer science, and writing production code that has processed billions of events. That background still shapes how I lead today. I value technical rigor, clarity of thinking, and leaders who stay close to the work.

I’m especially interested in how complex systems emerge from simple parts, whether that’s distributed systems, data platforms, or multi-agent AI architectures. These days, I spend a lot of time thinking about how to make AI systems more reliable, observable, and useful in the messy reality of enterprises.

Outside of work, I co-host Software Engineering Daily and Software Huddle, where I get to learn in public by talking with builders, founders, and researchers across the industry.

If you’re working on hard problems at the intersection of AI, data, and systems or just enjoy thoughtful conversations about technology, I’m always happy to connect.

Connect with me here.

I love applying principles of computer science, data mining, machine learning, and statistics to pop culture. I cover most of these side projects in my writings on my website.

Here's a few highlights:

• The Monty Hall Problem as Seen on Survivor
• The Optimal White Elephant Strategy
• Survivor’s Race Problem: How the Odds are Stacked Against BIPOC Players
• Survivor’s Gender Problem: The Impact of the Hidden Immunity Idol
• Crowdsourcing a Behavioral Model for Survivor

• @seanfalconer on Twitter
• /in/sfalc on LinkedIn
• @thefalc on GitHub
• thefalc.com my website