Systems | Development | Analytics | API | Testing

AI isn’t just evolving—it’s reshaping who your customers are, how systems operate, and what real time really means. From machines making purchase decisions to agents increasing query volume across databases, the realities of 2026 are forcing leaders to rethink data architecture and governance strategies at a fundamental level. In this episode, Joseph is joined by Will LaForest (Field CTO, Confluent), Adi Polak (Director of Developer Advocacy & Experience, Confluent), and independent analyst, Sanjeev Mohan, to break down critical insights from Confluent’s 2026 Predictions Report.

Busie Agentic Driver and Vehicle Scheduling: Intelligent assignment of drivers and vehicles to trips using real-time data on driver location and availability, vehicle utilization, and customer sentiment to optimize efficiency, service quality, and outcomes.

Apache Kafka is mission-critical for many organizations—but where you deploy it matters just as much as how you use it. In this video, two OpenLogic experts discuss why they increasingly encourage customers to move their Kafka clusters to Kubernetes and utilize the Strimzi operator, and what that shift unlocks from an operational, scalability, and resilience standpoint.

Kafka is powerful—but common Kafka mistakes can quietly undermine performance, reliability, and scalability. In this video, two OpenLogic experts break down the most frequent Kafka anti-patterns they see in real customer environments—and how to avoid them. Based on hands-on experience fixing production Kafka clusters, this discussion covers: If you’re running Apache Kafka in production—or planning to—this video will help you spot Kafka mistakes early and apply proven best practices to build a more stable, scalable event streaming platform.

Andy Steinmann of MarketAxess walks through how his team learned that “managed” Apache Kafka wasn’t really managed—and why Confluent Cloud was different.

AI agents are only as good as the data they can access. In this video, we explore the Model Context Protocol (MCP) and how it creates a bridge between AI models and Apache Kafka. Learn how MCP allows AI agents to securely produce, consume, and manage Kafka topics in real-time—transforming your event streams into actionable context for LLMs.

Andy Steinmann of MarketAxess shares how access to Apache Kafka experts—not just software—became the turning point in MarketAxess’ shift to Confluent Cloud.