In the age of AI, the definition of great software architecture is being rewritten. While Large Language Models capture the headlines, the real challenge for architects lies in the infrastructure that surrounds them. It is no longer enough to simply "plug in" an LLM; designing for the next generation of software requires a fundamental rethink of how we manage context, ensure data safety, and evaluate non-deterministic systems. The shift from static applications to dynamic, autonomous agents demands a move from simple prompt engineering to robust Context Engineering.

The hurdles are significant: How do you prepare a data platform to serve the unique needs of Agentic Systems? How can we leverage Semantic Knowledge Layers—like Knowledge Graphs and Ontologies—to reduce hallucinations and provide agents with high-precision reasoning? As we move toward modular ecosystems, mastering standardized protocols like the Model Context Protocol (MCP) becomes essential for building maintainable and efficient agent-data integrations. Furthermore, the traditional testing playbook is being replaced by AI Evals, requiring new techniques to monitor and improve app behavior in the wild.

Join us at the Architectures in the Age of AI track, where we move beyond the hype to explore the actionable blueprints of the AI era. From mastering context to scaling production-grade evaluations, you will gain the insights and strategies needed to build reliable, safe, and sophisticated AI-driven systems. This is your chance to discover how to architect a future where AI doesn't just exist in your app—it excels.