Lior Gavish, CTO and co-founder of Monte Carlo Data, discusses the critical transition from data observability to agent observability. He covers the widespread adoption of AI agents in data teams, the new challenges they introduce for monitoring, and why traditional tools fall short in providing the necessary insights into agent performance, security, and governance.
Matthew Glickman, CEO of Genesis Computing, discusses the rise of AI data agents designed to automate complex data engineering workflows. He covers the "last 10%" problem in enterprise AI, the unique value of targeting the data engineer persona, and how these agents can tackle challenges like legacy system migration and knowledge capture, ultimately giving valuable time back to data teams.
Joe Reis and Matt Housley, authors of "Fundamentals of Data Engineering," discuss how AI has transformed data engineering practices since their book's release. They emphasize the enduring importance of foundational knowledge, the challenges AI poses for junior engineers, and the critical balance between leveraging AI assistance and maintaining core expertise in an increasingly complex field.
Ciro Greco, CEO of Bauplan, outlines a new paradigm for data engineering that applies software engineering principles like version control, transactionality, and a code-first approach to build a programmable lakehouse designed for AI-driven automation and enhanced developer productivity.
Joe Reis and Matt Housley, authors of "Fundamentals of Data Engineering," reflect on the book's principles three years after its publication. They discuss how the rise of AI has created both powerful tools and dangerous "bear traps" for engineers, the critical role of expertise in a world of AI-generated content, and why foundational knowledge is more important than ever.
Akshay Agrawal, CEO of Marimo, discusses how Marimo addresses the critical flaws of traditional notebooks like Jupyter. He explains its reactive architecture, the benefits of storing notebooks as pure Python files for version control and reusability, and its AI-native features that leverage runtime context for more intelligent LLM-assisted coding.