Ekaterina Gorshkova, author of "Kafka for Architects", discusses her journey with Apache Kafka, from its early adoption in enterprise integration to its modern role as a foundational layer for AI and ML systems. The conversation covers key architectural decisions, the limitations of Kafka, and why the real challenges are often organizational rather than technical.
Shopify CTO Mikhail Parakhin details their aggressive internal AI adoption, revealing the internal stack—Tangle, Tangent, and SimGym—that powers reproducible ML, auto-research, and customer simulation. He also discusses how AI shifts the software bottleneck to PR review and CI/CD and explains their use of Liquid AI for low-latency, non-transformer workloads.
Mihail Eric, Head of AI at Monaco and Stanford Lecturer, discusses the fundamental shift in software engineering due to AI. He explores how the developer's role is evolving from a line-by-line coder to a systems architect and agent director, emphasizing the growing importance of upfront planning, robust validation, and clear articulation to effectively manage AI-driven workflows.
An engineering leader details the journey of self-hosting LLMs at enterprise scale, covering how his team slashed latency by 70% with TensorRT-LLM, optimized GPU costs through counterintuitive scaling, and built a verticalized AI platform for HR tech. The summary explores practical solutions for cold starts, KV cache optimization, and managing the cultural adoption of AI coding agents in engineering teams.
Johann Schleier-Smith from Temporal explains Durable Execution, a paradigm for building reliable, long-running applications. He details how Temporal's model of deterministic workflows and stateful activities provides a robust alternative to traditional checkpointing and event-driven architectures, especially for complex, LLM-driven agentic systems.
This panel delves into the strategic implementation of open-source, community-driven agentic stacks, balancing the benefits of open-source frameworks and models for rapid iteration, cost-efficiency, and compliance against the complexities of abstraction and debugging in production environments. Experts from NVIDIA, Stacklok, and Prosus discuss when to adopt open source, challenges in framework choice, the critical need for robust observability, and the role of no-code solutions for diverse user groups, emphasizing the importance of aligning tooling decisions with specific use cases and organizational needs.