Vanessa Huerta Granda explains how marathon incidents expose the gap between work as imagined and work as done. Drawing from real-world scenarios, she shares how complex outages reveal organizational fragility, human limits, and system interdependencies—and why incident response requires structured endurance, humane rotations, and holistic cross-functional coordination.

Sarah Deitke discusses how Duolingo drives cultural AI adoption beyond tooling access. She explains their internal AI literacy workshops and observability dashboards, then shares a case study on redesigning code review using an automated PR risk-assessment bot. Deitke demonstrates how pairing targeted developer education with safe AI guardrails speeds up delivery without increasing defect rates.

Alex Porcelli discusses the critical gap in enterprise AI: non-deterministic output and lack of accountability in high-stakes decisions. He shares how integrating DMN decision models with LLMs, agent skills, and NeMo guardrails creates auditable, deterministic agentic architectures - allowing business leaders to own decision logic while engineers maintain robust architectural governance.

Cassie Shum discusses why knowledge graphs serve as a critical foundation for agentic systems. Moving beyond basic RAG, she explains 4 practical architectural patterns: context bundling, decision provenance, code as truth, and agent visibility. She demonstrates an engineering harness built on a knowledge graph to streamline feedback loops, optimize token usage, and maintain system reliability.

Ross McFarlane and Kevin Holditch discuss Form3's evolution from a single-cloud setup to a triple active multi-cloud architecture. They share key engineering strategies for cross-cloud networking, distributed databases with CockroachDB and NATS, custom Kubernetes operators, and navigating distinct regional disaster recovery expectations across the UK, Europe, and US financial markets.

Felipe Huici explains how Unikraft achieves millisecond cold boots, stateful scale-to-zero, and extreme density for sandboxing AI workloads. He discusses isolation primitives, Linux kernel optimizations, and snapshotting tricks, demonstrating how to maintain sub-10ms performance at scale while integrating seamlessly into Kubernetes environments with hardware-level security.

The panelists explain how platform teams adapt to support AI-assisted engineering, highlighting which capabilities belong in the platform. They discuss trade-offs between standardization and developer autonomy, while sharing strategies to manage AI tooling, security guardrails, and shifting workflows.

Joe Cassavaugh shares his journey from software engineer to successful solopreneur with a $2M+ indie franchise. He explains how he scaled production to 10 games in 5 years, adopted Unity to boost velocity 4-6x, optimized content pipelines, and leveraged refactoring patterns. He discusses key trade-offs between corporate engineering and solopreneurship for senior devs and leaders.

Zhou Yu discusses why AI agents stall in demo phase and shares how simulation-driven testing solves compliance and reliability bottlenecks. Learn how Columbia and Arklex AI use synthetic user personas, trajectory entropy, and automated CI/CD pipelines to evaluate multi-turn agents, catch edge cases before deployment, and scale self-learning workflows in production.

Joseph Stein discusses engineering an enterprise AI-as-a-Service platform within a private cloud data center. He explains how to maximize underutilized GPU pools via multi-namespace scheduling, leverage Valkey and Lua for atomic priority queuing and backpressure management, mitigate OWASP Top 10 LLM risks via central proxy gateways, and scale batch pipelines using a custom S3-to-Kafka proxy.

Sergiu Petean discusses the strategic journey of evolving DevOps into platform engineering within heavily regulated enterprise environments. He explains how to maximize efficiency using dynamic reference architectures, align platform KPIs directly with board-level business goals, reduce cognitive load via custom team topologies, and maintain innovation sovereignty through open-source technology.

Amir Langer discusses the evolution of latency reduction, from the Pony Express to modern hardware. He explains how separation of concerns - decoupling business logic from I/O - and tools like Aeron and the Disruptor achieve single-digit microsecond speeds. He shares insights into replicated state machines, consensus protocols like Raft, and the future of low-latency sequencer architectures.

Sepehr Khosravi discusses the current state of AI-assisted coding, moving beyond basic autocompletion to sophisticated agentic workflows. He explains the technical nuances of Cursor’s "Composer" and Claude Code’s research capabilities, providing tips for managing context windows and MCP integrations. He shares lessons from industry leaders on shrinking process time beyond just writing code.

Madelyn Olson discusses the evolution of Valkey's data structures, moving away from "textbook" pointer-chasing HashMaps to more cache-aware designs. She explains the implementation of "Swedish" tables to maximize memory density. She shares insights on systems intuition, memory prefetching, and the rigorous testing needed for mission-critical caches.

Franka Passing discusses the architectural shift of Duolingo’s 500+ backend services to Kubernetes. She explains the move toward GitOps with Argo CD, the transition to IPv6-only pods, and the "cellular architecture" used to isolate environments. She shares "reports from the trenches" on managing developer trust, navigating AWS rate limits, and productionizing early adopter services.

Andrew Harmel-Law and a panel of expert architects discuss the shifting practice of architecture in 2025. They explain strategies for communicating technical debt to stakeholders, the benefits of decentralized decision-making through ADRs, and the career paths of modern leaders. The panel shares insights on bridging the gap between mobile and backend teams to ensure a holistic system.

Adrian Cockcroft explains the transition from cloud-native to AI-native development. He shares his "director-level" approach to managing swarms of autonomous agents using tools like Cursor and Claude Flow. Discussing real-world experiments in BDD, MCP servers, and language porting, he discusses why the future of engineering lies in building platforms that orchestrate AI-driven development.