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From OTEL to SLMs: Distilling Frontier Model Behaviour from Production Telemetry
Ben O'Mahony shares how to build a data flywheel for AI agents using OpenTelemetry, explaining how behavioral user signals can be mined to distill and fine-tune smaller, localized language models.
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The Rust High Performance Talk You Did Not Expect
Ruth Linehan discusses Momento’s 3-year migration from Kotlin to Rust, explaining how the borrow checker speeds up delivery velocity and why Rust lowers overall engineering costs in production.
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Postgres for Production Agents: Your Relational Foundation for Enterprise AI
Gwen Shapira discusses how to power enterprise AI features using Postgres, explaining advanced relational SQL context retrieval, pgvector semantic tuning, and transitioning to agentic workflows.
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Lessons Learned in Migrating to Micro-Frontends
Luca Mezzalira discusses a practical roadmap for migrating to micro-frontends, explaining how to optimize for team autonomy, identify domain boundaries, and leverage edge-compute routing.
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Road to Compliance: Will Your Internal Users Hate Your Platform Team?
Davide de Paolis shares how to scale internal compliance and platform engineering without breaking developer velocity, detailing automated feedback loops and "minimum viable governance" on AWS.
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Chaos Engineering GPU Clusters
Bryan Oliver explains how to apply chaos engineering to massive GPU clusters. Learn how to handle hardware variability, NUMA nodes, and network faults to secure your AI infrastructure.
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Accelerating Netflix Data: a Cross-Team Journey from Offline to Online
Raj Ummadisetty and Ken Kurzweil explain how Netflix transitioned its key-value abstraction from stateless to stateful, reducing data deployment time by 90% and infrastructure costs by 70%.
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The Multi-Agent Approach: Building Reliable and Controllable Software Development Automation
Itamar Friedman explains how to transition from "vibe coding" to reliable software delivery. Learn how to govern agent communication and build a context-driven SDLC that scales.
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Designing AI Platforms for Reliability: Tools for Certainty, Agents for Discovery
Aaron Erickson shares how NVIDIA scales AI agent hierarchies by balancing determinism and discovery, offering engineering leaders a practical blueprint for building reliable, purpose-built systems.
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Practical Robustness: Going beyond Memory Safety in Rust
Andy Brinkmeyer explains how to leverage Rust beyond memory safety. Discover how senior devs and architects can embed runtime protocols into types to eliminate bugs at compile time.
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Fine Tuning the Enterprise: Reinforcement Learning in Practice
Will Hang and Wenjie Zi explain how OpenAI's Agent RFT (Reinforcement Fine-Tuning) optimizes reasoning models end-to-end, enabling autonomous agents to learn efficient tool use and cut latencies.
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Enhancing Reliability Using Service-Level Prioritized Load Shedding at Netflix
Anirudh Mendiratta and Benjamin Fedorka explain how Netflix handles massive traffic storms using service-level prioritized load shedding and client-side attempt budgets to protect critical path APIs.
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