Aug 25, 2025

Iterating on Your AI Evals // Mariana Prazeres // Agents in Production 2025

Moving an AI agent from a promising demo to a reliable product is challenging. This talk presents a startup-friendly, iterative process for building robust evaluation frameworks, emphasizing that you must iterate on the evaluations themselves—the metrics and the data—not just the prompts and models. It outlines a practical "crawl, walk, run" approach, starting with simple heuristics and scaling to an advanced system with automated checks and human-in-the-loop validation.

Aug 25, 2025

Integration of AI into Traditional Systems // Hakan Tek // Agents in Production 2025

This talk explores practical, low-disruption strategies for integrating AI capabilities into traditional and legacy enterprise systems without requiring a complete overhaul. It covers common challenges, effective integration patterns like API-based and hybrid approaches, and highlights readily available tools to help teams start small and deliver immediate business value.

Aug 25, 2025

Aaron Levie and Steven Sinofsky on the AI-Worker Future

Experts from a16z, Box, and Microsoft debate the definition and future of AI agents. They explore the shift from monolithic AGI to specialized agent networks, the technical challenges of autonomous systems, and how this new platform will reshape enterprise software, workflows, and the very nature of work.

Aug 25, 2025

AI Agents: Transforming Anomaly Detection & Resolution

Martin Keen explores how agentic AI can significantly reduce IT downtime and Mean Time To Repair (MTTR) by moving beyond naive data dumps and embracing context-aware analysis. The key lies in using topology-aware correlation to curate relevant data for an AI agent, which can then systematically identify the root cause, provide explainable insights, and generate actionable remediation steps, ultimately augmenting human SREs rather than replacing them.

Aug 24, 2025

Building an Agentic Platform — Ben Kus, CTO Box

Ben Kus, CTO of Box, outlines the technical evolution of their AI platform, detailing the transition from a promising but fragile LLM-based metadata extraction system to a robust, scalable agentic architecture. He explains why this shift was necessary to handle enterprise-level complexity and the key lessons learned.

Aug 24, 2025

Inside the little-known expert network quietly training every frontier AI model | Garrett Lord

Garrett Lord, CEO of Handshake, details the company's extraordinary pivot from a college career network to a dominant AI data provider. He explains how they leveraged their proprietary network of 500,000 PhDs and 3 million advanced degree holders to build a business on track to surpass $100 million ARR in its first year by providing high-quality, expert-generated data for training frontier AI models.