Jeff Huber of Chroma argues that building reliable AI systems hinges on 'Context Engineering'—the deliberate curation of information within the context window. He challenges the efficacy of long-context models, presenting a 'Gather and Glean' framework to maximize recall and precision, and discusses specific challenges and techniques for AI agents, such as intelligent compaction.
Jake Heller, founder of Casetext, shares a pragmatic framework for turning powerful large language models like GPT-4 into reliable, professional-grade products. He details a rigorous, evaluation-driven approach to prompt and context engineering, emphasizing iterative testing, the critical role of high-quality context, and advanced techniques like reinforcement fine-tuning and strategic model selection.
Gal Peretz introduces CodeAct, a paradigm where LLMs generate and execute Python code for tool interaction, offering a more flexible and powerful alternative to traditional JSON-based function calling for building complex, production-ready AI agents.
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.
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.
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.