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Explore the transition from research-based autonomous agents to production-ready systems in this 19-minute conference talk that introduces CodeAct, a revolutionary paradigm for agent architectures. Learn how Large Language Models can generate and execute Python code for tool interaction, moving beyond traditional JSON or function-calling approaches to create more flexible, scalable, and robust agent systems. Discover practical deployment strategies, common integration challenges, and hands-on lessons from working with LangGraph and open-source libraries. Examine live examples demonstrating how CodeAct streamlines complex workflows while building more transparent, auditable, and powerful AI agents for production environments. Gain actionable insights for implementing executable agent workflows that deliver real-world impact, presented by an AI leader with extensive experience in public safety applications and agentic system development.
