Agentic AI Summit Coming to NYC

- The Agentic AI Foundation is backed by the Linux Foundation and was co-founded by major AI players including OpenAI, Anthropic, and Block. This collaboration aims to create open and interoperable standards for AI agents, preventing vendor lock-in as the technology matures. - A key focus of the summit, the Model Context Protocol (MCP), is designed to be a universal adapter, enabling AI agents to securely and consistently interact with external data sources and tools. For data engineers, this standardizes how AI applications can connect to platforms like Snowflake, with dbt Labs providing an MCP server to build agentic workflows on top of structured data. - In the insurance sector, agentic AI is being explored for its potential to autonomously analyze diverse data sources for more dynamic and precise risk profiling and underwriting. However, actuarial bodies like the International Actuarial Association and the Institute and Faculty of Actuaries are actively discussing the new risks and ethical considerations, such as the opaqueness of models within agentic planners, and the need for human oversight and validation. - For those aspiring to engineering management, leading AI teams requires a shift in focus from code generation to production excellence and architecting effective human-AI collaboration. New management models are emerging, such as the "Centaur Pod," where a senior lead manages a hybrid team of engineers and specialized AI agents. - From a product management perspective, the pivot to agentic AI involves defining features with a ladder of autonomy, starting with suggestions and moving towards independent action within clear guardrails. Product managers in this space focus on orchestrating complex systems, managing the agent's memory and state, and defining new success metrics beyond simple clicks and conversions. - The consumer retail and fashion industries are leveraging agentic AI to create hyper-personalized customer experiences, acting as digital stylists that can curate outfits and guide purchasing decisions in real-time. These agents can also optimize inventory by forecasting demand with greater accuracy, reducing overproduction and waste. - The New York City tech scene features a growing number of startups focused on agentic AI, including companies like Lyzr, Vellum, and Mutiny, which are developing platforms for building and deploying AI agents for various business functions. - MLOps for agentic AI is evolving to address the continuous learning and adaptation required by these systems. Key practices include automated agent evaluation pipelines, implementing continuous feedback loops, and using unified observability to monitor the behavior of autonomous agents in production.