Real-world grounding in agentic AI

The year 2026 marks a definitive shift in the AI landscape: we have moved from models that simply know to agents that do. Foundation models (FMs) — large Transformer models pretrained with massive datasets and fine-tuned for diverse downstream tasks — have moved far beyond chatbots, coding, and other digital applications. They are now used as the cognitive engines for AI agents in the physical world, where they plan, use tools, and execute multistep tasks across complex, digitally integrated environments, from warehouses and factories to transportation systems and hospitals. At Amazon, you can see the transition to this new era of "physical AI" in the debut of Project Eluna, an agentic AI model designed to transform how Amazon fulfillment centers operate. To be useful in a high-stakes physical environment, however, an agent needs to be more than fluent in…