Smart home payments are payments that connected devices in your home can initiate on your behalf—without you opening an app, swiping a card, or clicking a button. Your washing machine detects you are low on detergent and orders more. Your smart speaker pays your electricity bill when you ask. Your refrigerator restocks itself before you…
Multi-agent attacks are security threats that target AI systems made of multiple cooperating agents, where one agent’s action, message, tool call, or stored memory can influence another agent. In multi-agent systems, the security risk is not only that one model makes a bad decision, but that a compromised agent can spread bad instructions, false data,…
Shift from Chat to Action Most of us are familiar with AI as a conversational partner — a chatbot that answers questions or drafts emails. But agentic AI represents a fundamental shift. Instead of waiting for the next prompt, these systems are designed to execute goals. They break down complex objectives, decide on the necessary…
What is agent compliance? Key takeaways: Agent compliance is the set of regulatory, legal, and governance obligations that apply to organizations building or deploying autonomous AI agents—systems that perceive their environment, reason through tasks, and take actions to achieve goals without continuous human prompting. Unlike traditional AI compliance, which assumes a human makes the final…
GENIUS Act The GENIUS Act—formally known as the Guiding and Establishing National Innovation for U.S. Stablecoins Act (bill number S.1582)—is the foundational federal framework governing payment stablecoins in the United States. Signed into law on July 18, 2025, it provides the first comprehensive set of rules for how these digital assets are issued, backed, and…
The inference tax is the gap between what an AI product could theoretically achieve and what current economic realities allow it to do at scale. It represents the hidden costs of operating generative AI that force developers to make trade-offs—capping context windows, truncating memory, gating features, or routing queries to cheaper models—to maintain profitability as…
A multi-agent system (MAS) is a system in which two or more autonomous AI agents interact within a shared environment, each pursuing individual or collective goals through coordination, communication, or competition.
Agent infrastructure is the production platform surrounding an AI agent that supplies persistent context and state, executes agent steps and tool calls, connects models to enterprise systems, and continuously controls, monitors, and audits the agent’s actions.
The Shift: From Voice Commands to Household Intelligence For years, we have lived with voice assistants that functioned like digital librarians. You asked a specific question, and they retrieved a specific answer. You gave a command, and they performed a single action. But the landscape of our homes is shifting. We are moving away from…
The Shift from Theory to Practice For years, the conversation around AI security felt like a theoretical exercise—a debate about what might happen when machines begin making autonomous decisions. That era has passed. We are now managing the practical realities of integrating autonomous systems into our digital infrastructure. When an AI agent is granted the…