The exponential growth of Internet of Things (IoT) deployments across enterprise environments has fundamentally transformed how organizations approach cybersecurity. The rapid increase in IoT connections has significantly expanded the attack surface, making it more challenging to secure networks. Enterprises face unique challenges and require robust IoT security frameworks to manage the scale and complexity of their deployments.

In our last post, we explored how short-term memory enables agentic AI to hold a conversation that doesn’t reset after every message. That form of memory is all about flow—preserving context, user intent, and logic within a single session, even as interactions stretch across multiple turns. The longer the session, the more memory is required to maintain continuity. But not all memory needs to be verbose. Long-term memory serves a different purpose: persistence across sessions.

As part of the DevSecNext AI series, Jit hosted Michael Balber—Principal Software Architect at CyberArk—for an in-depth session on how his team built and evaluated real Retrieval-Augmented Generation (RAG) agents in production. Unlike abstract discussions about LLMs and assistants, Michael shared a grounded view of what it takes to deploy agents that don’t just talk—they act.

The transformation of urban environments through Internet of Things (IoT) technology has created unprecedented opportunities for improving city services, enhancing quality of life, and optimizing resource utilization. This process of digital transformation modernizes and integrates city infrastructures, improving efficiency but also introducing new cybersecurity challenges.