A practical guide to the four strategies of agentic adaptation, from "plug-and-play" components to full model retraining.

Karthik Ramgopal and Daniel Hewlett discuss the evolution of AI at LinkedIn, from simple prompt chains to a sophisticated ...

AI agents will reshape 2026: they’ll feed on synthetic/structured data, remake the web, swarm unpredictably, and empower ...

CISOs are vocal about the risks. Seventy-three percent say they are very or critically concerned about AI agent behavior. Yet ...

AI agents have emerged from the lab, bringing promise and peril. A Carnegie Mellon University researcher explains what's ...

See how Langraph powers a multi-agent stock sim with configurable rounds and models, helping you compare trade plans without ...

Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

As AI moves from controlled experiments into real-world applications, we are entering an inflection point in the security ...

Norm Hardy’s classic Confused Deputy problem describes a privileged component that is tricked into misusing its authority on ...