Raymond James is using knowledge graphs as a reasoning and context layer for its AI agents — and the architecture offers a lesson for any business deploying autonomous systems. Here's why the data layer underneath an agent matters as much as the agent itself. Read more
Most businesses treat AI deployment as a finish line. CoreWeave Forge treats it as a starting point. The AI improvement loop — run, observe, evaluate, improve — is continuous by design, and understanding it changes how businesses should think about going live with agents. Read more
OpenAI's Dots launch gives AI agents their own cloud computers and persistent memory — no prompt required for every step. What does a shift from reactive to always-on architecture actually mean for businesses running autonomous agents? Read more
Conventional databases store facts about the world as it was. AI agents need to know the world as it is — right now. Keewano's $12M raise backs infrastructure designed to close that gap, and it signals a broader shift in how agentic systems are built from the ground up. Read more
For decades, network engineers have followed the same ritual: alert fires, dashboards open, logs pulled, answer maybe found an hour later. Extreme Networks' Agent ONE signals something different — an AI that doesn't surface information, it completes the reasoning. What does that actually mean for autonomous operations? Read more
What happens when one AI agent knows something another one doesn't? In enterprise deployments, that gap isn't just an inconvenience — it's a governance failure waiting to surface. Writer's Enterprise Brain points toward a more coherent architecture. Read more