In agentic infrastructure, AI workloads, and Agents as a whole, networking is 90% of what you need to get right. It encompasses the security aspect of AI, how traffic flows in and out
Knowing what LLM you're routing to, whether or not failover for more expensive tasks exists, what LLMs are available, and policy enforcement/implementation for the people accessing LLMs are critical pathways
Many of us are "hands-on-keyboard" interacting with Agents in our terminal or via a desktop app. That's, however, when you want to do something at the exact
A typical gateway comes with a lot of policy enforcement, authentication/authorization implementations, and filtering for both agentic and API-centric traffic. However, there may come a time when you need:
* Custom auth,
The MCP protocol can now be stateful or stateless, ingest only one tool to the Agent, call API endpoints, and use functions/methods in a codebase as tools. The one concern still, however,
