Quality output from an LLM is the make-or-break between a task that performs well and a hallucination. The level of accuracy that's output is top of mind for everyone using Agents.
Architecture diagrams always look something like this:
Agent -> Gateway -> LLM (or MCP Server).
The Agents that organizations are typically referring to are Agents that perform an action via prompts
Accuracy and quality of output from an Agent is the make or break between what's truly usable across the enterprise and what's simply a toy. Aside from taking the
Security is no longer taking a backseat in the world of Agentic. Just about every conversation that happens in organizations around AI has something to do with security, and it's not
The importance of setting up proper observability via tracing for end-to-end application health isn't out of the ordinary in any regard. The majority of Platform and DevOps teams have this level
