Everything Agent, Model, and MCP Server related right now is spread across countless packages, libraries, providers, and you realistically have no way of knowing if any of it is secure, stable, or production
There are two types of Models/LLMs you see in today's Agentic world:
1. "SaaS-based Models", which are Models that are managed for you (Claude, Gemini, GPT, etc.)
2.
AI started out as a cool chatbot that you could ask questions to and get responses in real-time, like an enhanced search engine. Fast forwarding a few years and it's changed
As AI Agents begin to increase in usage, knowledge, and understanding of specific tasks, there may be a time when a task is too great for one Agent's knowledge. When that
Agents and Agentic Infrastructure give engineers the ability to have a 24/7/365 engineering helper (with the right implementation of course). The current perdiciment is when using public/cloud-based LLMs (Claude, GPT,
