5 stories
Most explanations of agentic AI systems stay at a high conceptual level. In this video, I trace a single user request step-by-step through a production-level agentic AI state machine from start to finish. I break down the three core components that make AI agents deterministic and reliable: 1.
Most AI tutorials show you a chatbot demo. This video shows you how that demo actually becomes a production system inside a bank — one component at a time, with the real engineering reasoning behind each addition. We start with 3 boxes: a chat UI, an agent, and an LLM.
Most AI tutorials show you a chatbot demo. This video shows you how that demo actually becomes a production system inside a bank — one component at a time, with the real engineering reasoning behind each addition. We start with 3 boxes: a chat UI, an agent, and an LLM.
Everyone wants to build AI agents - but underneath every agent is one raw API call most people never look at. A short, no-frameworks look at what actually happens when you call an LLM API - the raw request, the raw response - that's it.
Why standard LLMs fail in production, and how to fix it. Today's system design breakdown: Mapping the AI Router Node. How an orchestrator classifies user intent and delegates to specialized workers without overloading a single prompt.
Showing 5 of 5 stories
You're all caught up.
Get the top AI news and tools straight to your inbox every week.
Weekly · AI news
Join 15,000+ AI enthusiasts
