Yassine Naji

Jev: Why AI Agents Don't Always Need LLMs

The deployment of LLMs in enterprise environments has revealed a mismatch between conversational AI and software automation. Using an autoregressive model to route a customer ticket, classify a document, or trigger an API is similar to using a generative engine for a simple database lookup. This article explores the emergence

Deep Agents: How Agent Harnesses Scale AI Agents

Based on the Deep Agents framework by LangChain. Scaling Large Language Models (LLMs) from reactive chatbots to autonomous enterprise systems exposes an architectural limitation: context saturation. Early agent implementations relied on a shallow tool-calling loop. As these agents interact with external enterprise databases or APIs, they ingest massive, unfiltered