It’s tempting to treat loop engineering as something invented in a single week in June, but the mechanics behind it are closer to five years old, and knowing the lineage is what separates a real understanding of the idea from just repeating the trend piece.
In this article, you will learn how agentic AI architecture has evolved by mid-2026, including the shift away from orchestrated reasoning loops, the rise of…
In this article, you will learn how to build a complete agentic workflow in Python with LangGraph, from a single model call to a tool-using…
In this article, you will learn what prompt injection and tool misuse are in the context of agentic AI systems, and which defense strategies experts…
In this article, you will learn how to get a small language model running locally on your own machine in under 15 minutes using Ollama….
In this article, you will learn how scikit-ollama bridges the scikit-learn interface with locally running Ollama models to perform zero-shot text classification; no cloud API…
In this article, you will learn how to evaluate LLM applications using the three dominant open-source frameworks — RAGAS, DeepEval, and Promptfoo — and why…
Agent systems change constantly in production.
In this article, you will learn how to choose the right memory strategy for an AI agent by working through a simple decision tree, one…
The default assumption in most LLM developer communities is that you start with raw API calls and graduate to a framework as your project grows.