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Foundations, no jargon — from "what is an LLM?" to how agents reason. Bilingual, فارسی-first.

From LLMs to agents: the complete journey

A language model, at heart, just guesses the next word. Here's how that simple guess becomes an agent once you add tools, memory, and planning — and where you actually need one.

3 min read llms-to-agents

How agents remember: memory and knowledge representation A language model has no memory of its own and begins each conversation from scratch. What gives an agent memory is the layers built around the model. Learn 4 min read How an AI agent thinks An agent takes a goal, reasons, acts, and observes the result — repeating that loop until it's done. A simple mental model for how agents reason and decide. Learn 3 min read Prompt engineering from zero: write a formal letter, not a text message A language model can't read your mind. Everything you'd take for granted in a casual chat has to be stated outright in the prompt — the six components that make a good one, and the five mistakes beginners make. Learn 4 min read One agent or many? When each one fits Sometimes a single agent is the best answer, and sometimes the work should be split across several. The deciding factor is the complexity of the task, not how advanced the architecture looks. Learn 5 min read