Math

“Agent” is one of the most overloaded words in AI right now. Everything from a simple function-calling wrapper to AutoGPT gets called an agent. This post cuts through the hype and explains the actual mechanics: how agents think, act, and plan, with the math to back it up. What Is an Agent? A bare LLM is a function: given a prompt, output a completion. An agent wraps that function in a loop: ...

The 2017 paper Attention Is All You Need changed NLP forever. Before it, sequence models meant RNNs or LSTMs — sequential, slow, and bad at long-range dependencies. The Transformer threw all of that out and replaced it with pure attention. This post walks through the key components with the actual math. The Problem with RNNs An RNN processes tokens one at a time. To compute the hidden state at step $t$, you need the state at $t-1$: ...