by Amit Shekhar · 13 April 2026
Feed-Forward Networks in LLMs
Feed-Forward Networks in LLMs - understanding what they are, how they work inside the Transformer architecture, why every Transformer layer needs one, and what role they play in making Large Language Models so powerful.
Read on Outcome School ↗then come back to lock it in
Before you read, guessHow does data movement behave in a Feed-Forward Network?
Ten seconds, a guess, then read — a wrong guess still makes the answer stick.
What this article covers
- The Big Picture
- What is a Feed-Forward Network?
- Understanding Feed-Forward Networks with a Real-World Analogy
- Where Does the Feed-Forward Network Sit in a Transformer?
- How Does a Feed-Forward Network Work - Step by Step
- The Expand-then-Contract Pattern
- Why Does the FFN Expand and Then Contract?
- ReLU and Activation Functions
- What Does the Feed-Forward Network Actually Learn?
- How Much of the Model is the Feed-Forward Network?
- Feed-Forward Networks in Mixture of Experts
- Why Feed-Forward Networks Are So Important
The article lives on outcomeschool.com. Read it there, then come back: the tutor in the margin has read it and will answer questions, and the questions below check what stayed.