by Amit Shekhar · 16 May 2026
Proximal Policy Optimization (PPO)
In this blog, we are going to learn about Proximal Policy Optimization (PPO). We will also see how PPO works step-by-step and how it is used in training Large Language Models with RLHF.
Read on Outcome School ↗then come back to lock it in
Before you read, guessWhat is the core mechanism of PPO for updating policies?
Ten seconds, a guess, then read — a wrong guess still makes the answer stick.
What this article covers
- What is Reinforcement Learning?
- What is a Policy?
- The Problem with Simple Policy Updates
- What is Proximal Policy Optimization (PPO)?
- The Key Idea Behind PPO: Clipping
- The PPO Objective Function in Simple Words
- How PPO Works Step-by-Step
- PPO in Large Language Models (RLHF)
- Advantages of PPO
- Disadvantages of PPO
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.