Phase 1: Self-Improving Systems · ~60 minutes · Python (stdlib · bootstrap-loop simulator)

STaR, V-STaR, Quiet-STaR — Self-Taught Reasoning

The smallest possible self-improvement loop sits inside the rationale.

Hiring signal: Can operate star, v-star, quiet-star in production

Introduction

A model generates a chain of thought, keeps the ones that land on correct answers, and fine-tunes on those. That is STaR. V-STaR adds a verifier so inference-time selection is better. Quiet-STaR pushes the rationale down to every token. All three work. None of them are magic — the loop preserves any shortcut that happened to reach the right answer.

Type: Learn Languages: Python (stdlib, bootstrap-loop simulator) Prerequisites: Phase 13 · 01-03 (Reasoning and CoT), Phase 15 · 01 (long-horizon framing) Time: ~60 minutes

Objective

Learning objectives

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You've read the first 2 sections. The rest of this lesson covers The Problem, The Concept, Build, Check Yourself, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.

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