AI Engineering/Phase 11/Lesson 02

Few-Shot, Chain-of-Thought, Tree-of-Thought

Telling a model what to do is prompting. Showing it how to think is engineering. The gap between 78% and 91% accuracy on the same model, same task, same data is not a better model. It is a better reasoning strategy.

Build 45 min Python

Prerequisites: Lesson 11.01 (Prompt Engineering)

#Learning Objectives

Implement few-shot prompting by selecting and formatting example demonstrations that maximize task accuracy
Apply chain-of-thought (CoT) reasoning to improve accuracy on multi-step problems like math word problems
Build a tree-of-thought prompt that explores multiple reasoning paths and selects the best one
Measure the accuracy improvement from zero-shot vs few-shot vs CoT on a standard benchmark

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The text and code of this lesson are based on AI Engineering from Scratch by Rohit Ghumare, MIT licensed.