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Least-to-Most Prompting

Least-to-most prompting solves a complex problem by first breaking it into sub-problems ordered from easiest to hardest, then solving them in sequence, using each answer as the basis for the next. Unlike free chain-of-thought, the decomposition here is explicit and progressive. Example: "Step 1: list the sub-problems from easiest to hardest. Step 2: solve them one by one, reusing prior results. Problem: compute this quarter's net margin from revenue, variable costs, fixed costs and tax." The model builds the solution in layers.

Definition

Use it for problems with cascading dependencies, multi-step math, compositional reasoning, tasks that generalise poorly from simple examples. It stops the model skipping steps and handling instances harder than the demonstrations.

Related terms

• Chain of Thought
• Self-Ask
• Skeleton-of-Thought
• Prompt Chaining
• Tree of Thoughts

More in Prompting

• Prompt
• Prompting
• Role Assignment
• Zero-shot
• Few-shot
• Chain of Thought
• Prompt Engineering
• Output Format

Put it into practice

• Real scenario: apply this concept with an instant AI verdict.
• Daily gym: short drills to train dictionary concepts.
• Playoff game: challenge other players, elimination-style.

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