---
id: "stanford-dspy"
title: "DSPy"
creator: "Stanford NLP"
creator_url: "https://dspy.ai/current/"
url: "https://dspy.ai/current/"
level: "advanced"
level_max: null
category: "prompting"
subcategory: "prompt-optimization"
region: "West"
license: "open"
license_scope: "linked-resource"
models: ["any"]
source_date: null
date_added: "2026-10-18"
---

[Prompting](/prompting/index.md)

# DSPy

by [Stanford NLP](https://dspy.ai/current/)

[Read the original →](https://dspy.ai/current/)

Build modular model programs and improve them against a metric.

DSPy separates task signatures, execution modules and optimization. Its examples show how prompts can be adjusted using training examples and a scoring function rather than maintained only through manual edits.

Level: [Advanced](/levels/index.md#advanced)
Models: any
Category: [Prompting](/prompting/index.md)
Tags: 
Source date: date not stated
Added: 2026-10-18
Last verified: 2026-10-18
Status: ok
Prerequisites: Requires implementation experience or critical reading of technical methods and system trade-offs.
Subcategory: [prompt optimization](/prompting/prompt-optimization/index.md)
Region: West
Original language: en
Access: free
Resource reuse: open: Source states MIT. Applies to the linked resource, not every referenced model or dataset. [Facet definitions](/about/index.md#facets)

Summary in our own words. Rights remain with the original creator. [Credit and correction policy](/about/index.md#credit-policy).

[Plain-text Markdown copy](/prompting/prompt-optimization/stanford-dspy/index.md)