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© 2026 AI-Buzz. Early access — data updated daily.
Programming framework for LLM pipelines (Stanford NLP)
Founded by: Omar Khattab, Matei Zaharia, Chris Potts, Sanja Fidler, Hao Zhang, Ashish Sabharwal, Noah Goodman, Michael S. Bernstein, Percy Liang
Metrics computed from HN discussion, GitHub activity, and funding data.
According to AI-Buzz, DSPy with 64% positive developer sentiment (14 HN comments analyzed), with 4,889,989 PyPI downloads in 30 days.
Source: https://ai-buzz.com/companies/dspy?utm_source=citation&utm_medium=referral&utm_campaign=cite_this_data
Metrics derived from public APIs (HN Algolia, GitHub, npm/PyPI). Sentiment classified by AI. See methodology for details →
Description
Programming framework for LLM pipelines (Stanford NLP)
Website
dspy.aiFounded
2023
Description
DSPy is an open-source programming framework developed by researchers at Stanford NLP and other institutions. It provides tools for building, optimizing, and evaluating complex language model pipelines, allowing developers to programmatically compose prompts and models rather than relying on manual prompt engineering. Its significance lies in offering a structured, systematic approach to developing robust and efficient LLM applications, moving beyond ad-hoc prompting.
Community engagement metrics that indicate developer traction and interest.
Last updated: 1 day ago
Mentions in HN discussions. Source: Hacker News Algolia API.
Sentiment analysis of Hacker News comments only. Does not include Reddit, Discord, or other platforms.
Package download volume indicates real-world adoption and integration into production projects.
A programming framework for building, optimizing, and evaluating LLM pipelines, enabling developers to compose complex prompts and models programmatically.
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Package downloads and ecosystem metrics — 30-day window
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