Paco N is a Principal Developer Relations Engineer and seasoned technologist with 15 years of experience building developer communities and production-ready AI solutions, currently leading ERKG (entity-resolved knowledge graph) developer relations at Senzing. He blends deep hands-on engineering—contributing core NLP algorithms like a Python TextRank implementation used for phrase extraction—with strategic community building and technical advising for startups and acquisitions (Argilla → Hugging Face). As Managing Partner of Derwen, Inc. he helps enterprises integrate open-source graphs, NLP, and optimization into AI production systems, applying both theoretical and empirical tools to solve high-leverage problems. A longtime educator and organizer, Paco co-runs Sonoma AI with Wine and previously led learning initiatives at O'Reilly and community programs at Databricks. His background spans research at Bell Labs and NASA through leadership roles in data science and analytics, reflecting a rare mix of academic depth and product-focused delivery. Based in Sebastopol, he pairs eclectic early-career experience (from dairy science to classics and neural nets) with practical open-source craftsmanship and public-facing developer advocacy.
15 years of coding experience
29 years of employment as a software developer
Math Computer Science, Math Computer Science at California State University, Stanislaus
United States Military Academy at West Point
Classics and Classical Languages Literatures and Linguistics, Classics and Classical Languages Literatures and Linguistics at San Francisco State University
California Polytechnic State University, San Luis Obispo
MS Computer Science (Systems), MS Computer Science (Systems) at Stanford University
Contributions:3 releases, 3 reviews, 28 commits in 9 months
Contributions summary:Paco's contributions primarily involve fixing typos, broken links, and improving the clarity of explanations within the provided Ray RLlib tutorials. They added descriptive text to existing rollout examples and provided clearer instructions on how to use different features and environments in the tutorials. The user's focus centered on enhancing the documentation and improving the readability and usability of the content.
Python implementation of TextRank algorithms ("textgraphs") for phrase extraction
Role in this project:
Back-end Developer
Contributions:28 releases, 15 reviews, 364 commits in 5 years 10 months
Contributions summary:Paco was primarily responsible for the implementation and maintenance of the core TextRank algorithm in Python, a natural language processing task involving phrase extraction. They focused on refining the algorithm's features and capabilities by adding support for stop words and a graph visualization tool. The contributions extended to extractive summarization by adding methods and data structures in code to determine and use text rank. Further contributions included code-level refactoring and improvements to internal functions.
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