I speak about the operational side of AI that often gets overlooked—from annotation quality and evaluation systems to taxonomy design and the human workflows that make reliable AI possible.
Format: Hands-on Python workshop
Community: Data Operations IL
Description: Early version of a practical workshop for building scalable, high-quality LLM-based data labeling workflows.
Availability: Recorded and available online.
Format: Podcast guest episode
Show: Data & AI with Mor Nitzan
Date: December 2025
Description: Conversation about human and LLM labeling, taxonomy design, and semantic layers in production data workflows.
Format: 5-minute lightning talk
Event: hayaData 2025
Description: Three key takeaways for building an LLM-based data labeling workflow that scales without sacrificing quality.
Event: Data TLV 2025 conference
Co-speaker: Liz Polansky
Description: How to design a data annotation operation from the ground up, from staffing and workflow design to governance and quality controls.
Also presented at: Code Mavens online meetup (recorded version).
Events: Data TLV 2024 and PyWeb meetup (March 2025)
Description: A practical walkthrough of data quality tooling, including many methods and techniques that are difficult to discover through generic search.
Focus: Turning quality practices into operational systems that teams can actually run and maintain.