Vibe modeling

AI coding assistants like "vibe coding" are gaining popularity, but their limitations are quickly becoming apparent for enterprise-grade data science.

Relying on code authoring alone fails to address the full ML lifecycle, which includes data discovery, validation, and training—the parts that are often the most labor-intensive. Furthermore, without a robust platform, you face significant challenges in ensuring reproducibility and lineage, which are critical for effective collaboration and governance.

This webinar will explore vibe modeling, a new, comprehensive approach that addresses the shortcomings of pure coding assistants.

Watch this session to learn:

• Why the traditional focus on "vibe coding" is insufficient for enterprise AI
• Why a model-first workflow is essential for delivering real-world value.
• How to extend your existing IDE and tools to manage the entire end-to-end data science lifecycle to increase productivity and reduce overhead.