AI models have advanced rapidly, and agents are beginning to automate real engineering tasks. Yet many organizations are discovering a hard truth: powerful models alone are not enough. Without a deep understanding of systems, architecture, and organizational constraints, AI can generate output but struggles to operate reliably in real-world environments.

In this thought leadership session, Dror Weiss, co-CEO of Tabnine, and Eran Yahav, co-CEO of Tabnine, will explore why context has become the critical missing layer in enterprise AI. They will discuss the challenges enterprises face when moving from experimentation to production, and why approaches that rely primarily on retrieving documents or fragments of code often fall short in complex environments where relationships, dependencies, and constraints matter.

The discussion will introduce the concept of the Enterprise Context Engine and the emerging idea of an organizational intelligence layer—a persistent, structured model of systems, relationships, and constraints that enables AI agents to reason about software environments and operate safely at scale.