Mar 25, 2026
Enterprises are facing an 80% failure rate for AI agents in
complex tasks because these systems lack the deep understanding
required to navigate established legacy environments and existing
internal systems. In this episode, Eran Yahav, CTO and co-founder
at Tabnine, outlines how an enterprise context engine acts as a
persistent memory and mapping layer that onboards AI systems into
specific business logic, security perimeters, and organizational
dependencies. The conversation highlights how this infrastructure
can double agent success rates and reduce token costs by 80% while
allowing technical leaders to establish swim lanes that ensure
agents operate reliably within complex software architectures. This
episode is sponsored by Tabnine. Learn how brands work with
Emerj and other Emerj Media options at go.emerj.com/partner. Want
to share your AI adoption story with executive peers? Click
go.emerj.com/expert for
more information and to be a potential future guest on the ‘AI in
Business’ podcast!