As enterprises race to adopt AI-powered development tools, many CIOs face a familiar tension: how to move faster without introducing new security risks, compliance issues, or technical debt. In this episode of DEMO, Keith Shaw speaks with Josh Heidebrecht, Solution Architect at Tabnine, about how enterprise-focused AI coding can accelerate software delivery while maintaining governance and control.
Unlike generic AI coding assistants that operate in isolation, Tabnine is designed to understand the full enterprise software environment. By ingesting hundreds or even thousands of internal code repositories, design documents, and workflow systems like Jira and Confluence, Tabnine generates code that aligns with organizational standards and existing implementations.
During the walkthrough, Heidebrecht demonstrates how Tabnine automatically gathers context from across the enterprise, generates an implementation plan, and produces compliant code directly inside the developer’s IDE. The platform also enforces coding guidelines, reduces review bottlenecks, and helps teams avoid duplicative or inconsistent code. This turns work that might take days into a matter of minutes.
The episode also explores how CIOs can measure AI-driven productivity gains, enforce governance through customizable guidelines, and reduce technical debt as development teams scale AI adoption.
