Sourcegraph Cody for enterprise teams managing large complex codebases is genuinely different from IDE plugins

Developers and enterprise teams managing large, complex codebases are the target. The primary strength being project-wide reasoning across millions of lines of code rather than file-level or repository-level context is the technical differentiation. An AI assistant that understands how a service interacts with five dependent services across three repositories is answering questions that a file-scoped AI cannot answer at all.

The enterprise focus meaning the evaluation question is not personal productivity but team productivity at codebase scale is the frame that changes which metrics matter. How much faster an individual developer writes a function is less important than how much faster they can understand how a change will affect the broader system.

The deep codebase understanding enabling accurate answers about why specific architectural decisions were made, which code handles a given business requirement and what the downstream effects of a proposed change would be is the institutional knowledge retrieval that changes new developer onboarding significantly.

For engineering leads at organisations with large codebases: how much time do new developers currently spend on codebase orientation before they can contribute confidently and would Cody's cross-repository context change that timeline?