Expert by Prompt: How Specialized Subagents Solve the Massive Codebase Problem

As AI assistants navigate multi-million-line codebases, their generalist approach becomes inefficient—each domain switch wastes tokens on redundant exploration and learning. Metabase's strategy of custom subagents with pre-loaded domain knowledge eliminates this overhead, preserving context for productive work. This approach signals a broader architectural shift: enterprise teams will increasingly compose specialized AI agents rather than rely on single generalist models for complex systems.