I've found that hybrid AI infrastructure offers the best balance for many engineering teams. Local or self-hosted models can handle repository context and sensitive code, while cloud models are useful for more complex reasoning when appropriate.

The deployment model matters, but repository awareness and how well AI fits into the SDLC often have a bigger impact on developer productivity than where the model runs.