GitHub Copilot now supports custom model endpoints, enabling developers to route code completion requests to alternative LLMs or self-hosted models instead of GitHub's proprietary backend. This removes a critical constraint in enterprise AI tooling adoption. Organizations can now standardize on Copilot's UX and integration layer while substituting the underlying model—whether for cost optimization, data residency requirements, or control over model selection. It erodes GitHub's lock-in advantage and forces competitive pressure on model performance and pricing. For builders, this shifts the economic calculus of AI-assisted development. Teams can route requests to cheaper open-source models (Llama, Code Llama) or internal infrastructure, reducing per-completion costs. Operators gain control over model versioning and fine-tuning pipelines without IDE tool switching. The custom endpoint pattern likely becomes standard across development tooling, creating infrastructure expectations that extend beyond Copilot to other IDE integrations and company-internal tooling.