An Agent shouldn't be locked to a single LLM provider. Different tasks suit different models — simple questions use cheap models, complex reasoning uses expensive ones, and some scenarios even require local models. Runtime needs change too: users might want deeper thinking mid-session, discover the budget is running low and need to downgrade, or switch to a local model to save money. Open Agent SDK's approach: define a unified LLMClient protocol, with Anthropic and OpenAI-compatible providers each having an implementation. Internally, the Agent uses Anthropic format throughout. Switching providers requires changing only one configuration parameter, and models can be switched dynamically at runtime with adjustable thinking depth and budget control. This article analyzes the SDK's multi-provider adaptation mechanism and runtime control capabilities. 1.…