kaxil opened a new pull request, #73902:
URL: https://github.com/apache/airflow/pull/73902

   Teams with a Pydantic AI agent of their own had no guide: the docs covered 
`AgentOperator` and assumed the operator runs the agent. The new Pydantic AI 
page shows the model from `PydanticAIHook.get_hook(...).get_conn()`, the same 
vendor handling `AgentOperator` uses, and the provider's toolsets passed 
straight to the agent. It lists what `AgentOperator` adds on top: durable 
replay, human review and tool-call approval, masking for the Agent Skills 
toolset and your own toolsets, templated connection IDs, and tool logging with 
the task's identity on spans. For spans, it points to the hook's 
`create_agent`, which instruments the agent the way `AgentOperator` does, with 
prompt text off by default.
   
   The sandbox guide now shows a Strands agent owning its sandbox's life with a 
`with` block.
   
   This is the top of the native agent framework stack; nothing else depends on 
it.
   
   
   ---
   
   * Read the **[Pull Request 
Guidelines](https://github.com/apache/airflow/blob/main/contributing-docs/05_pull_requests.rst#pull-request-guidelines)**
 for more information. Note: commit author/co-author name and email in commits 
become permanently public when merged.
   * For fundamental code changes, an Airflow Improvement Proposal 
([AIP](https://cwiki.apache.org/confluence/display/AIRFLOW/Airflow+Improvement+Proposals))
 is needed.
   * When adding dependency, check compliance with the [ASF 3rd Party License 
Policy](https://www.apache.org/legal/resolved.html#category-x).
   * For significant user-facing changes create newsfragment: 
`{pr_number}.significant.rst`, in 
[airflow-core/newsfragments](https://github.com/apache/airflow/tree/main/airflow-core/newsfragments).
 You can add this file in a follow-up commit after the PR is created so you 
know the PR number.
   


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