Internal policies change every month.
Answers must use the latest policy without retraining the model after each update.
Which architecture should be considered first?
Use retrieval to fetch the current policies and pass them as context; fine-tuning is generally for behavior or format adaptation, not frequent knowledge refresh.
Detailed explanation
External documents can be updated and retrieved at inference time.
External documents can be updated and retrieved at inference time.
This is unnecessarily expensive and slow for routine document changes.
This is unnecessarily expensive and slow for routine document changes.
Length, permissions, and conflicting documents still require control.
Length, permissions, and conflicting documents still require control.
Fine-tuning does not automatically ingest future updates.
Fine-tuning does not automatically ingest future updates.
Try it yourself
An example you can run in a temporary verification environment.
Amazon Bedrock Knowledge Bases公式ドキュメントでデータ取り込み、検索、生成の流れを確認する。Expected result
更新頻度の高い知識にはRAG、振る舞いや形式の適応には微調整という使い分けを説明できる。Key points
- Knowledge freshness
- RAG
- Fine-tuning
Notes
- Environment: AWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認
- Command output formatting can vary slightly by distribution or tool version.
- Run the example in a temporary directory or process when possible.
Foundation review
Read the scope first
Check whether the command acts on the current shell, a new process, an existing process, or a file.
Verify the observable result
Use the supplied command and compare the output with the expected result.