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Add an AGENTS.md (agents.md convention) and llms.txt (llmstxt.org convention) at the repo root so AI coding agents generate SageMaker Python SDK v3 code by default instead of deprecated v2 code. Both files carry a v3-by-default rule, a banned-v2-pattern to v3 replacement table grounded in migration.md, the sagemaker-core/-train/-serve/-mlops module map, a contributor workflow, and a self-check step before emitting code. --- X-AI-Prompt: Create AGENTS.md and llms.txt for the SDK repo to steer AI agents to SageMaker Python SDK v3 X-AI-Tool: Kiro
Add an "SDK-first" section (with a natural-language intent -> v3 interface table) so AI coding agents default to the SageMaker Python SDK v3 as the primary interface for SageMaker tasks, rather than dropping to raw boto3 (create_training_job/create_endpoint), the AWS CLI, or hand-rolled framework scripts. --- X-AI-Prompt: Add SDK-first (library-selection) guidance so agents default to the SageMaker Python SDK v3 without an explicit nudge X-AI-Tool: Kiro
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Recreating from current upstream master so the diff shows only the incremental SDK-first additions (branch was based on the squash-merged #5982 and diverged). |
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What
Adds an SDK-first section to
AGENTS.mdandllms.txt(both merged earlier in #5982).The prior files already steer agents from SDK v2 → v3. This change addresses a distinct
gap: when a task doesn't name the SDK (e.g. "generate training code for a SageMaker serverless
job"), agents often drop to raw
boto3(create_training_job/create_endpoint), the AWS CLI,or a hand-rolled framework script instead of the SageMaker Python SDK.
Changes
the primary interface.
ModelTrainer, deploy →ModelBuilder, process →ProcessingJob, pipeline →sagemaker.mlops, image →image_uris.retrieve).Notes
Docs-only change (
AGENTS.md,llms.txt); no SDK source touched.X-AI-Prompt: Add SDK-first (library-selection) guidance so agents default to the SageMaker Python SDK v3 without an explicit nudge
X-AI-Tool: Kiro