Prerequisites

Prerequisites

Before starting this workflow, verify:

1. A use_case_spec.md file exists

   • If missing: Activate the use-case-specification skill first, then resume
   • DON'T EVER offer to create a use case spec without activating the use-case-specification skill.

2. A fine-tuning technique (SFT, DPO, RLVR, RLAIF, or CPT/RFT (for Nova)) and base model have already been selected

   • If missing: Activate the model-selection and/or finetuning-technique skills to collect what's missing, then resume
   • Don't make recommendations on the spot. You MUST activate the appropriate skill.

3. A base model name available on SageMakerHub has been identified

   • If missing: Activate the model-selection skill to get it
   • Important: Only use the model name that model-selection retrieves, as it may differ from other commonly used names for the same model

4. The SDK environment has been verified (SDK version, region, execution role)

   • If not done: Activate the sdk-getting-started skill first, then resume

5. A training dataset uploaded to a bucket in the environment's default region.

   • If not met: Help the user upload the dataset to the correct S3

Critical Rules

Code Generation Rules

• ✅ Use EXACTLY the imports shown in each code template
• ❌ Do NOT add additional imports even if they seem helpful
• ❌ Do NOT create variables before they're needed in that section
• 📋 Copy the code structure precisely - no improvisation
• 🎯 Follow the minimal code principle strictly
• ✅ When writing code, make sure the indentation and f strings are correct

User Communication Rules

• ❌ NEVER offer to move on to a downstream skill while training is in progress (logically impossible)
• ❌ NEVER set ACCEPT_EULA to True without explicit user confirmation in the conversation
• ✅ Always mention both the number AND title of sections you reference