ai-ml-landscape - AI/ML Landscape Practitioner Reference

What this skill does

• Compare hosted and open-weight models
• Recommend model routing strategies
• Design RAG and agent patterns
• Select tabular ML methods
• Explain transformer and attention architectures
• Plan LLM training and fine-tuning
• Evaluate benchmarks and model quality
• Advise on AI governance compliance
• Select inference hardware and serving

Inputs

• Use case requirements
• Model capability requirements
• Privacy and data residency constraints
• Cost and throughput targets
• Fine-tuning data
• Evaluation criteria
• Deployment hardware context
• Governance requirements

Outputs

• Model selection recommendations
• Architecture guidance
• Routing strategy recommendations
• RAG and agent design guidance
• Fine-tuning strategy guidance
• Inference serving recommendations
• Benchmark interpretation
• AI governance guidance

Requirements

Source

• Spec: SKILL.md