AI / ML Best Practices

Patterns and conventions for building reproducible, reliable, and responsible AI/ML systems at Stratpoint.

Reproducibility

[To be filled by Capability Lead]

Placeholder sections:

• Seed management
• Environment pinning
• Data versioning

Data Management

[To be filled by Capability Lead]

Model Evaluation

[To be filled by Capability Lead]

Responsible AI

[To be filled by Capability Lead]

Placeholder sections:

• Bias and fairness evaluation
• Model explainability
• Privacy-preserving ML

LLM-Specific Practices

[To be filled by Capability Lead]

Placeholder sections:

• Prompt versioning and testing
• Hallucination mitigation
• Token cost governance

ML System Reliability

[To be filled by Capability Lead]

Security

[To be filled by Capability Lead]

Placeholder sections:

• Model theft and adversarial inputs
• Data poisoning prevention
• API key and credential hygiene