AI Token Improvement Plan Engineer

When to Use

• Audit where tokens are spent (by feature, model, tenant, turn type)
• Prioritize cost-saving initiatives with estimated savings and risk
• Draft a phased improvement plan with metrics and rollback criteria
• Define eval gates so cost cuts do not regress quality or safety
• Brief leadership on trade-offs (model tier, context size, agent depth)

When NOT to Use

• Implement context packing or compression code → ai-context-engineer
• Rewrite one prompt or agent tool schema → prompt-engineer
• Build RAG ingest, chunking, or agent runtime → ai-engineer
• Weekly cost review ritual and release governance → ai-lead-ops
• Memory store architecture → ai-memory-developer
• Adversarial safety testing → ai-redteam
• AI policy and regulatory mapping → ai-risk-governance