AI Stack & Token FinOps Audit Sheet
Printable 1-page due diligence checklist to audit LLM token consumption, model tier routing, prompt caching, and API key security.
AI STACK ARCHITECTURE & FINOPS AUDIT
Inference Optimization, Prompt Caching & Security Protocol • 2026 Edition
Project / App
__________________
Primary LLM Tier
GPT-4o / Claude 3.5
Fallback Model
DeepSeek V3 / Flash
Monthly Token Budget
$ ________________
1. Model Tiering & Cost Routing
Semantic Router: Simple classification routed to Flash/Haiku (90% cheaper).
Complex Reasoning: Frontier models reserved strictly for multi-step reasoning.
Fallback Strategy: Automated failover if frontier provider rate-limits or 503s.
Self-Hosting Check: Local Ollama/vLLM evaluated for batch offline tasks.
2. Prompt Caching & Token Optimization
Prefix Caching: System instructions and few-shot examples pinned at prompt start.
Token Trimming: Removed redundant formatting pleasantries from system prompts.
Max Output Limits: Hard token caps set per response to prevent runaway loops.
Structured JSON: Enforced JSON schema mode to prevent conversational preamble.
3. Retrieval-Augmented Generation (RAG)
Chunking Strategy: Recursive character chunking (500–1000 tokens with overlap).
Embedding Model: Cost-efficient embeddings utilized (e.g. text-embedding-3-small).
Reranker Active: Cross-encoder reranks top 5 results to minimize context clutter.
Vector DB Pruning: Expired or redundant vectors purged to control storage fees.
4. API Security & Rate Guardrails
Secret Rotation: API keys stored in environment secrets (never client-side JS).
Hardware 2FA: Developer accounts protected via YubiKey hardware security keys.
Hard Spend Caps: Account-level billing limits configured to stop billing shock.
Injection Defense: User inputs sanitized against prompt injection jailbreaks.
Generated by AITools.yield • AI FinOps & Token Optimization Suite.
AI Stack Protocol 2026
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