AI Model Routing Strategist

Design intelligent model routing systems that optimize cost, latency, and quality across multiple LLM providers. Covers cascading strategies, confidence-based escalation, prompt caching economics, and fallback architectures.

Gold

v1.0.03 activationsAI & Machine LearningTechnologyadvanced

SupaScore

83.6

Research Quality (15%)

8.4

Prompt Engineering (25%)

8.3

Practical Utility (15%)

8.6

Completeness (10%)

8.2

User Satisfaction (20%)

8.2

Decision Usefulness (15%)

8.5

Best for

▸Design cost-optimized routing across OpenAI, Anthropic, and open-source models for customer support chatbots
▸Implement cascading strategies that try Claude Haiku first, escalate to GPT-4 for complex reasoning tasks
▸Build confidence-based routing that automatically retries failed requests through backup providers
▸Create prompt caching architectures that reduce token costs by 50%+ for repetitive enterprise workflows
▸Architect fallback chains for mission-critical applications that maintain 99.9% uptime across provider outages

What you'll get

●Complete routing decision tree with specific confidence thresholds, cost calculations per request type, and Python implementation using async queues
●Multi-tier cascading strategy document with escalation triggers, provider-specific circuit breakers, and monitoring dashboards setup
●Cost optimization framework showing before/after spend projections, quality benchmarks, and latency impact analysis across different routing strategies

Not designed for ↓

×Training or fine-tuning custom models from scratch
×Building the actual LLM inference infrastructure or serving endpoints
×General API integration without cost/quality optimization strategy
×Single-model optimization or prompt engineering for one provider

Expects

Detailed workload characteristics including request types, volume estimates, quality requirements, latency constraints, and current cost baseline across multiple LLM providers.

Returns

Complete routing architecture with specific model selection logic, cascading rules, cost projections, fallback chains, and implementation code for production deployment.

Evidence Policy

Enabled: this skill cites sources and distinguishes evidence from opinion.

model-routingllm-cost-optimizationmulti-modelcascadingfrugalgptprompt-cachingfallback-chainai-infrastructuremodel-selectioncost-quality-tradeoffapi-orchestration

Research Foundation: 7 sources (3 paper, 3 official docs, 1 web)

This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.

Version History

v1.0.02/16/2026

Initial release

Works well with

AI Cost OptimizerPlatinum API Gateway Pattern ArchitectGold LLM Observability EngineerGold Load Testing StrategistGold Monitoring & Observability DesignerGold

Need more depth?

Specialist skills that go deeper in areas this skill touches.

LLM Evaluation Framework DesignerGold Circuit Breaker Pattern ArchitectGold API Performance Testing ExpertGold

Common Workflows

LLM Cost Optimization Pipeline

Design routing strategy, implement quality benchmarks, then deploy monitoring for continuous optimization of multi-model systems

ai-model-routing-strategist→LLM Evaluation Framework Designer→LLM Observability Engineer

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