AI for BusinessAI Agent Prompt Engineering for LLM Cost Detection
How do you use prompt engineering with AI agents to automatically detect when LLMs hallucinate about real-time AI model cost-per-million-tokens pricing and hidden inference surcharges across Claude, GPT-4o, Gemini 2.0, and open-source models, dynamically synthesize live pricing feeds from provider billing dashboards and third-party cost aggregators, and generate cost-transparency scored deployment recommendations with explicit pricing freshness timestamps that help enterprise teams reduce unexpected AI infrastructure costs by 60% while maintaining budget predictability for scaled production workloads in 2026?