Run the AI spend audit in AgentaaS OS. API call logs aggregated over 30 days show 847 million tokens consumed across 6 models. The top cost driver is GPT-4 Turbo (512M tokens, $153,600). Claude 3 Opus accounts for $48,000 (160M tokens). Gemini Ultra: $28,800 (96M tokens). 40% of calls are from Jupyter notebooks that were never promoted to production.
Cost Optimizer: model tier matching for experiments reduces monthly spend from $240K to $144K. Production models (GPT-4 Turbo) remain unchanged. Experiment models forced to Haiku and GPT-3.5.
The audit shows 40% of spend ($96K) is from experiment notebooks using frontier models. What is the highest-ROI immediate action?
Hint: AI FinOps: match model capability to task maturity. Experiments use small models; production uses the right model for the job.