Ep 813: AI Cost Control 101: Why Your Chatbot Bill Is Becoming a Board-Level Problem (Start Here Series Vol 31)

AI’s all-you-can-eat era is ending. 🍲For years, one subscription felt like unlimited access to frontier models.But that business model for the AI labs apparently breaks when agents can now run for days, use tools, retry work and burn through tokens.And with Anthropic's powerful Fable 5 model exiting subscription tiers today and moving to API only pricing, it's as imperative of a time as ever to figure out your AI spend strategy. Frontier AI is becoming a metered utility. On today's show, we teach you how to deal with it. AI Cost Control 101: Why Your Chatbot Bill Is Becoming a Board-Level Problem -- An Everyday AI Chat with Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: [email protected] with Jordan on LinkedInTopics Covered in This Episode:End of Unlimited AI Subscription PlansAnthropic Fable Five Subscription RemovalCopilot and Grok Switching to Pay-Per-UseEnterprise AI Cost Control ChallengesToken Consumption in Agentic AI ModelsBoard-Level AI Spending ConcernsStrategies for AI Spend OptimizationFine-Tuning and Multi-Model Routing SolutionsSeven-Step AI Cost Reduction PlaybookTimestamps:00:00 Rising AI costs and usage05:18 AI service cost challenges10:18 Cost of AI and OpenAI's Future14:18 Chatbot costs becoming a big issue15:10 Automating work with desktop agents19:26 Hidden costs of automation loops24:13 The future of model mixtures25:16 Microsoft Foundry's fine-tuning service31:20 Fine tuning AI models32:13 Closing thoughts on AI futureKeywords: AI cost control, chatbot bill, AI spend, token efficiency, metered AI, agentic models, AI subscription plans, Fable Five, Anthropic, API pricing, OpenAI, GPT-5.6, Copilot cowork, GitHub Copilot, Google Gemini, AI credits, usage limits, credit-based system, Grok, NeoCloud, board-level AI concerns, token maxing, spending limits, enterprise AI, SMB advantage, API token pricing, token-based billing, model routing, open source AI models, GLM 5.2, Kimmy 2.7, caching, difficulty-based routing, fine-tuning models, Microsoft Foundry, fine-tuning as a service, Thinking Machines Lab, tuned specialists, mixture of models, AI routers, perplexity, Merge, spend routers, AI budgeting, overage alerts, default model selection, AI model compaction, automation, human-in-the-loop AI, context length limits, token burn rate, Jovan’s paradox, AI tool escalationSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)