The $20-a-month AI Party Is Almost Over. Remember when Uber rides were cheap? That ended when venture capital stopped subsidizing your commute. Prices are up roughly 90% since 2018. AI is on the same path. OpenAI loses money on its $200/month plan. Anthropic added usage caps to Claude Code. Perplexity rolled out its own $200 tier. These are not random pricing tests. They are corrections. The math was always fragile. Every prompt burns real compute. This is not SaaS, where you build once and scale cheaply. Costs rise with usage. The subsidies that hid this reality are thinning out. Expect the shift in the next 18 to 24 months. The $200-a-month users are not the solution for companies. They are doing exactly what the pricing invites. Unlimited plans attract heavy users. Heavy users consume far more compute than the fee covers. Losses are baked in. The pressure lands downstream. Anything built on top of OpenAI or Claude APIs faces a hard choice. Raise prices sharply or shut down. Many AI tools will not survive that squeeze. There is a smarter move right now. Stop tying your workflow to one model. Platforms like Genspark, Notion AI, Abacus AI, and OpenRouter let you switch models without rebuilding everything. When one gets expensive, you pivot. Even better, learn pay-per-use with API keys. Most tasks do not need top-tier reasoning. Cheaper models handle the bulk of the real work; route simple tasks to Llama or Mistral. Reserve the expensive models for decisions that actually matter. This is the cheap era. It is temporary. At the same time, efficiency gains, smaller task-specific models, and open-source alternatives are pushing costs down in pockets of the stack. The real challenge is not higher prices alone, but volatile pricing that makes planning, budgeting, and product design harder. The teams building model-agnostic systems now will adapt quietly when prices rise. What’s your plan if your AI stack costs 3x more next year?