As enterprises rush to automate with generative AI, the harder problem is no longer capability alone - it is controlling spend, limiting what the system can touch, and stopping bad output before it becomes a business decision.
As enterprises race to cut AI spend, the sharpest savings are coming from architecture choices - shorter prompts, smarter routing, caching, and selective local inference.
SpaceX’s planned purchase of Cursor is less interesting as a valuation story than as a test of whether privacy controls, model choice, and enterprise trust can survive a change in ownership.
Enterprise AI is no longer just about picking the right model; it is about controlling how prompts, context, routing, and retries turn every request into a measurable cost.
A short-lived test of Fable 5 becomes a useful lens on a bigger AI question: when several models, access tiers, and cost choices sit behind one interface, the prompt is only part of the result.