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Allen Institute releases TutorMoments framework evaluating LLM ability to balance pedagogical scaffolding and cognitive rigor in math tutoring Research publication
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TLDRocket
7 August 2026
The shine is coming off tokenmaxxing. After burning through its entire 2026 AI budget in months by encouraging reckless token consumption, Uber's CTO declared the era of excessive inference spending over, signaling a broader industry reckoning. Companies from Accenture to Uber discovered the hard way that unlimited API access breeds inefficiency—PDFs converted to images, then to markdown; non-engineers treating LLM queries like free compute. The solution isn't restriction but optimization: better prompt caching, smarter routing, cost-per-token metrics. Yet this creates a darker arithmetic: as inference gets cheaper, total spending may not fall at all. Uber quadrupled AI tool adoption while cutting per-token costs, but the Jevons paradox lurks—efficiency breeds proliferation, and proliferation breeds cost creep.
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