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This tag gathers mini classes around one specific topic. Start with the newest post, then use categories and related reading for context.
Model prices keep falling, yet long AI tasks still bring surprise bills. The money goes to resending context and rerunning failures, so the limit belongs in code outside the model, as one budget per task.
AWS FinOps Agent traces cloud cost spikes to the change behind them, but its named owner is only as good as your account-to-owner map. Write the map first, then route findings.
Apple raised Mac and iPad prices as AI data centers soak up memory. Your needs didn't change; upgrading for future AI just got pricier. Start from the work your device blocks each week.
In 2026, companies burned through yearly AI budgets by midyear. Model prices don't explain it; real cost includes retries, input size, and fix-up time. Track cost per accepted result first.
NVIDIA's RTX Spark brings Arm CPUs and up to 128GB of memory to Windows laptops for local AI. On Arm, your apps, plug-ins, and drivers may not run natively. Check your tool list, then test a real task.
Copilot bills by usage from June 2026: completions stay free, chat and agents cost, with no cheap-model fallback. Decide whether to stop or pay when credits run out, and who gets the priciest mode.
Glean passed $300M in ARR pitching lower AI bills. Savings count only if an old cost can be canceled on a set date or a measurable work metric drops; anything else is an experiment cost.