Every AI inference is a mind that’s used once and thrown away.

75% of inference is redundant. $67 billion burned annually recomputing answers that already exist. 337 TWh of energy wasted. And the industry’s answer is to build bigger models and burn more compute.

That’s not a scaling strategy. That’s a bonfire.

The Mythos Stack is built on a different premise — that inference has a lifecycle. Reasoning can be captured, governed, reused, and compounded. Pre-Inference and Inference Recycling don’t optimize how fast you burn compute. They eliminate the need to burn it again. OPEX becomes CAPEX. Every inference becomes an asset. Every reuse is ROI.

This isn’t incremental. It’s a reclassification of how the entire AI economy works.

What to expect:

This Substack is where I build that case in public. Weekly posts — typically Tuesdays — covering inference economics, the lifecycle of intelligence, infrastructure architecture, sustainability, and the occasional founder dispatch from the front lines of a paradigm shift. Always free.

Who this is for:

Venture capitalists, investors, and partners evaluating where AI infrastructure is actually headed. Architects, developers, and designers building the next generation of intelligent systems. Academics, researchers, and writers thinking critically about AI’s economic and environmental trajectory.

If you believe compute should compound instead of combust — subscribe.

Brian Price

ambientagentics.ai

Originally published at https://open.substack.com.