In scope: generation (nuclear, gas, renewables), PPAs and offtake, grid interconnect queues, power arbitrage, energy ownership as a moat, transformer and switchgear lead times, energy cost pass-through. Out: the buildings themselves (datacenters), the cost of a token (inference-economics).
This rung has no compiled overview yet. Until it does, the base is best read across the stack rather than down one rung.
Start here
- 01LLM Inference Prices Have Fallen Rapidly but Unequally Across Tasks
Start at the number the whole base chases: what a token costs, and how unevenly that price has actually fallen.
inference-economics - 02Memory-Centric Computing: A Paradigm Shift for Sustainable and Efficient Systems
The reason the price falls the way it does — the bottleneck is moving data, not doing arithmetic on it.
hardware - 03AI Hyperscaler Capex 2026: Why Microsoft, Google, Meta and Amazon Are All Spending at Once
Where the money physically lands once the bottleneck is priced: buildings, land and power, committed years ahead.
datacenters - 04Speculative Decoding Meets Quantization: Compatibility Evaluation and Hierarchical Framework Design
How the cost is actually cut in software, and what the two cheapest tricks do to each other when you stack them.
serving - 05Agentic Reasoning for Large Language Models
The demand side: the systems wrapped around the model are what decide how many tokens the price applies to.
harnesses