Start from the problem on your desk.

Tie the increase to what the company is actually using, down to the function.

Find the step where the wait happens before you grow the estate.

Where there is pressure, where there is slack, and what a purchase would actually buy.

What a service costs today, how it behaves, and what it must keep delivering after the move.

Measured demand next to the team's assumptions, before the peak.

Each finding tied to the service it affects, and priced.

After the response, which points need a second look, and in what order.

Current cost, expected benefit and the cost of change, each with its proof.

Function by function into memory-safe Rust, verified against production before anything ships.

Hotspots ranked by cost, agents behind one permission boundary, receipts before anything deploys.

Content-addressed kernels pinned to trust pools: shadow, canary, primary, rollback, on AWS, Azure, Google Cloud, your hypervisor or bare metal.

Cost per token, GPU utilization per node, a backtested forecast and placement per run, before the next purchase order.