The "1-megawatt rack" framing is the wrong unit of analysis. The underlying constraint is that agentic AI workloads no longer behave like batch compute: they run at sustained peak power, not average power. Power delivery infrastructure sized for average load is now a validation failure mode, not a design choice. The OCP Mount Diablo project (Google, Meta, Microsoft collaborating within OCP's Diablo framework) is trying to standardize the response (cooling, high-voltage DC delivery, rack infrastructure) before every hyperscaler re-invents the same solution and every rack vendor has to support twelve incompatible power delivery specs.
The hardware validation implication is direct. Power integrity analysis on server boards has traditionally operated against a transient or burst model: how does the board respond to a peak, then recover? That model breaks when the workload is always at peak. Teams designing for AI inference racks now need to validate against sustained, not burst, power profiles. The testing methodology (scope setups, PDN models, thermal runaway margins) is not the same as burst validation, and most frameworks in use today were not built for it.
Teams designing hardware for hyperscaler deployment have 12-18 months before 1-MW rack specs harden into procurement requirements. The OCP Mount Diablo timeline is the forcing function. Designs that miss the power delivery and thermal assumptions baked into that spec face re-spin cost, not a software patch.