04

Compute capacity is fragmented across people

The company simultaneously has paid, unused capacity and tasks waiting for someone else’s quota to reset.

One team, two opposite problems
Developer A
limit
Developer B
idle
Artist
wrong service

A personal subscription is often a bundle of mismatched capabilities. A programmer uses Codex but barely touches the powerful web model or image generation. An artist needs image generation but not a coding agent. One person hits a weekly limit while another uses less than half of the capacity the company paid for.

A centralized pool would change the unit of planning itself: compute would be assigned to a task for as long as needed. Running a benchmark set on Kimi once a week would not require a monthly subscription for a particular employee. The team could see its total shortage and idle capacity, then buy resources for the actual workload.

A shared compute budget changes the scale of experiments a team can attempt. The team can test major technical hypotheses not because it knows the outcome in advance, but because the cost of testing has become acceptable. For example, it could temporarily rewrite a Java server in C#—not for an immediate release, but to measure speed, memory use, and maintenance complexity. Such an experiment is often blocked not by engineering difficulty, but by reluctance to burn through a personal quota.