The local-first compute thesis treats placement as a human decision as well as a scheduler decision: stay local when latency or privacy makes that right; propose a temporary burst only when the task earns it. It is a design target, not a shipped control plane in this repository.
Jointly optimize latency, energy, memory pressure, cost, and consent while giving the owner a reason they can understand and override.
The same person may have an on-device model, a Mac, a desk system, and a cloud account. A scheduler that only sees FLOPS cannot decide whether moving the work is acceptable.
The local-first compute ladder and hu_ssh transport are published research/reference design. This repository does not contain the placement engine, provider, credential vault, burst API, job store, or macOS agent.
Primary source: Private Agent One heterogeneous-supercompute dossier
Build a placement simulator first. Compare resource-only policy, privacy-first policy, and owner-overridable policy on the same trace before provisioning any cloud resource.
The companion essay is written for a broader technical audience. The repository and developer community are the places to turn a claim into a contribution.
One is made by Hushh Technologies Corporation: private, sovereign AI that runs on what you own.
One is made by Hushh Technologies Corporation: private, sovereign AI that runs on what you own.