It looks like a desktop. It's a data center. Sign up, drop a file, say what you want — that's the whole setup.
Everyone landed on the same line — give the agent a computer: a sandbox, a harness, a place to run. But a computer is finite: fixed disk, one machine, memory that resets when the task ends. A finite computer doesn't remove the agent's ceiling — it moves it:
Nothing on that list is a wall here — the pieces are modular, and the ground under them is elastic. And the rails don't just hold the agent up; they make it better: credentials it can use but never read, a receipt on every run, state it can trust, an optimizer that learns from each execution. A harness gives your agent a place. Rails make it good. Better rails, better agent.
Plenty of good tools give AI somewhere to run code. This is where the work lives — files, keys, schedules, and APIs on your own private cloud, on a desktop you can watch.
Your drive isn't a disk — it's a bottomless shelf. 150 GB today, 1.5 TB next quarter: same desktop, same paths, nothing to migrate. Ever.
Every run gets a fresh machine for exactly as long as it works — one job or a thousand in parallel — then it's gone. Nothing stays on for you to maintain.
Schedules fire from the platform itself. No process stays up all night on your behalf — and it still never misses a morning.
If you've ever moved a growing project onto a bigger machine, you know the day this removes.
Run Hermes today. Try OpenClaw tomorrow. Seat the newest, best agent the day it ships — and every one of them walks up to the same desktop with everything already there. Your files, your schedules, your keys, your running products: none of it belongs to any one agent. Swap the mind. Keep the world. The system grows with you — through every agent generation.
And they can work together: two agents at one desktop share one set of information and one set of visibility — the files one saves, the next one reads; every schedule they arm lands in the same 📅 window you watch. The one room no agent enters is Keys — secrets are granted to code at run time, never readable, never printable. Secrets stay human.
One file is your scratchpad, your script, your API, and your scheduled job — promoted by a save. Try an idea at 9:02; have it running every morning by 9:04. No environment day, no deploy step. The file is the product.
Quick scripts run on a penny-a-day CPU, and small models run there too, nearly free. A 7B wakes a starter GPU for cents of actual use; the big open models get serious cards when quality is worth it. Every run picks its metal and is billed for its own seconds.
A small model for the daily grind, a big one for hard thinking, frontier brains — plugged in with one key — for the moments that matter. All at one desktop, all seeing the same files. You don't commit to a model. You commit to your work.
Every fresh machine normally repays the same cost — load the model, compile the kernels, tune the settings — and throws it all away when the run ends. SeqPU keeps it. A snapshot freezes the warmed machine — models in memory, kernels built — and wakes it in seconds. Underneath, the optimizer watches every run and starts the next one from what already worked.
Pay the heavy cost once — imports, model weights, warmed kernels — then freeze it. The next run wakes inside that state in seconds instead of booting cold. CPU or GPU, single card or many. Save is a real execution technique, not a cache.
The learning optimizer observes each execution across workload, hardware and state, measures what actually helped, and starts future runs from better learned settings instead of rediscovering them mid-request. Eight months, thousands of runs.
A better model, a cheaper GPU, a new provider — plug it in and the workspace doesn't move. Every swap is just another comparison the engine learns from. The building stays; the occupants change.
The primitives underneath get cheaper, faster and better. SeqPU gets more valuable as they do.
[REDACTED]Twelve tools. One desktop. AI writes the software now — this computer runs it, and you're billed only for the seconds it works.
A file becomes a product. Publish it as a headless API or a UI app and it lands in Applications — then it opens with a click, answers a POST, gets wielded by your agent, fires on a schedule, or talks to a bot. Five doors, one file. Edit its code or its interface in place; every caller keeps working. Chain tools into a system with one entry point. It isn't a demo — it's a product operating itself on your infrastructure, billed by the second, receipts attached.
We're here to build. Bring the ambition — the computer's already on.
Every run reports its duration and its exact cost. No estimates — settlements.
Move a file a schedule depends on. The next run refuses — and tells you the fix:
No firing into a void. The schedule waits, grey, until you hit Resume.
Vault values are write-only. Your scripts use them; no output can print them.
We earn on the meter, not the markup — a small slice of the work that flows through, so we're never rooting for the expensive path.
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