The Edge
The whole thing runs on a
$250 computer.
Not a cluster. A single board on a desk, running an agent that wakes itself up and works while nobody is watching. The interesting engineering is what fits, not what scales.
Why a small machine is the point
An agent that lives on hardware you own has properties a hosted one cannot have. It keeps working when the internet doesn't. Its memory is a file on your disk rather than a row in someone else's database. And its running cost is electricity.
The constraint is also the research programme. Making a capable agent fit in 8 GB forces the questions that matter — what does it actually need to remember, which decisions need a large model and which need a small one that answers in milliseconds.
The distillery
Most of what an agent does every hour is reflex, not reasoning: classify this, route that, decide whether this is worth waking up for. Those calls do not need a hundred-billion-parameter model, and paying one to make them is the largest avoidable cost in the whole system.
So we distil specialists — small models trained on one bounded job, certified on the device they run on. The benchmark artifacts are their first publications, and the method is the product: we show the runs, the seeds and the failures.
Caveat — distillation targets reflexes, not judgement. Anything requiring actual reasoning still goes to a frontier model, and we say which did what.
Read the work
The field notes are the research wing — written up in full, including the runs that disagreed with each other.
Field Notes →The product side
The same intelligence, pointed at your errands and your inbox instead of a bench.
repryntt Bot →