nen. The model designed for humans.
Neither built for benchmarks or for being liked. Built for the person using it.
Around it, a space for notes, tasks, habits and a logbook, to keep what matters.
October in nenspace.
The app went flat: features now sit on one ground, divided by hairlines.
Working memory backend was rebuilt using decision models and is now displayed as a unified list.
And the model improved significantly on internal benchmarks, to be released soon.
Every reply is held to three gates.
It answered the question. It said what it did not know. It held the register.
A fluent answer that misses the question still fails the first.
Disagree.
The moat is the data flywheel, proprietary feedback compounding with usage, captured by agent training platforms.
"SLMs make this sharper: when model access is becoming less distinctive, unique data and the learning system around it carry more of the advantage." 👇
