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Answers & Confidence

Uncertainty

The honest "I'm not sure" signal that lets a system defer instead of guessing, exposed through probabilities and confidence.

Category
Answers & Confidence
Also known as
—
Related terms
5
Directory entries
2
Docs
docs.typesafe.ai
Added
2026-09-24

Definition

The confidence page opens with the principle: if an intelligent system cannot express honest uncertainty, the system cannot be trusted. Calibrated probabilities are how Jev expresses it, and the middle of a Noul's range is a natural hand-off to a person.

Uncertainty is meant to be designed with, not optimized away: low confidence often means the options are ambiguous or the state lacks information, and both are signals your code can route on.

Tagsconfidencedesign

From the directory

How TypeSafe reports certainty, how it differs from probability, and how to use it architecturally to gate and route decisions.
Practices & PatternsDocs#official#confidence#routing
Official
Why TypeSafe trains decision models with RLCD instead of RLHF: calibrated probabilities where 0.2 outcomes happen about 20% of the time, and the case for machine-to-machine automation.
Sites & GuidesDocs#official#docs#evaluation
Official

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ESTA HERRAMIENTA ACABA DE ROMPER TODO EL MERCADO DEL AD SPY Maxfusion ha cogido JEV, el modelo nuevo de TypeSafe, y le ha metido la ad library entera de una marca → 1.891 anuncios clasificados → 19 segundos → 0,12 $ Y no es un resumen: cada anuncio etiquetado por etapa del Show more

Ori Silver
Ori Silver
@OriSilver

JEV makes competitor research feel like a cheat code We fed it Resilia’s ad library and it classified 1,891 ads in 19 seconds for $0.12 Customer journey stage, ad style, and a full account deep dive Coming soon to the maxfusion MCP

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