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The language exists because AI workflows repeat the same control patterns.

Confidence

probable<T> represents a value with confidence metadata, and every probable value records where its number came from: a Jev judgment, the model’s own self-report, a value you supplied, or unknown. An unknown confidence never passes a gate. A plain ask() reply is unmeasured, so its confidence is unknown. For a real probability, ask Jev with judge(...) and convert a choice answer with to_probable():
The compiler warns (ANLY004) when a gate checks an ask() value, because that gate can never pass.

Context budgets

ctx makes token windows explicit.

Budget fallback

within budget expresses controlled degradation.

Semantic routing

match similar routes by meaning rather than keywords.

Agents

Agent primitives express lifecycle directly.

Memory, tools, and errors

Voss also includes memory primitives, @tool definitions, prompt classes, try/catch, and use imports.

Coordination constructs

The same language scales from one agent to a whole team. These constructs declare an engineering organization — roles, culture, gates, and memory — as compiler-checked config.
The goal is AI workflow control and team coordination, not Python syntax parity.