probable<T>
Confidence belongs in the type system
Model calls return values with confidence attached. Gates like `intent @ 0.80` make trust explicit instead of burying it in app code.
Language
AI patterns as syntax.
Voss is a small AI-native language that compiles to readable Python. The core move is turning recurring AI workflow code into explicit constructs the compiler and runtime can reason about.
agent Classifier {
ctx(token_budget: 1000) {
intent = ask "Classify this request" probable<string>
if intent @ 0.80 {
return intent.value
}
fallback "unknown"
}
}The five constructs.
These are the pieces Voss treats as first-class instead of framework convention.
ctx
Prompt windows are scoped resources
Context blocks define token budgets, inputs, compression, and eviction as part of the program structure.
match similar
Semantic routing is declarative
Route by meaning with embedding indexes prepared ahead of runtime, not by sprinkling ad hoc similarity calls through handlers.
within budget
Cost limits are control flow
Budgets and fallbacks are explicit language constructs, so overruns have a designed path instead of a surprise bill.
spawn / gather
Agents compose like concurrent tasks
Parallel agent work, timeouts, and fallbacks are written directly, with the runtime owning lifecycle and coordination.