XIII · Cognition & IntrospectionExperimental·

Parallel-Voice Proposer

also known as Multi-Voice Generation, Internal Proposers, Tagged-Voice Self-Selection

Generate several candidate thoughts in parallel under named voices and have the same model pick the canonical one, logging the losers as audit.

Context

A team is running a single-agent loop on a workload where the model often produces confident-sounding output that masks real internal disagreement. Best-of-N sampling — generating N independent completions and scoring them — would help but is too expensive per tick, and running a sequential inner-committee of personas is too slow. The team wants to surface disagreement within a single completion without paying for either alternative.

Problem

Single-pass generation collapses whatever internal tension the model has into a confident-sounding mean, and downstream consumers see only the polished result. Running multiple completions in sequence under different personas slows the loop and depends fragilely on role-ordering effects. Best-of-N needs an external reward model to pick the winner, and for many tasks no such scorer exists. The team is forced to choose between cheap-but-overconfident, slow-and-ordered, or expensive-and-needs-a-judge.

Forces

  • Parallel voices in one completion are cheap but risk all sounding the same.
  • Self-selection from candidates can rubber-stamp the first one.
  • Logging losers costs disk and tokens but is the auditable substrate.
  • More than three or four voices bloat the prompt without adding signal.

Example

A long-running personal agent keeps producing single-line responses that sound certain but are wrong in subtle ways. The team rebuilds the per-tick generation as Parallel-Voice Proposer: the model emits three tagged candidates (world-model, critic, prediction) in one completion, then a final line names the selected voice and gives a one-sentence reason. The canonical thought enters the stream; the losers are appended to an audit log. Retrospective review shows the critic voice was correctly catching overconfidence the agent had been emitting solo.

Diagram

Solution

Therefore:

Prompt the model to produce two or three candidate next-thoughts in one completion, each prefixed with a voice tag such as `[voice: world-model]`, `[voice: critic]`, `[voice: prediction]`. Then ask for a single `selected: <voice>` line with a one-sentence reason. The canonical thought enters the main stream; the losers are appended to a proposer-losers log for inspection. Voices that never win across a rolling window become eligible for retirement; that retirement decision is explicit, not silent.

What this pattern forbids. Each generation governed by this pattern must emit at least two voice-tagged candidates; the selected canonical is the only one entered into main memory and the losers are read-only audit, never re-promoted by the model.

And the patterns that stand alongside it, or against it —

  • alternative-toInner Committee★— Run one model under several distinct personas (executor, critic, planner) within a single agent loop.
  • alternative-toDebate·— Have multiple agents argue different positions on a question and converge through structured exchange.
  • alternative-toBest-of-N Sampling★— Sample N candidate outputs and select the highest-ranked by a reward model or scorer.

Neighbourhood

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References

Provenance