VI · Multi-AgentEmerging★

Heterogeneous-Model Council with Synthesis Judge

also known as Multi-Architecture Council, Decorrelated-Model Judge

Three or more role-specialized personas run on different model architectures in parallel; a synthesis judge — given only their structured JSON, not the original input — produces the final verdict.

This pattern helps complete certain larger patterns —

  • specialisesVoting-Based Cooperation★— Finalise a decision across multiple agents by collecting and tallying their votes on candidate options, so the joint output reflects collective rather than single-agent judgement.
  • specialisesParallel Fan-Out / Gather★— Multiple independent agents execute in parallel on a partitioned task; a dedicated aggregator agent reconciles their results into a single output.

Context

A team uses a council/voting pattern for high-stakes decisions. Council members all run on the same model, so their errors correlate. The judge sees both the council outputs and the original input, allowing bias from the input to drive the verdict.

Problem

Same-model councils give correlated errors — a hallucination one model makes is likely to be made by clones of the same model. Judges that see the original input can drift toward their own interpretation, ignoring the council's signal. Distinct from voting-based-cooperation by mandating heterogeneous models AND blind judge.

Forces

  • Heterogeneous models are more expensive to operate (multiple vendor relationships).
  • Blind judge cannot apply input-specific judgment, which sometimes is warranted.
  • Structured-JSON exchange constrains what council members can express.

Example

A drawing-feedback agent: Technician (vision model from vendor A) judges technical execution, Storyteller (vision model from vendor B) judges narrative, Coach (vision model from vendor C) judges progress vs prior work. Each emits {dimension, score, evidence}. Judge (text-only model, never sees the image) takes 3 JSON outputs and produces final verdict. A geometry hallucination by Technician does not correlate with Storyteller's narrative reading; judge sees disagreement and downweights.

Diagram

Solution

Therefore:

Council of N (typically 3) role-specialized personas, each on a different model architecture. Each produces structured JSON output per a fixed schema. A judge — different model again, blind to original input — synthesizes from JSON only. Errors decorrelate across model families; judge cannot drift from council signal. Pair with voting-based-cooperation, llm-as-judge, parallel-fan-out-gather.

What this pattern forbids. Council members must run on architecturally distinct models; the judge must not see the original input; only structured JSON flows from council to judge.

The smaller patterns that complete this one —

  • generalisesParallel Fan-Out / Gather★— Multiple independent agents execute in parallel on a partitioned task; a dedicated aggregator agent reconciles their results into a single output.

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

  • complementsLLM-as-Judge★★— Use an LLM to score open-ended outputs against rubric criteria when no exact-match metric applies.
  • complementsCross-Reflection★— Reflection step performed by a *different* agent or foundation model from the original generator, so critique error is decorrelated from generation error.
  • alternative-toInner Committee★— Run one model under several distinct personas (executor, critic, planner) within a single agent loop.

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References

Provenance