llm-council

You can achieve multi-model architecture decision-making by initiating a planning task where up to four models independently generate plans, which are then anonymized, judged, and synthesized into a final proposal with reasoning.

Anonymous judging in cross-model AI collaboration evaluates architecture plans based strictly on merit rather than model identity, ensuring the final decision is unbiased and selected or merged from the best independent approaches.

You need parallel model execution for major architectural decisions such as data pipeline design, service decomposition, or cross-model risk analysis, where diverse input and independent plan generation are required.

You synthesize independent architecture plans through an anonymized judging process that evaluates parallel model outputs, either combining the best elements or selecting the optimal plan, and presents the final architecture with reasoning.

Yes, you can use multi-model planning for service decomposition decisions; it utilizes parallel execution by multiple models, anonymized evaluation, and final plan synthesis to produce the optimal architecture.