agent-council

Multi-agent debate for architectural decision-making uses pydantic-ai to orchestrate adversarial agents that stress-test assumptions, run premortems, and cross-examine trade-offs to surface hidden risks before you commit.

Convergence diagnostics in structured multi-agent debate provides quantitative confidence dispersion and argument novelty metrics to determine whether a decision is truly resolved or requires further cross-examination.

Yes, you can evaluate database migration trade-offs by spawning expert agents with pydantic-ai to simulate a structured debate, stress-test assumptions, and surface hidden risks before committing.

Yes, you need Python 3.10 or higher and pydantic-ai installed to execute the structured debate graph and generate typed synthesis reports with convergence diagnostics.

Structured debate prevents groupthink in complex architectural decisions by simulating adversarial collaboration across multiple expert agents, forcing iterative cross-examination and premortems instead of positional commitment.

You should avoid multi-agent debate for simple, low-stakes decisions where the overhead of spawning expert agents and running convergence diagnostics outweighs the benefit of surfacing hidden assumptions.