Coordination patterns for multi-model AI systems

This is Part 2 of a series on agentic systems — This was especially weird given how eosteric it can be to describe how to work better with agents, but this is my shot at it.

The article walks through the coordination patterns to address types of error:

- Single-writer: one agent writes, others review read-only. Eliminates oscillation. Maps to the single-writer principle from concurrent systems.

- Sequential planning: parallel planners cluster even across different models. Sequential divergence acts as a covering algorithm — 3 sequential planners explore more than 5 parallel.

- Sequential vs parallel review: parallel voting catches common issues (mean quality). Sequential review compounds scrutiny but risks scope creep. Both are useful.

- Human interview gating: open-ended questions yield ~5x more useful context than closed ones. "REST or GraphQL?" vs "What should we know about how this API will be consumed?"

- Adversarial validation: separate environment, separate agent, explicit goal of breaking the application. Tests the spec, not the implementation.

Hope it's useful reading