Kleiber Orchestration

AI agent orchestration manages specialized roles like Architect, Engineers, and Validator to enable complex task decomposition and parallel execution. It enforces production-readiness through quality gates, model routing, and defined protocols across software development workflows.

Route AI tasks to different models by implementing model routing logic that optimizes cost and performance based on task complexity. Assign high-complexity tasks to advanced models like Opus, standard development to Sonnet, and lightweight checks to Haiku to balance execution speed and cost.

Prevent infinite loops in automated AI agent workflows by enforcing quality gates and hooks that run automated checks during execution. These defined protocols monitor code quality, test coverage, and task completion states to halt runaway processes and ensure production-ready outcomes.

Use multi-agent orchestration when building features that span multiple files or concerns, such as frontend and backend integration. It benefits tasks requiring parallel execution across specialized roles like architecture, engineering, and validation to ensure production-ready outcomes.

AI agent teams for code reviews rely on defined protocols and automated verification to maintain quality, but they lack open-ended creative reasoning. Limitations include rigid adherence to anti-patterns and the need for explicit quality gates to prevent context loss during complex task decomposition.