AI Orchestration Toolkit
Research & DesignA toolkit born from real-world experience orchestrating 13+ AI agents simultaneously. Captures the patterns, tools, and protocols needed to run reliable multi-agent workflows.
Based on a comprehensive gap analysis of current orchestration frameworks (OpenClaw, CrewAI, LangGraph, AutoGen) against state-of-the-art techniques. Covers structured communication, quality assurance, and advanced orchestration patterns.
The 4-phase roadmap: Foundation (structured schemas, confidence scoring), Quality Assurance (critic loops, progress streaming), Advanced Orchestration (persistent memory, consensus voting), and Protocol Integration (MCP, event-driven architecture).
Tech Stack
Key Features
- ✓Structured output schemas for agent communication
- ✓Confidence scoring and quality gates
- ✓Fallback chains and error recovery
- ✓Critic/reviewer loops for quality assurance
- ✓Progress streaming and real-time monitoring
- ✓Persistent agent memory across sessions
- ✓MCP protocol integration
- ✓Consensus voting for critical decisions
Challenges
The gap between current orchestration tools and production needs is significant. Most frameworks handle the 'happy path' well but lack robust error recovery, quality verification, and cross-agent memory. Building these as composable, framework-agnostic modules is the goal.