clavain

You can orchestrate the full software development lifecycle by routing tasks through heterogeneous AI models. This Skill coordinates Claude, Codex, and GPT-5.2 Pro to manage phases from discovery and brainstorming to execution, review, and shipping.

The best way to coordinate code generation and review across AI agents is using a layered architecture with skills, agents, commands, and hooks. This setup routes specific development tasks to the appropriate AI model for execution and automated review.

Yes, you can use workflow orchestration to manage your project from planning to shipped code. The Skill onboards your project, generates an initial roadmap, sets up documentation, and guides the AI through coding and review phases.

Yes, this multi-model AI agent approach supports project discovery and strategy planning phases. It explicitly manages these initial stages before moving into execution, ensuring your development lifecycle starts with structured problem discovery and strategic alignment.

You need multi-model coordination to leverage the distinct strengths of different AI models within your development workflow. Integrating Claude, Codex, and GPT-5.2 Pro allows the system to route diverse lifecycle tasks to specialized models for better execution.

A limitation of using heterogeneous AI models for workflow orchestration is the dependency on the availability and integration of external models like Codex and GPT-5.2 Pro. You must ensure your environment supports these connections for the layered architecture to function.