autopilot

You can automate the full RPI cycle by orchestrating multi-model exploration and stateful execution via MCP tools. This approach coordinates parallel exploration, constraint extraction, automatic planning, and automated implementation with cross-model validation to produce runnable results.

Stateful workflow automation preserves progress across context clearing by using dedicated state tooling to save phase states. This mechanism ensures that work resumes seamlessly from the exact initialization, research, planning, implementation, or review phase without losing prior context.

Yes, you need both Codex and Gemini MCP access to run automated planning workflows. The multi-model exploration coordinates these specific tools for constraint extraction and plan validation, ensuring cross-model validation during the end-to-end implementation process.

Yes, end-to-end RPI automation is explicitly applicable for solo developers or small teams. It provides hands-off exploration, constraint extraction, automatic planning, and automated implementation with cross-model validation, making it suitable for smaller scale development contexts.

The best way to start is to provide a clear requirement description and enable the automated workflow to run the full RPI cycle. The system initializes the phase-structured workflow, automatically updating state as it progresses through research, planning, implementation, and review.

Multi-model exploration uses parallel constraint extraction during planning to validate plans across different models. Coordinating Codex and Gemini ensures that the automated implementation phase receives cross-validated constraints, reducing errors and producing reliable, runnable code results.