AI coding assistants are powerful, but they suffer from context reset between sessions. Even after explaining your project, you waste valuable time:
- Repeatedly explaining the same codebase structure
- Rebuilding projects due to forgotten architectural decisions
- Re-establishing coding conventions after every reset
- Fighting against token window limitations
Our Solution:
CodeRide eliminates the context reset cycle once and for all. Through MCP integration, it seamlessly connects to your existing AI coding workflow, enhancing how you vibe code. Once connected, CodeRide transforms your development tasks into a structured Kanban, where each task preserves complete context and instructions your AI needs to work autonomously. Compatible with all major AI code editors including Cursor, Cline, and Windsurf, plus any MCP client like Claude.ai.
The platform ensures your AI assistant maintains persistent memory throughout your entire project, preventing knowledge loss between tasks and chat sessions that typically derails development.
How it Works:
π€ IMPORT - Upload your task list manually, via CSV, or generate from project documentation
β¨ OPTIMIZE - CodeRide automatically enhances each task with perfect context preservation
π€ LAUNCH - Watch as your AI assistant retrieves and completes tasks with full project awareness
π MONITOR - Track progress as your tasks flow through the Kanban with consistent implementation
What Can You Achieve with CodeRide?
π§ End the cycle of explaining your codebase over and over
π Never rebuild projects because your AI forgot critical decisions
π§© Smart code pattern recognition and reuse across your entire codebase
π° Reduce token usage by up to 40% through optimized context
β Maintain consistent coding style without constant reminders