AI coding assistants have become powerful enough to generate working code in minutes. But power without process creates chaos—especially when you're racing to build an MVP that investors will scrutinize.
Relay, an open-source tool from developer Yoni Raviv, addresses this by turning Claude Code into a visual Kanban build loop. Instead of managing AI-generated code through an endless chat transcript, founders and developers get a structured interface for organizing, tracking, and managing what the AI is building. It's a small innovation that highlights a bigger shift: the best AI development tools are no longer just about raw capability—they're about workflow, visibility, and control.
Why Workflow Matters When Building With AI
When you're using Claude, Cursor, or another AI coding assistant to build your product, the work happens fast. Too fast, sometimes. Code gets generated, features get added, bugs get fixed—all in a conversational flow that can become difficult to track.
For solo founders or small teams building an MVP, that lack of structure creates three problems:
- You lose track of what's been built. Without a clear system, you forget which features are complete, which are half-done, and which still have edge cases.
- You can't demonstrate velocity. Investors want to see that you can execute and iterate quickly. A chaotic commit history or unclear development process signals disorganization.
- You ship bugs you didn't catch. When AI writes code conversationally, it's easy to miss test coverage gaps or integration issues until they surface in production.
Relay solves the first problem by giving you a Kanban board for AI-assisted development. You can see tasks move from "To Do" to "In Progress" to "Done," even when an AI agent is doing the coding. That visibility makes it easier to stay organized, spot gaps, and communicate progress—whether to co-founders, early customers, or investors.
What Relay Does and Why It Matters
Relay integrates with Claude Code to provide a visual project management layer on top of AI-driven development. Instead of managing everything through a chat interface, you organize coding work into cards on a board.
The tool is open source and designed for developers who want more structure around their AI coding workflow. You can track what the AI is working on, see what's been completed, and manage the queue of upcoming tasks—all in a familiar Kanban format.
For founders, this kind of workflow tooling is as important as the AI itself. Speed matters, but so does discipline. Investors don't just want to hear that you're building fast—they want to see that you're building smart. A clear development process, visible iteration cycles, and evidence of systematic progress all signal that you can scale beyond the MVP stage.
The Bigger Shift: AI Tools Are Maturing
Relay represents a broader trend in AI development tools. The first wave focused on raw capability—how much code can the AI write, how accurately, how fast. The second wave is about integration, workflow, and reliability.
We're seeing this across the ecosystem:
- AI coding assistants are adding project-level context and multi-file editing.
- Platforms are building review and testing workflows around AI-generated code.
- Tools like Relay are adding structure and visibility to what used to be freeform chat-based development.
This maturation matters for founders because it makes AI-assisted development more practical for real products—not just prototypes or experiments. When you can organize, track, and manage AI-generated code systematically, you can build faster and more reliably.
Key Takeaways
- Workflow matters as much as speed when building with AI coding tools—visibility and organization help you ship faster and with fewer bugs.
- Relay adds Kanban structure to Claude Code, making it easier to track what's been built and what's next.
- Investors care about process as much as product—showing a clear development workflow signals execution capability and scalability.
- AI dev tools are maturing from raw capability to integrated workflows, making them more practical for real MVPs.
- Use structure to stay organized even when building fast—a simple Kanban board or task tracker keeps AI-assisted development manageable.
For founders, the lesson is clear: use AI to move fast, but add process and structure to move smart. When you can show both speed and discipline in your build process, you're in a stronger position to pitch investors and scale your product.
Sources: https://github.com/YoniRaviv/Relay