Our Strategy for Boosting Developer Productivity by 10x Using Agentic AI Coding and a Tailored “Orchestration” Layer

Transforming Development Velocity: How AI-Driven Orchestration Accelerates Our Workflow

In today’s competitive tech landscape, rapid feature delivery is essential. Recently, we revolutionized our development process by integrating AI-powered tools and creating a custom orchestration layer that significantly boosts our efficiency. Here’s an inside look at how we’re now able to push out months’ worth of features every week, leveraging cutting-edge AI technologies like Claude Code, CodeRabbit, and more.

A Key Innovation: Collaborative AI Agents

The core of our approach is that AI agents don’t merely generate code—they actively review and critique each other’s work. This dynamic interplay ensures high-quality, production-ready code with minimal human intervention.

Our streamlined workflow includes the following steps:

1. Initiation in Project Management: Tasks are created and prioritized.
2. AI-Driven Task Acquisition: Customized commands enable AIs to fetch and understand tasks.
3. Deep Codebase Analysis: The AI examines our existing code, design documents, and related resources, conducting web research if necessary.
4. Task Detailing: It crafts comprehensive descriptions, including requirements for test coverage.
5. Code Development: The AI generates production-level code adhering to our standards.
6. Automated Pull Request Creation: The system opens a GitHub PR automatically.
7. Dual AI Code Review: A second AI tool performs a meticulous line-by-line review of the submitted code.
8. Interactive Feedback Loop: The first AI responds to review comments—either accepting suggestions or defending its approach.
9. Continuous Learning: Both AI agents record insights from each interaction to improve future performance.
10. Result: Achieving approximately 98% of code ready for deployment prior to human review.

One of the most fascinating aspects is observing these AI agents engage in a virtual debate within GitHub comments, effectively teaching each other best practices and deepening their understanding of our codebase.

To give you a clearer picture, we’ve prepared a concise 10-minute walkthrough demonstrating this entire process. You can watch it here: Watch the Video.

Looking ahead, we’re exploring applying this orchestration model beyond development—potentially to areas like customer support. We’re also eager to hear from others experimenting with AI systems, especially in marketing and other disciplines.

Indeed, this is an exciting era for innovative building. The possibilities are accelerating fast, and we’re thrilled to be at the forefront.