Our Journey to Decuple Developer Productivity Using Agentic AI Coding and a Personalized “Orchestration” Framework

Maximizing Development Efficiency with AI-Powered Automation and Custom Orchestration

In the rapidly evolving landscape of software development, leveraging artificial intelligence has become a game-changer for many teams. Recently, our team achieved a tenfold increase in development speed by integrating advanced AI coding tools and developing a bespoke “Orchestration” layer to streamline our workflows.

The core of our approach involves utilizing cutting-edge AI agents that not only generate code but also engage in reciprocal code reviews. This collaborative AI environment allows for rapid iteration and enhanced code quality, significantly reducing the manual review burden.

Here’s an overview of our streamlined development process:

1. Initiating tasks within our project management system.
2. Using custom commands, AI agents extract tasks directly.
3. The AI studies our existing codebase, design documents, and relevant documentation, supplementing with web research as necessary.
4. It then crafts a comprehensive task description, including specific testing and coverage requirements.
5. The AI proceeds to produce production-ready code aligned with our standards and best practices.
6. Upon completion, a pull request is automatically generated on GitHub.
7. A secondary AI agent reviews the proposed code in detail, commenting inline and suggesting improvements.
8. The original AI responds to feedback—either accepting suggestions or defending its initial implementation.
9. Throughout this iterative process, both AI agents learn from each interaction, refining their future performance.
10. Remarkably, approximately 98% of the code is deployment-ready prior to human review.

What truly stands out is witnessing these AI agents engage in technical debates within GitHub comments, effectively educating each other to become more proficient developers. This self-improving dynamic has drastically transformed our development lifecycle.

We documented a brief 10-minute walkthrough demonstrating this innovative system: Watch here.

While our primary focus has been on accelerating development, we’re exploring how this system can enhance other functions, such as customer support and marketing. We’re eager to learn from others experimenting with AI-driven processes in their organizations.

This period of innovation marks an exciting chapter in software development—one that continually pushes the boundaries of what’s possible.