Our Journey to Decupling Development Speed by Tenfold Using Agentic AI Coding and a Tailored “Orchestration” Framework

Transforming Development Efficiency: Harnessing AI-Driven Coding with Custom Orchestration

In today’s fast-paced tech landscape, accelerating development cycles without compromising quality is a constant challenge. Recently, our team achieved a remarkable tenfold increase in development speed by integrating advanced AI coding agents alongside a bespoke “Orchestration” layer. Here’s an inside look at how this innovative approach is revolutionizing our workflow.

Our core strategy leverages AI not merely as a code writer but as a collaborative entity capable of peer review. This dual-AI system simulates a dynamic development environment where two agents critique, refine, and validate code autonomously, significantly reducing human review time and elevating code quality.

The streamlined process unfolds as follows:

1. Initialization in the project management tool
2. AI agents retrieve assigned tasks through custom command protocols
3. They analyze our existing codebase, design specifications, documentation, and, when necessary, conduct web research
4. The agents craft comprehensive task descriptions, explicitly outlining testing and coverage requirements
5. They develop production-ready code conforming to our internal standards
6. An automatic Pull Request (PR) is generated on GitHub
7. A second AI agent conducts an immediate, line-by-line review of the proposed code
8. The first agent responds to feedback—either accepting suggestions or justifying its initial approach
9. Throughout this process, both agents learn from each interaction, storing insights for future tasks
10. The outcome is an impressive 98% of code deemed ready for deployment before human review

What’s truly fascinating is observing these AI agents engaging in constructive debates within GitHub comments. They effectively teach each other best practices and deepen their understanding of our codebase, creating a self-improving development ecosystem.

We’ve documented a brief 10-minute walkthrough demonstrating this entire process—check it out here: https://www.youtube.com/watch?v=fV__0QBmN18.

While our current focus is on scaling development, we’re exploring extending this system to other areas, such as customer support and marketing. If you’re experimenting with AI-driven workflows in your organization, we’d love to hear about your experiences and ideas.

This evolution in automation and AI collaboration marks an exciting chapter in software development—propelling us toward faster, smarter, and more efficient builds.