Our Journey to Decuple Developer Velocity Using Agentic AI Coding and a Tailored “Orchestration” Layer

Transforming Development Efficiency: How We Achieved a 10x Boost with AI-Driven Coding and Custom Orchestration

In today’s rapidly evolving tech landscape, maximizing development speed without compromising quality is more crucial than ever. Recently, our team embraced innovative AI tools and a bespoke orchestration layer that revolutionized our workflow — enabling us to deliver months’ worth of features on a weekly basis.

Central to this transformation is the deployment of advanced AI agents—not merely for generating code but for collaboratively reviewing each other’s work. This peer-review mechanism within the AI ecosystem has become a powerful force multiplier, drastically enhancing accuracy and efficiency.

Here’s an inside look at our optimized process:

1. The journey begins with task assignment via our project management system.
2. An AI agent retrieves tasks through custom commands tailored to our workflow.
3. The agent analyzes our existing codebase, design documents, and relevant online research when required.
4. It then drafts a comprehensive task description, explicitly detailing testing requirements and coverage.
5. Using our coding standards as a guide, the AI produces production-ready code.
6. A GitHub pull request (PR) is automatically generated to facilitate review.
7. Another AI agent immediately performs a line-by-line review of the proposed changes.
8. The initial AI responds to this critique, either accepting suggestions or justifying its implementation choices.
9. Throughout this iterative exchange, both AI agents learn from each interaction, accumulating insights to refine future performance.
10. Remarkably, this process results in code that is approximately 98% ready for deployment before human review.

What truly astonishes us is witnessing these AI agents engage in constructive debates about implementation details within GitHub comments. They are effectively teaching each other, deepening their understanding of our codebase and elevating their development capabilities.

To see this process in action, we recorded a concise 10-minute walkthrough that demonstrates the entire workflow: Watch the video here.

While our immediate focus is on scaling development, we are exploring extending this system to areas like customer support and marketing. We’re eager to learn from others experimenting in these domains as well.

This innovative approach is shaping the future of efficient software development—and we’re excited to be part of it. The possibilities are vast, and the potential to redefine how we build is truly motivating.

Stay tuned for more insights as we continue to push the boundaries of what’s possible with AI-driven processes!