Boosting Developer Productivity by Tenfold Using Agentic AI Coding and a Custom “Orchestration” Layer

Revolutionizing Development Speed: How AI-Powered Orchestration Transformed Our Workflow

In today’s fast-paced tech landscape, efficiency and innovation are paramount. Recently, our team embarked on an experimental journey to significantly accelerate our development cycle by integrating advanced AI tools and custom orchestration layers. The results have been nothing short of remarkable — enabling us to deploy what would typically take months in just a matter of weeks.

At the core of this breakthrough is a sophisticated collaborative AI system. Unlike traditional automation, our setup leverages multiple AI agents that not only generate code but also perform peer reviews of each other’s work, effectively creating a dynamic, self-improving development ecosystem.

Here’s an overview of our innovative workflow:

1. Initial task definition is managed through our regular project management channels.
2. Our AI agents retrieve assigned tasks via custom commands tailored to our environment.
3. They analyze our existing codebase, review relevant designs and documentation, and conduct web research as needed.
4. The AI then formulates a comprehensive task outline, detailing implementation steps and test coverage expectations.
5. It proceeds to develop production-ready code aligned with our established coding standards.
6. Upon completion, a GitHub Pull Request (PR) is automatically generated.
7. A second AI agent conducts a meticulous line-by-line review of the proposed code.
8. The original AI responds to the review comments, either accepting the suggestions or defending its choices.
9. Each interaction contributes to the AI’s learning, allowing it to refine future outputs.
10. As a result, approximately 98% of code submitted is production-ready before any human review takes place.

One of the most fascinating aspects of this process is witnessing the AI agents effectively “debate” implementation strategies within GitHub comments. They analyze, critique, and improve each other’s work, cultivating a self-sustaining cycle of code quality enhancement.

For those interested in seeing this process in action, we’ve prepared a brief 10-minute demonstration explaining each step in detail: Watch the walkthrough.

While our current focus is on development acceleration, we are exploring how this AI orchestration approach can extend into other areas such as customer support and marketing. We’re excited to hear from others experimenting with AI-powered workflows—especially outside of development.

This technology-driven evolution makes it an exhilarating time for builders and innovators alike. Stay tuned for more updates as we continue to refine and expand this system