Our Journey to Decupling Developer Productivity by Tenfold Using Agentic AI Coding and a Proprietary “Orchestration” Framework

Maximizing Development Efficiency: Harnessing AI-Driven Coding and Custom Orchestration

In today’s fast-paced tech environment, accelerating development timelines while maintaining high-quality standards is more critical than ever. Our team has embraced a groundbreaking approach that leverages advanced AI tools combined with a custom “Orchestration” layer to dramatically enhance our software delivery process. In this post, we’ll share insights into how this strategic integration has enabled us to deploy months’ worth of features on a weekly basis.

The cornerstone of our methodology is the use of sophisticated AI agents that not only generate code but also engage in self-review and collaborative refinement. This bidirectional interaction fosters an environment where AI components serve as both creators and critics, ensuring a higher standard of code quality before human oversight.

Here’s an overview of our streamlined workflow:

1. Initiation begins with a task assignment in our project management system.
2. An AI agent retrieves tasks through customized commands tailored to our process.
3. The AI studies our existing codebase, design documentation, and conducts necessary web research.
4. It then formulates a comprehensive task description, including specific test coverage criteria.
5. The AI proceeds to generate production-ready code aligned with our established coding standards.
6. Once ready, it automatically opens a pull request on GitHub.
7. A second AI agent performs an immediate, meticulous line-by-line code review.
8. The initial AI responds to review feedback — either accepting suggestions or articulating reasons for its implementation choices.
9. Both AI agents learn from each interaction, storing insights to optimize future tasks.
10. The result is a notable 98% of code ready for production before human intervention is needed.

What truly fascinates us is witnessing these AI agents “debate” implementation details within GitHub comments. They effectively teach each other and enhance their understanding of our codebase, continually refining their skills and collaboration.

For a closer look at this innovative process, we’ve prepared a short 10-minute walkthrough video that demonstrates each step in action: Watch here.

While our primary focus has been on development, this systems approach inspires us to explore its applications across other areas such as customer support and marketing. We are eager to connect with others who are experimenting with AI-driven workflows and share insights.

This is undeniably an exciting era for builders and innovators alike. Embracing these advancements allows us to accelerate our progress and elevate the quality of