Boosting Our Development Velocity Tenfold Using Agentic AI Coding and a Tailored “Orchestration” Layer

Transforming Development Efficiency with AI-Driven Automation: Our Experience with Agentic AI and Custom Orchestration

In the rapidly evolving landscape of software development, leveraging artificial intelligence to streamline workflows has become a game-changer. At our organization, we have successfully accelerated our delivery pipeline by implementing a sophisticated AI-powered orchestration system that enables us to ship months of features within a single week.

Central to this transformation is our innovative approach where AI agents not only generate code but also collaboratively review and refine each other’s work. This dynamic exchange creates a robust, self-improving environment that enhances both speed and quality.

Our streamlined development process looks like this:

1. Task initiation occurs within our project management platform.
2. An AI assistant retrieves and processes tasks through custom command integration.
3. It examines our existing codebase, design documents, and relevant web research to inform development.
4. A comprehensive task description is crafted, including specifics on testing and coverage expectations.
5. The AI then develops production-ready code aligned with our coding standards.
6. An automatic pull request is generated on GitHub.
7. A second AI agent immediately conducts a detailed line-by-line review.
8. The first AI responds to review comments, either accepting suggestions or justifying its implementation choices.
9. Each interaction feeds into a learning process, allowing AI agents to continuously improve and adapt for future tasks.
10. Impressively, approximately 98% of the code reaches a deployment-ready state prior to human intervention.

What makes this approach truly fascinating is witnessing the AI agents engage in code debates within GitHub comments—effectively teaching each other to become more proficient developers. Over time, they gain a deeper understanding of our codebase, which further refines their collaborative capabilities.

For a closer look at this process, we’ve prepared a concise 10-minute walkthrough video explaining the mechanics in detail: Watch Here.

While we’ve primarily focused on development automation, we’re exploring extending this system to other areas such as customer support and marketing. We’re curious to hear from others experimenting with AI-driven workflows—what sectors or processes are you optimizing with automation?

We’re living in an exciting era of innovative building, and we’re eager to discover how others are harnessing AI to transform their workflows.