Our Journey to a 10-Fold Increase in Development Speed Using Agentic AI Coding and a Tailored “Orchestration” Framework

Transforming Development Efficiency with AI-Driven Orchestration: A Deep Dive

In today’s fast-paced tech landscape, accelerating development cycles without sacrificing quality is a dream for many engineering teams. Recently, our team achieved a remarkable tenfold increase in development throughput by integrating cutting-edge AI tools and a custom orchestration system into our workflow. Here’s an insider look at how we’re leveraging AI agents to streamline our processes and deliver features at an unprecedented pace.

The core of our approach involves deploying intelligent AI agents that don’t just generate code—they actively collaborate and critique each other’s work. This dynamic exchange creates a self-improving development environment, enabling us to ship multiple months’ worth of features every week.

Our AI-powered workflow unfolds as follows:

1. Initiation Stage: Tasks commence within our project management platform.
2. Task Assignment: Customized commands prompt our AI agents to fetch and interpret the assigned tasks.
3. Research & Preparation: The AI reviews our existing codebase, design documents, and related resources, including web research when necessary.
4. Task Detailing: It then crafts comprehensive task descriptions, highlighting testing and coverage requirements.
5. Code Implementation: Following our coding standards, the AI develops production-ready solutions.
6. Pull Request Generation: A GitHub pull request is automatically created for the new code.
7. Automated Review: A second AI agent performs a meticulous line-by-line review of the proposed changes.
8. Feedback Loop: The original AI responds to review comments—either adjusting its implementation or defending its initial approach.
9. Knowledge Sharing: Both AI agents learn from each review interaction, continuously refining their future performance.
10. Outcome: We achieve approximately 98% production-ready code prior to human review, dramatically reducing review time and iterations.

What’s truly fascinating is witnessing these AI agents debating implementation strategies within GitHub comments. They’re essentially teaching each other, deepening their understanding of our codebase and evolving into more effective developers.

To illustrate this process, we’ve prepared a concise 10-minute walkthrough video: https://www.youtube.com/watch?v=fV__0QBmN18

Looking ahead, we’re exploring how this orchestration model can extend beyond development—possibly into areas like customer support or marketing. We’re eager to learn what innovative approaches others are testing in their organizations.

This is an exciting era for building and innovation. Embracing AI-driven workflows opens new horizons for productivity and