Our Journey to Decuple Our Development Velocity Using Agentic AI Coding and a Tailored “Orchestration” Framework

Accelerating Development Efficiency with AI-Driven Coding and Custom Orchestration at Our Organization

In today’s fast-paced digital landscape, staying ahead requires innovative approaches to software development. Our team has recently implemented a cutting-edge system that has exponentially increased our development velocity, enabling us to deliver months’ worth of features within a single week. At the core of this transformation are advanced AI coding agents combined with a bespoke “Orchestration” layer that streamlines and automates our workflow.

A Key Catalyst: AI Collaboration and Quality Assurance

What sets this approach apart is not just AI-generated code, but the collaborative process among AI agents. These agents don’t simply produce code—they actively review and critique each other’s work, fostering a self-improving ecosystem that ensures higher quality and efficiency.

Our streamlined process unfolds as follows:

1. Project Tasks Initiation: Tasks originate from our project management platform.
2. Intelligent Task Retrieval: AI agents extract task details through customized commands.
3. Contextual Analysis: The AI reviews our existing codebase, design documents, and documentation, supplementing knowledge with web research when necessary.
4. Detailed Planning: It formulates comprehensive task descriptions, including requirements for testing coverage.
5. Code Generation: The AI develops production-ready code adhering to our established standards.
6. Automated Pull Requests: A GitHub pull request is automatically created.
7. Peer Review by AI: A secondary AI agent conducts an immediate, in-depth review of the proposed code, scrutinizing each line.
8. Feedback Loop: The original AI responds to review comments—either accepting suggestions or defending its implementation.
9. Continuous Learning: Both AI agents retain insights from each interaction, refining their future performance.
10. Minimal Human Intervention: Remarkably, approximately 98% of our code reaches a production-ready state before human review is required.

The most fascinating aspect of this system is observing AI agents engage in conceptual debates within GitHub comments. They effectively teach each other, deepening their understanding of our codebase and enhancing their development skills.

We documented this process in a concise 10-minute walkthrough: Watch here

While our current focus is on revolutionizing development workflows, we’re exploring applications of this methodology beyond coding—such as customer support automation. We’d be eager to hear from others experimenting with similar AI-driven systems, especially in the marketing domain.

Innovation is accelerating, and it’s an exciting era for builders and creators