How We Boosted Our Development Velocity Tenfold Using Agentic AI Coding and a Tailored “Orchestration” Layer

Accelerating Development Velocity with AI-Driven Coding and Custom Orchestration

In today’s fast-paced software landscape, rapid iteration and efficient workflows are essential for staying ahead. Recently, our team revolutionized our development pipeline by integrating advanced AI tools alongside a bespoke “Orchestration” layer, resulting in a tenfold increase in our development speed.

At the core of this transformation are AI agents that do more than just generate code—they collaboratively review and optimize each other’s work. This peer-review mechanism ensures higher quality and accelerates delivery timelines significantly.

Here’s an overview of our innovative workflow:

• Initiation begins with a task assigned in our project management system.
• An AI agent retrieves tasks using tailored commands designed for seamless integration.
• It thoroughly analyzes our existing codebase, design documents, and related materials, supplementing with web research as necessary.
• The AI then formulates a comprehensive task description, explicitly defining test coverage and quality criteria.
• It proceeds to develop production-ready code in strict adherence to our internal standards.
• Once complete, an automated process opens a pull request on GitHub.
• A second AI agent immediately reviews the proposed code line-by-line, providing detailed feedback.
• The original AI responds to this critique—either accepting suggestions or defending its approach.
• Each interaction is logged, enabling the AIs to learn and improve their collaborative process over time.
• Remarkably, this cycle results in code that’s approximately 98% ready for deployment with minimal human intervention.

A particularly fascinating aspect of this system is observing the AIs engage in code discussions within GitHub comments—debating implementation strategies and effectively mentoring each other. This self-improving dynamic not only enhances code quality but also fosters continuous learning.

To illustrate this process, we recorded a concise 10-minute walkthrough available here: Watch the full demonstration.

While our immediate focus is on refining development workflows, we’re also exploring broader applications—such as improving customer support processes—using similar AI orchestration strategies. We’d love to hear from others experimenting with AI in marketing, customer engagement, or other areas.

Exciting times lie ahead for builders and innovators alike. Embrace the transformation!