Our Journey to Decupling Development Time by a Factor of Ten Using Agentic AI Coding and a Tailored “Orchestration” Framework—Variation 58

Accelerating Development Velocity with AI-Powered Coding and Custom Orchestration: A Case Study

In today’s rapidly evolving tech landscape, efficiency and speed are paramount. At our organization, we’ve harnessed the power of advanced AI tools combined with a bespoke orchestration layer to dramatically boost our development throughput—achieving what was once thought impossible: delivering months’ worth of features in just a week.

Our approach leverages cutting-edge AI agents, not only for writing code but for peer-reviewing each other’s work—a process that acts as a force multiplier in quality and speed. Here’s a detailed overview of our innovative workflow:

Streamlined Development Workflow with AI Collaboration

1. Task Initiation: Our project manager assigns new work through a centralized system.
2. AI Task Retrieval: Intelligent agents extract task details via custom commands tailored to our environment.
3. Contextual Analysis: These agents analyze our codebase, associated designs, documentation, and perform web research as necessary.
4. Task Specification: They generate comprehensive task descriptions, including specific testing and coverage requirements.
5. Implementation: The AI develops production-ready code aligned with our coding standards.
6. Automated Pull Requests: A GitHub PR is generated automatically by the AI system.
7. Peer Code Review: A second AI agent performs a rigorous line-by-line review of the submitted code.
8. Feedback Loop: The original AI responds to review comments, either accepting suggestions or defending its approach.
9. Knowledge Accumulation: Both AIs learn from these interactions, continuously refining their understanding and processes.
10. High-Quality Output: This cycle results in code that is approximately 98% ready for deployment without human intervention.

What truly fascinates us is observing these AI agents engaging in meaningful debates over implementation strategies within GitHub comments. Their exchanges resemble a professional developer discussion, with AI effectively mentoring itself to better understand our ecosystem and write more efficient, reliable code.

To provide a closer look into this transformative process, we recorded a concise 10-minute walkthrough demonstrating how our system operates in real time: Watch the video here.

While our current focus is on optimizing software development, we are exploring how this methodology can extend to other domains such as customer support and marketing. We’re eager to learn from the community—what innovative AI-driven systems are others experimenting with in their organizations?

This is undeniably an exciting era for builders and creators, as AI continues to redefine our capabilities