Our Journey to Decuple Developer Productivity Using Agentic AI Coding and a Custom “Orchestration” Layer

Unlocking Accelerated Development: How AI-Driven Coding and Custom Orchestration Are Transforming Our Workflow

In today’s fast-paced software development landscape, efficiency and quality are more vital than ever. At our company, we’ve embarked on a groundbreaking journey to dramatically boost our development speed—achieving what we call a 10x increase—by harnessing the power of advanced AI tools combined with a bespoke orchestration layer.

Our secret sauce lies in leveraging AI agents that not only generate code but actively review and critique each other’s work. This collaborative, AI-driven approach has revolutionized our development pipeline, enabling us to deploy features at an unprecedented pace.

Here’s a glimpse into our innovative workflow:

1. Initiating Tasks: The process begins within our project management system, where new development tasks are created.
2. AI Task Acquisition: Customized commands enable our AI agents to automatically fetch and interpret these tasks.
3. Deep Codebase Analysis: The AI agents thoroughly examine our existing code, design documentation, and online research resources as necessary.
4. Detailed Task Planning: They craft comprehensive task descriptions, including specific requirements for test coverage.
5. Code Implementation: The AI then generates production-ready code compliant with our internal standards.
6. Pull Request Creation: An automated process opens a GitHub pull request for the new code.
7. Peer Code Review: A second AI agent meticulously reviews the code line-by-line, providing feedback or approval.
8. Iterative Feedback Loop: The original AI agent responds to the review, either defending its approach or accepting suggested improvements.
9. Continuous Learning: Both AI agents adapt and refine their processes based on each interaction, building a knowledge base for future tasks.

Remarkably, this system results in code that is approximately 98% ready for deployment before any human review—saving significant time and resources.

What’s truly captivating is witnessing these AIs engage in a dynamic dialogue within GitHub comments, effectively mentoring each other and deepening their understanding of our codebase. It’s like watching a pair of expert developers collaboratively evolve their craft.

For a closer look, we’ve prepared a concise 10-minute walkthrough demonstrating this entire process. You can watch it here: https://www.youtube.com/watch?v=fV__0QBmN18

While we’re currently focusing on development, our broader vision