Our Journey to Accelerate Development Tenfold Using Agentic AI Coding and a Custom “Orchestration” Platform

Transforming Development Efficiency: How AI and Custom Orchestration Accelerate Our Coding Workflow

In today’s fast-paced software landscape, staying ahead means embracing innovative strategies to streamline development processes. Recently, we implemented a groundbreaking approach that has exponentially increased our coding productivity — leveraging advanced AI coding assistants combined with a bespoke coordination layer.

Here’s an inside look at how we’re delivering months’ worth of features on a weekly basis, thanks to tools like Claude Code, CodeRabbit, and others that have revolutionized our workflow.

The core success factor? Our AI agents aren’t just generating code; they’re engaging in a collaborative review process. This internal peer review mechanism ensures higher-quality output and accelerates development significantly.

Our streamlined process unfolds in the following stages:

1. Initialization: Tasks originate from our project management system.
2. Task Retrieval: AI agents fetch specific assignments through custom commands.
3. Code Analysis & Research: The AI reviews our existing codebase, documentation, and relevant web resources.
4. Detailed Planning: It formulates comprehensive task descriptions, including criteria for test coverage.
5. Implementation: The AI crafts production-ready code aligned with our standards and best practices.
6. Pull Request Creation: An automated GitHub PR is generated upon completion.
7. Automated Review: A second AI agent conducts a meticulous line-by-line review of the proposed code.
8. Feedback Loop: The first AI responds to critique—either refining the implementation or defending its initial approach.
9. Learning & Adaptation: Both AI systems learn from each review cycle, storing insights for future tasks.
10. Outcome: Up to 98% of the code delivered is ready for deployment before human oversight.

What’s truly fascinating is witnessing these AI agents engage in constructive “debates” within GitHub comments, effectively teaching each other and enhancing their understanding of our specific codebase. This emergent behavior resembles a collaborative developer team evolving in real-time.

For a detailed walkthrough of this process, check out our short video demonstration: Watch here.

While our current focus is on software development, we’re exploring expanding this system’s application into other areas like customer support and marketing automation. We’re eager to hear from other professionals who are experimenting with similar integrations.

In this exciting era of intelligent automation, the possibilities for innovation are limitless. Embrace the change — your team’s productivity might just reach