Boosting Our Development Efficiency by Tenfold Using Agentic AI Coding and a Personalized “Orchestration” Layer

Revolutionizing Development Workflow with AI: How We Achieved a 10x Increase in Engineering Speed

In the fast-paced world of software development, staying ahead often requires innovative strategies and cutting-edge tools. Recently, we embarked on a transformative journey to dramatically accelerate our development process by integrating advanced AI agents and custom orchestration layers, leading to a tenfold increase in our output efficiency.

The Core Strategy

Our approach revolves around leveraging AI to handle not just coding tasks but also quality review processes, creating a collaborative environment where AI agents augment each other’s work. This setup enables us to deliver feature-rich updates weekly—something previously thought unattainable.

How the Workflow Functions

Here’s a step-by-step overview of our AI-driven development pipeline:

1. Task Initialization: Our project manager assigns work items into the system.
2. Task Retrieval: An AI agent fetches these tasks through tailored commands.
3. Codebase Analysis: The agent examines our existing code, designs, documentation, and performs web research if necessary.
4. Detailed Specification: It creates comprehensive task descriptions, including testing and coverage criteria.
5. Implementation: The AI writes production-ready code aligned with our guidelines.
6. Pull Request Creation: An automatic PR is generated on GitHub.
7. Code Review by AI: A second AI tool conducts a meticulous line-by-line review of the proposed changes.
8. Interactive Feedback Loop: The first AI responds, accepting suggestions or defending its approach, fostering a dynamic debate.
9. Knowledge Sharing: Both AI agents learn from these interactions, continuously refining their understanding for future tasks.

Remarkably, this process results in code being approximately 98% ready for deployment before human review, significantly reducing our manual oversight and review time.

The Dynamic of AI Collaboration

One of the most fascinating aspects is witnessing AI agents ‘discuss’ implementation details within GitHub comments. This iterative back-and-forth effectively teaches the systems to improve their coding capabilities and comprehension of our specific codebase, mimicking collaborative developer teamwork.

See It in Action

We’ve documented a concise 10-minute walkthrough demonstrating the full process. Check it out here: Watch the video.

Beyond Development

While we’re excited about the efficiencies gained in software engineering, our vision extends beyond coding. We’re exploring applying this orchestrated AI approach to areas like customer support and marketing. If you’re