The 48-Hour Legacy Refactor: How AI Agents Saved My Production Deployment

It was Friday night, 9:00 PM. I was staring at 50,000 lines of "spaghetti" Node.js code—a decade-old monorepo that had become the single point of failure for our production systems. We had 48 hours to migrate it to a serverless architecture, or we’d miss our 2026 scaling targets.

1. The Crisis of Context

The problem wasn't the code; it was the hidden knowledge. Every time I touched a route, a database trigger would fire in a service I didn't know existed. Conventional IDE search was useless. I needed an agent that could see the entire picture at once.

I pulled in Gemini 1.5 Pro. With its 2 million token context window, I fed it the entire monorepo, including 5 years of logs and a scattered documentation wiki. In under 60 seconds, it drew a dependency graph that my team had spent months trying to map.

2. Orchestrating the "Swarm"

Once I had the map, I needed the workers. I leveraged the new Model Context Protocol (MCP) to connect Claude Code directly to our AWS environment.

3. The 3:00 AM Breakthrough

By 3:00 AM on Saturday, the "Swarm" was working. Claude was handling the logic refactoring, while a sub-agent I configured using GPT-5.2 Codex was automatically updating the Terraform files to match the new infrastructure.

This is where Utilizing Tools correctly matters. I wasn't just asking for code; I was a Systems Conductor. I spent my time reviewing the "Why" and approving the tests generated by the agents.

4. Reviewing the Unreviewable

The biggest fear in 2026? Shipping "AI Slop." To prevent this, I used a custom Review Chain. Every line written by Claude was audited by Gemini 1.5 Pro specifically for "Redundant Logic." If Gemini found a similar utility elsewhere in the 50k lines, the PR was rejected. This kept our new codebase 40% smaller than the original.

5. The Aftermath: Survival is a Skill

Monday morning, 9:00 AM. The migration was live. The monorepo was gone, replaced by a decoupled, event-driven architecture. What used to take a senior engineering team 6 months took one engineer and three agents 48 hours.

The lesson? In the AI-native world of 2026, your value isn't your ability to write syntax. It's your ability to orchestrate complex systems and maintain the architectural vision.