How Ramp Engineers Accelerate Code Review with GPT-5.5 and Codex

Ramp, a corporate expense management platform, uses OpenAI's Codex powered by GPT-5.5 to accelerate code review. Instead of waiting hours for an available senior engineer to review a PR, engineers get detailed feedback in minutes.

How AI Accelerates Code Review

Codex is integrated into GitHub and analyzes every pull request on the fly. The system examines code changes, checks style (variable names, indentation, structure), searches for potential bugs (null checks, logic errors, race conditions), and suggests refactoring.

This was a turning point for Ramp. The startup is growing, and every day dozens of PRs are waiting for review. Hiring senior engineers is lagging behind the development pace. That's why they chose Codex—not to replace review, but to automate the first pass.

The process is straightforward: engineer opens a PR → Codex generates comments directly in the code → developer sees feedback immediately. Once AI provides its observations, the code is already ready for human review—faster, cleaner, and less likely to miss anything. The live reviewer focuses on design and architecture.

What Changes in the Process

• Ship speed: minutes instead of hours for code review
• New engineers learn from AI feedback—seeing best practices in context
• Seniors focus on architectural observations and design decisions
• Fewer cycles: AI catches stylistic and logical errors on the first pass
• Consistency: the system always delivers the same feedback based on the same rules

In parallel, Ramp is working on integration: Codex sees the context of the entire repository, understands the team's architectural conventions (for example, how they typically structure error handling), and can provide feedback that sounds like it's coming from an experienced Ramp colleague. Quality has actually improved because no error will slip through—neither from humans nor machines.

"With Codex, we've saved thousands of hours on mechanical code review.

Engineers now focus on what truly matters."

What This Means

AI code review is transforming from an experimental tool into an industry standard. When machines can provide instant feedback on style and simple bugs, people are freed up for work that requires judgment—architecture, test strategy, and UX implications of code.