How MongoDB Cut PR Size by ~50% and Improved PR Cycle Time with Optimal AI

MongoDB’s Internal Tools team was scaling impact across the organization. But behind the scenes, getting a reliable view of engineering health was harder than it should’ve been. Teams pulled data with home-grown scripts, copied dumps into spreadsheets, and stitched together dashboards by hand. It worked—until it didn’t.

“It was never as good as we wanted it to be,” says Lila Brooks, Engineering Manager, Internal Tools. “We had to run it manually and modify the data. It wasn’t easy to use.”

MongoDB needed a single, trusted place to see engineering metrics—without maintaining scripts—and a smoother experience that leaders and engineers would actually adopt.

The Problem

Ad-hoc scripts, spreadsheet gymnastics, and limited adoption

Before Insights, visibility depended on manual effort across teams:

• Custom scripts maintained by different departments to extract data
• CSV/Excel workflows to transform and aggregate metrics
• Hand-built dashboards that required constant updates

“We were using scripts folks had written, dumping data into Excel, then producing higher-level dashboards… it was never easy to use.”
— Lila Brooks, Engineering Manager, MongoDB

The friction showed up everywhere: metrics were slow to produce, hard to trust, and inconsistent across org levels. Adoption lagged because switching views, filtering by teams/people/activities, and answering simple questions took too much effort.

Without a single source of truth, it was difficult to:

• See where time was going (tech debt vs. bugs vs. discovery vs. feature work)
• Understand where PRs were getting stuck and why cycle time was high
• Spot patterns and unblock issues before they affected delivery

The Solution

A single source of truth with Investments, Jira integration, and smooth UX

MongoDB adopted Optimal AI Insights to replace scripts and spreadsheets with a single, navigable system for engineering metrics.

• Unified dashboards: One place to see all metrics, with fast filters by team, person, and activity.
• Investments view: Clear allocation across technical debt, bug fixes, discovery, feature development, and more—by week, sprint, or quarter.
• Jira integration: Real-time view of effort by epics/initiatives, where work got blocked, and why—fueling root-cause discussions.
• Adoption-ready UX: Smooth switching between views and filters → better usage from engineers to directors and above—no code, no scripts.

“We now have a single place to see all the metrics. We can filter by teams, people, activities—without writing or maintaining code. The UX is smooth, so adoption improved from engineers up to directors.”
— Lila Brooks

With shared visibility, leaders and ICs could pinpoint large PRs, see who/why, and run the right conversations to create quick wins—like reducing PR size and improving deployment frequency.

The Results

PRs ~50% smaller, faster cycle time, and organization-wide adoption

The move to Insights produced noticeable, measurable improvements:

• PR size reduced by nearly 50%
• Improved PR cycle time, driven by clarity on where/why reviews were slow
• Higher PR quality, supported by focused conversations on large PRs
• Improved deployment frequency, enabled by smaller, easier-to-review changes
• Widespread adoption across levels (engineers → senior engineers → directors+)

“We were able to get the size of our PRs much smaller—nearly 50%—and improve our PR cycle time by understanding why review was taking time.”
— Lila Brooks

“Investments shows where the team’s effort is spent. Seeing tech debt, bug fixes, discovery, and features—by sprint or quarter—helps us focus.”
— Lila Brooks

Scaling faster with Developer Experience at the center

With Insights in place, MongoDB’s Internal Tools team moved from ad-hoc reporting to repeatable, trusted visibility—the basis for better conversations, faster iteration, and higher-quality software.

“I highly recommend teams invest in developer experience. Measure the right KPIs and show them to the team. That’s what improves productivity and experience.”
— Lila Brooks