Code Longevity in the Age of AI

Why Milestone measures what actually matters

Every organization experimenting with AI in software development now faces the same paradox: productivity looks higher, yet software stability feels lower. AI accelerates output, but nobody knows whether that output is good for the codebase, the team, or the business.

Milestone has built the first system that definitively answers this question.

Traditional metrics such as cycle time, PR velocity, lines of code, DORA, tell you how fast engineers work. They say nothing about whether the resulting code survives, remains stable, or requires expensive rework months later.

Milestone introduces a fundamentally new metric: Code Longevity, the measure of how long any piece of code lives before it is rewritten, replaced, or repaired.

This is not a heuristic.
It is grounded in the complete historical record of your organization’s code.

While we have been tracking code longevity for some time, our upcoming implementation will offer a high-definition view, like taking off sunglasses to reveal hidden detail, showing nuances in code survival that have never been visible before.

Milestone performs full-scale blame graph reconstruction across every repository, every commit, and every branch. This requires:

• Ingesting millions of commits across thousands of repos
• Reconstructing merges, squashes, renames, and refactors
• Computing forward and backward blame for every line
• Correlating code changes with developer identity and AI assistance
• Building a longitudinal “change graph” of the entire codebase

The result is an unparalleled view of how software actually evolves at enterprise scale.

Before Milestone’s Code Longevity metric, there was no direct way to observe whether AI or any other factor was making codebases more fragile or more robust. Traditional metrics such as velocity, throughput, lines of code – are too noisy and influenced by multiple parameters to provide clear answers. Our code‑survival analysis provides a direct lens into code stability. Early signals show varied patterns, but the key point is that this is the first method that allows organizations to truly know, rather than guess, how long code survives.

Enterprises are discovering that speed is not the bottleneck, stability is.
With AI producing more short-lived or brittle code, the cost of maintenance rises, risk increases, and architectural coherence erodes.

Milestone’s Code Longevity metric gives engineering leaders the first reliable way to answer these questions:

• Is AI improving or degrading our codebase?
• Where is rework being generated, and why?
• Which reasoning patterns lead to long-lasting code?

This clarity is becoming essential for large-scale engineering organizations adopting AI.

Building a real Code Longevity metric is an immense technical undertaking. At Milestone, the team had to:

• Process millions of commits across thousands of repositories and normalize them
• Reconstruct every branch, merge, rename, and refactor to maintain continuity
• Compute forward and backward blame for every line of code to track its history
• Correlate code changes with developers and AI assistance at scale
• Build a longitudinal change graph that reflects how software truly evolves

This level of analysis has never been done before. It requires ingenuity, expertise in distributed systems, and countless hours of engineering work. The result is a detailed map of your codebase’s health, one that celebrates the hard work of our team and gives organizations a new way to understand software stability and longevity.

Milestone measures the one thing that ultimately matters: how long code survives. This is the real indicator of engineering health in the AI era, and no other platform can compute it.

As AI reshapes how software is written, our work provides the stability and clarity that enterprises need to build enduring systems in a faster, noisier world. Our team has solved the technical challenge of measuring code survival at scale, and we are excited to share the insights this unlocks.

At Milestone, we are committed for the long haul. Building the deep datasets and rigorous analysis needed to tell the real story hidden in code is more valuable than presenting simple metrics or overclaiming quick wins. The complexity and beauty of the engineering process deserve this level of attention to detail, and our team celebrates that craftsmanship by going deep to unearth truths that help organizations thrive in the AI era.