A new study from Stanford University has brought some eerie truths to light: approximately 9.5% of software engineers in tech teams aren’t really contributing as much as they should. These “ghost engineers” have sparked a fresh round of debate in the industry about the real value of certain employees, what counts as productivity, and whether traditional performance metrics are too outdated.
Who are these ghost engineers?
No, this isn’t about engineers pulling off the ultimate vanishing act. Instead, these “ghosts” are employees whose work doesn’t seem to leave much of a mark. Whether it’s a lack of measurable output or simply not being part of the action, these engineers often appear in reports, but not in results.
In fact, the study points to an unsettling reality: a chunk of the tech workforce is either disengaged, underutilized, or misaligned with their team’s goals. It’s like having an extra player on the team who never actually touches the ball.
Is productivity still just about lines of code?
Tech companies have long relied on the same tired metrics to measure productivity: lines of code written, number of bugs fixed, or sprints completed. But, as the study suggests, these numbers are starting to feel more like a poor gauge of actual value.
“Someone who writes a hundred lines of code that are messy, redundant, and prone to failure is not necessarily ‘working’ more than someone writing just a handful of clean, efficient lines,” said one tech consultant. It seems the focus on volume over quality might be part of what’s fueling this ghost engineer phenomenon.
The ghost in the machine: Is leadership to blame?
The study doesn’t just point fingers at individual engineers. It takes a hard look at leadership and company culture too. Engineers are complex creatures, and when they’re in roles that aren’t defined, aren’t challenging, or aren’t appreciated, they’re likely to check out—at least mentally.
Managers might be missing the bigger picture: those “ghosts” could actually be doing important work that doesn’t show up in spreadsheets—mentoring junior team members, tackling behind-the-scenes problems, or just keeping the team together when things get rough. If this work isn’t being recognized or tracked, it’s easy to overlook the value these engineers bring to the table.
AI and automation: Are we getting too comfortable?
With AI tools like GitHub Copilot and ChatGPT now handling some of the grunt work for engineers, traditional productivity measures have become even more muddied. If an AI tool can write part of the code for you, does that make you more or less productive?
This shift means that engineers might be focusing on higher-level tasks, leaving behind the time-consuming chores that once made up their daily grind. But without a clear way to measure the quality of that high-level work, it’s easy for people to slip into ghost territory.
What does this all mean for the future?
The study’s findings leave a lot of questions hanging in the air. If nearly 10% of engineers aren’t making a tangible impact, what does that say about the effectiveness of tech teams? Is the problem with the engineers themselves, or is it a sign that companies need to rethink how they’re organizing and measuring work?
Ultimately, it’s about getting smarter with how we measure productivity. The answer isn’t simply about working more or harder—it’s about working more meaningfully. And that means getting rid of outdated productivity metrics and focusing on impact over output.
The ghost engineers are here, but they might just be a sign that it’s time to reimagine how we think about tech teams, leadership, and what truly defines success.