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Ghost Engineers Are Hiding in Your Team—Can AI Sniff Them Out?

Ghost Engineers Are Hiding in Your Team—Can AI Sniff Them Out?

10% of engineers are collecting salaries while doing almost nothing. AI can track them—but will it help or turn you into Big Brother?

Gino Ferrand
March 25, 2025

"You can’t manage what you can’t measure."

—Peter Drucker

Gino Ferrand, writing from Seattle, Washington...

Ghosts have always haunted the technology world. Not literal ghosts...those who rattle chains in old mansions...but quieter, digital ones. Yegor Denisov-Blanch, a researcher at Stanford, recently startled the software community awake by declaring that nearly 10% of engineers today are essentially phantoms: drawing salaries but producing almost nothing. 14% in remote roles, half that in the office. I suspect the number might be inflated; after all, measuring productivity in lines of code is like measuring journalism by word count. But having encountered them myself, there's no denying that this is a real issue…

You might be tempted to think this is a new problem, born from the Zoomified chaos of post-pandemic remote work. But history tells us otherwise. Tech has long grappled with the difficulty of seeing clearly into the productivity of its creators. Even in IBM’s mainframe days, in the 1970s and 1980s, with engineers scattered across continents, executives tried desperately to peer through primitive management tools to catch glimpses of productivity. Or the dot-com bubble around 2000, when investors threw billions at shiny startups, often without noticing if developers behind the scenes were truly building...or just enjoying gourmet catered lunches.

Can AI offer a solution to this age-old problem?

Executives certainly hope so...and companies are scrambling for tools that promise to pull back the curtain. The pitch is seductive: AI sees what managers miss, tracking patterns, predicting disengagement, and keeping teams humming. But the reality? The line between insight and surveillance is razor-thin. Some of the latest AI-driven tools making waves in developer productivity tracking include:

Pluralsight Flow

Scans commit velocity, PR activity, and coding patterns to pinpoint developer efficiency...or lack of it. The algorithm tells you who’s moving fast and who’s bogging down the pipeline.

LinearB

Digs into cycle times, idle work, and engineering throughput, promising to separate high performers from seat-fillers. The AI keeps score, whether engineers like it or not.

CodeClimate Velocity

Goes beyond raw commit counts to measure real engineering impact. Tracks how fast teams push meaningful changes, surfacing the difference between activity and productivity.

CleverControl

Watches work patterns, flags disengagement risks, and scores employee focus levels. A digital detective, always watching, always judging.

But every wave of innovation comes with unintended side effects. The telegraph brought instant global messages...and misinformation traveled just as swiftly. Surveillance cameras promised safety, but privacy vanished. Now, AI promises clarity on team performance, but it's a double-edged sword. Leaders who lean too hard into AI’s monitoring abilities risk resurrecting the specter of "bossware," digital overseers counting keystrokes and mouse movements, alienating talented engineers, and souring team morale.

AI-Enabled Nearshore Engineers: The Ultimate Competitive Edge

The future of software engineering isn’t just AI... it’s AI-powered teams. By combining AI-driven productivity with top-tier remote nearshore engineers, companies unlock exponential efficiency at a 40-60% lower cost, all while collaborating in the same time zone.

✅ AI supercharges senior engineers—faster development, fewer hires needed
✅ Nearshore talent = same time zones—real-time collaboration, no delays
✅ Elite engineering at significant savings—scale smarter, faster, better

The key, as with anything, is striking a balance. AI can expose genuine ghost engineers, but equally important, it can shine a light on quiet heroes...mentors, collaborators, engineers whose contributions aren't easily quantified in simple metrics. AI can be either a magnifying glass or a microscope... it all depends on how it's wielded.

The era of AI-driven oversight could follow one of two paths: it could become the overbearing Big Brother feared by Orwell, or it could lead to a healthier, more transparent workplace. Smart leaders will use it not as a blunt instrument of control but as a nuanced tool of understanding and support.

As with every tech cycle, some ghosts will remain. But the wisest leaders, leveraging AI with care and caution, will ensure that their teams remain vibrant, visible, and engaged.