Pinterest terminated two engineers for creating software that identified which colleagues had been laid off—a move that crystallizes the information asymmetry at the heart of modern tech employment.

The tool was built internally during a period of workforce reductions at the company. It answered a simple question: who's still here? Apparently, that question wasn't one Pinterest wanted answered.

Here's the context: tech companies have gotten strategic about layoffs. Gone are the days of announcing "we're cutting 10% of the workforce" and doing it all at once. Modern layoffs are often rolled out in waves, sometimes called "performance management" or "organizational restructuring" to avoid the negative headlines that come with mass termination announcements.

This creates uncertainty. Employees don't know if their team is affected. Managers can't always say who's been cut. The company controls information about its own workforce composition, and shares it selectively.

The engineers who built the tracking tool were, from one perspective, just solving an information problem with the tools at their disposal. They had access to internal systems. They built software to aggregate data about employment status. In most contexts, that would be called "good engineering."

But employment is not most contexts. Companies consider workforce data sensitive. Who's been laid off, who's been hired, org chart structures—these are deliberately controlled. Transparency isn't the default.

From Pinterest's perspective, the engineers violated trust. They accessed internal systems to extract data about employees, then built unauthorized tools around that data. In corporate security terms, that's policy violation regardless of intent.

From the engineers' perspective, they built a tool to answer questions management wouldn't address. In an environment of rolling layoffs and stealth terminations, knowing who's still on the team is practical information, not corporate espionage.

Both can be true.

Here's what makes this story notable: it exposes the power dynamic in tech employment. Companies want maximum information about employees—productivity tracking, keystroke monitoring, engagement metrics. But they punish employees who seek symmetrical information about the company.