Over the past few weeks, the headlines have been difficult to ignore.
Meta announced plans to cut 10% of its global workforce, roughly 8,000 employees with cuts beginning on May 20. Microsoft reduced headcount. Oracle laid off as many as 30,000 people. Snap eliminated 16% of its staff. So far in 2026, more than 113,000 workers across the technology sector alone have lost their jobs.
The headlines frame this as an AI story. Companies are investing hundreds of billions in AI infrastructure while simultaneously cutting the people who used to do the work AI is now doing. The narrative is efficient: machines in, people out.
That story is partly true. But it is missing something important.
Most of the people who lost their jobs at Meta, Microsoft, and Oracle were not replaced by AI. They were released as part of a broader recalibration — organizations restructuring spans of control, removing management layers, and consolidating teams that grew too quickly during a period of cheap capital and aggressive hiring. AI provided a useful rationale. It is not always the actual cause.
This distinction matters because the lesson most professionals are drawing from these headlines is the wrong one. The lesson is not to learn AI as fast as possible and hope that protects you. That thinking puts your security in your technical currency, which changes every eighteen months.
The professionals I watched hold on through restructuring after restructuring across twenty years in global organizations, shared a different quality.
They were trusted.
Not trusted because they were liked. Not trusted because they were loyal in the sentimental sense. Trusted because their organizations had enough evidence, accumulated over time, that these individuals could be counted on to behave predictably, communicate clearly, and make sound decisions without constant supervision.
When headcount decisions are made, that evidence does not live on a performance scorecard. It lives in the quiet impressions formed over months of working alongside someone. It lives in the hallway conversations, the meeting behaviors, the way someone handled a difficult quarter or a leadership change.
This is what most professionals are not managing deliberately.
They are managing their output. They are not managing their organizational reputation. Those are not the same thing, and in a market where 113,000 jobs have disappeared in less than five months, that gap has never been more expensive.
The professionals who survived last month’s cuts were not necessarily the highest performers on paper. They were the ones whose managers could not imagine explaining their absence to a senior leader. That is a different kind of value — and it is built before any restructuring announcement is ever made.
If you are in a stable role right now, the temptation is to wait and watch. To keep delivering and assume that performance is protection. It is a factor, it is not a guarantee.
What protects you in a market like this one is the accumulated trust that makes your name the one a manager says out loud when someone asks who cannot be lost. That reputation is not built during a restructuring. It is built in the quiet months before it.
The time to work on it is now, not when the headlines get closer to your industry.
If you are navigating a new role and want to build that foundation deliberately, I built First 90 Coach — a free AI companion on the OpenAI GPT Store trained on the frameworks in The Ultimate Impression. It is designed for exactly the window where organizational trust is formed.
