Investigation: Meta explored slashing many teams by ~60% to become “AI native”, but pulled back after staff revolted and data showed AI agents were ineffective
To make its workforce “AI native,” Meta explored slashing the size of many teams across the company by as much as 60% in two waves, internal documents show.
ReutersKatie Paul
Context & Ripple Effects
Meta’s workforce strategy had already shifted sharply toward AI in 2026: it cut 8,000 jobs and reassigned 7,000 workers to AI initiatives in May, following reports that infrastructure costs were helping drive plans for deeper reductions. The newly reported internal deliberations show that the company tested a far more aggressive operating model than that earlier reallocation.
The account also gives the AI-first program an operational constraint: internal evidence indicated the agents were not effective enough to support the proposed staffing model. Public reaction focused on the associated morale and engineering-retention risks, though those assessments are opinions rather than established outcomes.
First-order effects
Meta’s pullback preserves human team capacity that the proposed reductions would have removed, while making ineffective AI agents unsuitable as a near-term substitute for those teams.
The AI organization built through May’s transfer of more than 1,000 engineers faces greater pressure to demonstrate dependable operational results, not simply deploy generative-AI systems.
Second-order effects
Meta’s workforce planning must separate roles where agents can assist employees from roles where they can reliably replace them, limiting the use of broad headcount targets as a proxy for AI productivity.
Staff opposition becomes an execution risk for further restructuring at Meta, adding retention and organizational stability to the criteria for any renewed AI-driven cuts.
Third-order effects
If similar internal validation failures recur, large employers’ “AI-native” reorganizations will move toward measured automation of specific workflows rather than company-wide staffing reductions based on projected agent capability.
The episode points to a more disciplined enterprise-AI cycle in which workforce redesign depends on demonstrated agent reliability and change-management capacity, not executive ambition alone.
The trend:Enterprise AI adoption is moving from broad automation narratives toward evidence-based deployment, with proven agent performance becoming the threshold for workforce restructuring.
The sense inside of Meta is Zuck + the exec layer just hates employees If this was not the case, at least someone would have had the backbone to say that firing people looks good on paper, but the strength of a team + company is in the people it has https://x.com/...
Well this is damning and explains SO MUCH about why Meta is losing its best engineers; why morale is rock-bottom; and why an engineering culture built up in 20 years was destroyed overnight. Zuck + execs wanted to lay off ~60% of staff. When the business does better than ever.
For all of us that spend countless hours working with Meta teams and products this article helps to explain 2026 in a nutshell working with the behemoth.
@GergelyOrosz I think the worst impact AI is having is feeding CEOs delusion that employees are just a necessary evil in their way to the chase for power, status and money
I claim partial responsibility for the desire to lay off 60% of the staff since in my farewell email told Mark he probably only needed 10% of the engineers. And, today I even more than back than I stand behind that number. They just did not execute properly.
Meta is the clearest example of a CEO having AI psychosis. You can't just cut 60% of the company...100% will try to leave. You'll never successfully make the jump to the AI future. As I have said repeatedly: No company openly hates their employees more than Meta
meta considered firing a bunch of people and replacing them with AI but didn't because it wouldn't remotely work! Feels like a huge story, and makes me wonder what the people talking about “Zuck's AI assistant” or “Meta's agents” were huffing
I still remember the time, around 2015, when working at Facebook was a sign of high prestige in tech. Nowadays, I don't know a single sane person who would even consider applying at Meta.
So even the companies at the leading edge of AI research that own their own data centers can't figure out how to make “AI agents” work... and we're spending $1 trillion a year on what, exactly?
And look, I'm not saying you should not work for Meta. But if you work for it, ONLY do it for the money. What mission does a company have where the mission (signed off by all execs) is to fire 60% of staff? That's a mission a company caring 0% about staff, 100% about minimizin…