Why Meta is bringing back middle managers

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SPEAKER_5 (1:45)

Meta is quietly asking staff in its 7,000 person Applied AI Division to volunteer to return to manager positions, completely reversing the corporate strategy of eliminating middle management and forcing managers into individual contributor roles.

SPEAKER_6 (2:01)

Yeah, that flies directly in the face of the massive flattening efforts that accompanied the thousands of job cuts across their entire organization. I mean, they spent an incredible amount of energy dismantling that exact layer of leadership.

SPEAKER_5 (2:13)

They took scores of people holding management titles and moved them all into individual contributor roles in a very short window.

The entire push was aimed at creating a leaner, faster company. But now, specifically for this Applied AI group, they are actively looking for people to step back into the jobs they just finished eliminating.

SPEAKER_6 (2:32)

Which leaves a massive open question hovering over this whole strategy. When you strip out the managers from an organization of that size, does the management work actually disappear or does it just crush the people left behind?

SPEAKER_5 (2:44)

If you look at the details of this new program to reinstate managers, the most revealing aspect is that it is entirely opt-in. They're asking people to choose to go back into management.

SPEAKER_6 (2:56)

That voluntary nature proves the individual contributor roles weren't operating as cleanly or functionally as the flattened structure promised on a spreadsheet.

SPEAKER_5 (3:05)

Because you can eliminate a manager's title and you can remove their official position on the org chart, but you absolutely cannot eliminate the tasks they were doing. We are talking about the daily coordination across different technical teams, the ongoing prioritization of feature development, and the very human act of coaching someone through a difficult call they have never had to make before.

SPEAKER_6 (3:26)

If I'm playing devil's advocate here, what do those tasks actually entail in a highly technical environment? If you have a team of highly paid, highly specialized AI engineers, shouldn't they just be able to log in, write their code, and log out? What is a manager actually doing for them on a random Tuesday afternoon?

SPEAKER_5 (3:43)

Well, if you are listening to this, and you have ever had your boss suddenly quit or get laid off, you know exactly what happens next. The work does not stop. It just lands squarely on your desk.

In a software engineering team, especially in an area as complicated as training large AI models, the work is never just writing code in isolation.

SPEAKER_6 (4:04)

Because there are dependencies.

SPEAKER_5 (4:06)

Constant dependencies. Let's say team A cannot deploy their new model until team B finishes optimizing the data pipeline that feeds into it.

SPEAKER_6 (4:15)

And someone has to track that dependency. If there is no manager whose explicit job is to monitor that intersection, that tracking work doesn't vanish into thin air. It lands somewhere. Usually it lands on your most expensive, most experienced technical specialists.