Meta Platforms is reportedly pulling top software engineers from across the company into a newly created AI unit on a mandatory basis, with the stated goal of eventually having autonomous agents perform the bulk of the work of building, testing, and shipping its products, and human engineers serving only to monitor them.
The development was based on an internal company memo authored by Maher Saba, a vice president in Meta’s Reality Labs division and a longtime associate of Chief Technology Officer Andrew Bosworth, who leads the new Applied AI (AAI) Engineering organization, reported Reuters. According to the report, Saba created AAI last month and initially sought volunteers to join. This week, he told selected employees their transfers are no longer a choice.
“AAI is one of the company’s highest priorities and we’re resourcing it by moving our strongest talent to address it. Therefore, the transfers aren’t optional,” Saba wrote in the memo, the report added.
The unit’s mandate goes significantly beyond building AI productivity tools. According to the memo AAI’s stated end goal is for autonomous AI agents to perform the bulk of the work required to build, test, and ship Meta’s products and infrastructure with human engineers monitoring rather than executing.
Gartner predicts that AI agents will require 80% of the engineering workforce to upskill by 2027, and separately forecasts that 40% of enterprise applications will embed task-specific AI agents by year-end 2026, up from less than 5% in 2025.
“Meta’s move signals that AI is now being fundamentally positioned within engineering as a core execution infrastructure, rather than just as a productivity layer,” said Ishi Thakur, senior analyst at Everest Group. “Competitive advantage will hinge less on access to models and more on how deeply organizations can embed AI into real-world engineering workflows.”
But analysts caution that the path there is far from straightforward. “For Meta-scale firms, agent-led engineering is achievable only in tightly scoped domains today,” said Charlie Dai, VP and principal analyst at Forrester. “Before reducing hands-on developer responsibility, enterprises must establish robust evaluation harnesses, policy-as-code controls, deterministic build pipelines, and explicit human escalation paths.”
What AAI is building
AAI will work alongside Meta’s Superintelligence Lab, headed by former Scale AI CEO Alexandr Wang, to build what Saba described as “the data engine that helps our models get better, faster,” according to the report. The organization consists of two teams: one focused on interfaces and tooling, and a second responsible for executing tasks, generating data, and providing evaluations that feed back to Meta’s modeling teams.
“This reflects a growing belief that traditional management layers will become less relevant as AI absorbs coordination and execution tasks,” said Thakur. “Value is concentrated in high-skill individual contributors augmented by AI.”
Dai cautioned that the structure carries significant governance risk. “If provenance tracking, gated approvals, and automated security testing are not mandatory, AI-generated code can overwhelm oversight and erode accountability for quality, compliance, and audits,” he said.
On Meta’s Q4 2025 earnings call in January, CEO Mark Zuckerberg said 2026 would be “the year that AI starts to dramatically change the way that we work.” Susan Li, Meta’s chief financial officer, said on the same call that output per engineer had already risen 30% since the start of 2025, driven largely by AI coding agents, with power users recording an 80% year-over-year productivity increase.
For Meta, AAI is the next step in embedding that trajectory deeper into its engineering infrastructure.
Workforce reductions ongoing
Separately, Meta has been reducing its overall headcount in 2026. The company has already cut approximately 10% of its Reality Labs division in January, affecting around 1,000 employees, and laid off several hundred more in late March across recruiting, sales, global operations, and Facebook social teams.
Meta’s capital expenditure for 2026 is projected between $115 billion and $135 billion, nearly double its 2025 spend, driven by investments in data centers, chips, and AI infrastructure. The company formalized that infrastructure drive with the launch of Meta Compute, consolidating its global data center and network operations under a single leadership structure.
“The dominant barrier is organizational,” said Dai. “Enterprises have not yet redefined ownership, incentives, and liability when software is produced by agents. Until accountability frameworks catch up, leadership caution will continue to slow adoption.”
Thakur put it plainly: “The real constraint is no longer technological capability, but whether organizations can evolve their operating models fast enough to responsibly absorb this level of autonomy.”
Meta did not immediately respond to a request for comment.