Zuckerberg is Building an AI Agent to Assist Him as CEO

marsbitPublished on 2026-03-23Last updated on 2026-03-23

Abstract

Meta CEO Mark Zuckerberg is developing a personal AI agent to assist him in his executive duties, enabling faster information retrieval and reducing reliance on hierarchical reporting. This initiative is part of Meta’s broader effort to become an "AI-native" company, streamlining operations and increasing efficiency amid growing competition from smaller, agile AI startups. Internally, Meta is encouraging widespread AI adoption, with tools like My Claw and Second Brain—an AI "chief of staff"—gaining traction among employees. The company has also made acquisitions to bolster its AI capabilities. However, this shift has raised concerns about potential layoffs, as Meta reportedly considers significant workforce reductions to align with its new AI-driven structure.

Author: Long Yue

Source: Wall Street News

With the deepening application of AI technology, Meta is attempting to reshape the way of work by building an "AI-native" enterprise, starting with its CEO, Mark Zuckerberg.

Recently, Meta CEO Mark Zuckerberg was revealed to be developing a proprietary "CEO agent" to help him perform his duties more efficiently.

According to sources familiar with the matter who spoke to The Wall Street Journal, the AI agent Zuckerberg is developing is still in the development stage. Its main function is to help Zuckerberg access information more quickly. In the past, he might have needed to go through layers of reporting to get answers, but now, this AI agent can directly retrieve and provide the information he needs.

This project reflects a culture within Meta: accelerating the pace of work, eliminating redundant layers in the organizational structure, and changing the daily work methods of employees. Meta has about 78,000 employees. Facing much smaller but highly competitive AI-native startups, Meta believes that fully adopting AI is key to maintaining competitiveness.

Zuckerberg hinted at AI efficiency during the earnings call in January: one person can do the work of a team. He said, "We are investing in AI-native tools so that individuals at Meta can accomplish more work. We are elevating the status of individual contributors and flattening teams." He is beginning to see that "projects that used to require large teams can now be completed by one very talented person."

Internal AI Adoption: From My Claw to Second Brain

Within Meta, the use of AI tools has rapidly become widespread. This is partly because the use of AI tools is now a factor in employee performance evaluations. According to sources familiar with the matter, Meta's internal message boards are filled with employees sharing new AI use cases and new tools they have built using AI.

Employees have begun using personal agent tools like My Claw. These tools can access their chat histories and work files, and can even communicate on their behalf with colleagues—or the colleagues' personal agents.

Another AI tool called Second Brain has also gained significant attention internally. Sources familiar with the matter revealed that this tool, which is somewhere between a chatbot and an agent, was built by a Meta employee based on Claude. It can index and query documents for projects. In the internal post announcing the tool, the employee described it as "designed to be an AI chief of staff."

There is even a dedicated group on the internal message board for employees' personal agents to communicate with each other. Additionally, Meta recently acquired the AI agent social media site Moltbook and hired its founder. At the same time, Meta also acquired the Singaporean startup Manus, which creates personal agents that can perform tasks for users. Meta is currently using this tool internally.

Organizational Reshaping: Ultra-Flat Structure and the Shadow of Layoffs

To accelerate the development of large language models, Meta recently established a new Applied AI Engineering organization. It is reported that these teams will adopt an ultra-flat structure, with up to 50 individual contributors reporting to one manager.

Maher Saba, the Meta executive responsible for the new organization, said in an internal post announcing the new teams: "We designed this organization to be AI-native from day one." These teams will report to the company's Chief Technology Officer, Andrew Bosworth.

However, this rapid change and focus on AI usage has also sparked anxiety among some employees about potential layoffs. Wall Street News recently wrote that Meta is planning large-scale layoffs, potentially reaching 20% or even higher. Based on Meta's approximately 79,000 employees as of the end of December last year, this layoff would affect over 15,000 people.

Related Questions

QWhat is Mark Zuckerberg developing to help him perform his CEO duties more efficiently?

AMark Zuckerberg is developing a personal AI agent, currently in the development stage, to help him retrieve information directly and perform his duties more efficiently.

QAccording to the article, what is one of the main functions of Zuckerberg's AI agent?

AThe main function of the AI agent is to help Zuckerberg get information faster by directly retrieving and providing the information he needs, eliminating the need to go through layers of reporting.

QWhat internal AI tool, built on Claude, is described as an 'AI chief of staff' at Meta?

AThe internal tool called 'Second Brain', which was built on Claude by a Meta employee, is described as an 'AI chief of staff' and is used to index and query documents for projects.

QHow is Meta's new applied AI engineering organization structured to be 'AI-native'?

AThe new applied AI engineering organization is designed with an ultra-flat structure, where as many as 50 individual contributors report to a single manager, reflecting an AI-native design from the start.

QWhat concern among employees is mentioned as a result of Meta's rapid AI adoption and changes?

AThe rapid changes and focus on AI usage have sparked anxiety among some employees about potential large-scale layoffs, with reports suggesting cuts could affect over 15,000 people.

Related Reads

The Recursive AI Anthropic Warned About: Tian Yuandong's New Company Has Just Taken the "First Step"

Anthropic recently highlighted the rapid progress toward "recursive self-improvement," where AI systems autonomously design and train their successors. In response, Recursive Superintelligence, a new company co-founded by former Meta researcher Tian Yuan Dong, has publicly demonstrated its first step toward automating AI research. The company released a system designed to autonomously execute the full AI research cycle: generating ideas, implementing code, running experiments, and learning from results. It validated this approach by achieving state-of-the-art results on three diverse benchmarks: 1. **NanoChat Autoresearch:** Optimizing a small language model's validation loss under a fixed 5-minute GPU budget, improving upon the community's best result. 2. **NanoGPT Speedrun:** Reducing the time to train a GPT model to a specific loss on 8 H100 GPUs from 79.7 seconds to 77.5 seconds, beating a highly optimized, human-driven community effort. 3. **SOL-ExecBench:** Improving the overall score on NVIDIA's suite of 235 GPU kernel optimization tasks by 18%, closing the gap to the hardware limit. The system discovered novel optimizations in this highly specialized domain without direct human expertise. Recursive's system operates as a general framework, capable of parallel exploration and cross-task knowledge transfer while incorporating safeguards against reward hacking. The company, backed by $650M in funding and a star-studded team including Richard Socher and Alexey Dosovitskiy, aims to create AI that recursively enhances its own research capabilities. This development represents an early but concrete move toward a new paradigm where AI accelerates its own advancement. It occurs alongside Anthropic's warnings about the need for industry coordination and potential pauses when recursive self-improvement thresholds are reached, highlighting the dual trajectory of rapid technical progress and growing calls for careful stewardship.

marsbit4m ago

The Recursive AI Anthropic Warned About: Tian Yuandong's New Company Has Just Taken the "First Step"

marsbit4m ago

The Gold Buy-on-the-Dip Guide: Watch Interest Rates, Not Just War

"Gold Buying Guide: Focus on Interest Rates, Not Just War" Four months ago, gold buyers likely didn't anticipate buying at a peak that even a war couldn't sustain. After hitting a record high of $5,596 on January 29, gold entered a bear market just 91 days later, its fastest decline since 2008. A key trigger was the Fed's hawkish shift, highlighting that monetary policy, not geopolitics, is the primary driver. The article argues that the traditional "buy gold in turmoil" script has changed. While the US-Iran conflict initially boosted prices, the sustained rally in oil prices heightened inflation fears, forcing central banks to maintain or consider tighter policy. Since gold yields no interest, higher rates increase its opportunity cost, eroding its appeal. This dynamic was evident when gold fell sharply on May 18 despite positive peace talks, as lower oil prices eased inflation and thus rate hike pressures. The recent sell-off is also part of a broader market deleveraging. Correlations between gold, Nasdaq, and Bitcoin spiked as leveraged investors sold liquid assets to cover losses, creating a synchronized downturn. Historically, gold bottoms align with policy shifts, not conflict resolutions. The 2008 and 2022 bear markets ended with shifts to extreme easing and peak inflation expectations, respectively. For potential buyers, the author suggests monitoring three signals: 1) Peak interest rate hike expectations, 2) Reopening of the Strait of Hormuz (to ease oil/inflation pressure), and 3) A return to net inflows for Gold ETFs, indicating the end of forced selling. While predicting the exact bottom is impossible, the author's personal strategy involves scaling into a position across price levels like $4000, $3700, and $3500, committing no more than 30% of the intended total allocation initially, and adding the remainder only if key signals emerge. The core conclusion: In turbulent times, watching interest rates is more crucial than watching wars.

marsbit10m ago

The Gold Buy-on-the-Dip Guide: Watch Interest Rates, Not Just War

marsbit10m ago

Recent On-Chain Review: No Clear Narrative Under U.S. Stock Market Pressure, Just Hype

This article analyzes the current state of the Solana meme coin and community token ecosystem, highlighting a market caught between two dominant forces: attention-based PvP and a gradual return to community-centric projects. The first part explores the "Attention PvP" dynamic, where success is driven by celebrity endorsements, viral events, and speed. Examples include $JOTCHUA, which surged after its meme creator's social media activity, and $WORLDCUP, which outperformed a similar Base chain project ($PITCH) largely due to influencer support. The recent "pump.fun GO" feature, allowing bounty tasks for token promotion, is critiqued for fostering sensationalist and often negative stunts—like people getting token tickers tattooed on their bodies for rewards—reminiscent of old internet shock content. In contrast, the article points to a resurgence of organic, community-driven tokens that survive market volatility through strong holder bases and shared ideology, not just hype. Influencer Ansem is cited, arguing that durable meme coins rely on communities willing to endure losses and promote their core message daily. Examples given are older tokens like $neet (anti-work ethos), $troll, $buttcoin, and $triplet, which have maintained relative price stability. A prime example of this community-build model is the new project $KINS, the token for the browser-based MMORPG Kintara. Its success stems not from advanced graphics but from consistently delivering updates, fostering player trust, and creating genuine engagement (e.g., in-game economies, events, property auctions). It has attracted a growing player base and even notable KOLs as participants, demonstrating that sustainable growth can come from building trust rather than orchestrating pumps. The article concludes by questioning whether the market is ultimately a game of mutual trust or mutual deception, expressing hope that such reflection might lead to a healthier ecosystem.

marsbit10m ago

Recent On-Chain Review: No Clear Narrative Under U.S. Stock Market Pressure, Just Hype

marsbit10m ago

On-Chain Scene on Opening Day: $20 Billion Already Staked, How Do On-Chain Contracts Know Who Wins?

On the opening day of the 2026 World Cup, over $2 billion had already been wagered on just the "tournament winner" contracts on platforms like Polymarket and Kalshi. This article explores how these blockchain-based prediction markets actually function once the games begin. It breaks down the massive volume and explains how single-game and tournament-long contracts are priced, with values moving between 1-99 cents to reflect implied probabilities. A key mechanism highlighted is "elimination zeroing," where a team's "champion yes" contract immediately settles to zero once they are mathematically eliminated. The core technical question answered is: how does a smart contract "know" who won a real-world match? The answer lies in oracles. The article details two primary paradigms: UMA's "optimistic oracle" (used by most of Polymarket), which allows a challenge period after a proposed result, and Chainlink's multi-source data aggregation (used by FIFA partners like ADI Predictstreet), which automates settlement with minimal dispute windows. Finally, the article injects a note of caution, citing research estimating that a significant portion of historical trading volume on these platforms might be "wash trading" to inflate numbers. It concludes by contrasting the legal status of these "event contracts" under CFTC rules in the U.S. versus traditional, state-regulated sports betting. As the tournament progresses, the real-time operation of this multi-billion dollar machine—its settlements, eliminations, and underlying mechanisms—becomes a story as compelling as the football itself.

marsbit26m ago

On-Chain Scene on Opening Day: $20 Billion Already Staked, How Do On-Chain Contracts Know Who Wins?

marsbit26m ago

Trading

Spot
Futures

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of AI (AI) are presented below.

活动图片