On the same timeline, two seemingly unrelated news stories are quietly aligning: on one side, Paul Mead, who has been rooted in Apple's hardware engineering team since 2010 and has been responsible for Vision Pro-related hardware since 2017, playing a key role in XR and spatial computing projects, has been reported to be leaving Apple, planning to join OpenAI's hardware department, the specifics of which have not yet been announced; on the other side, Animoca Brands, which has over 600 portfolio companies globally, announced a strategic investment in AllScale, a stablecoin payment infrastructure company, and plans to explore applying AllScale's stablecoin payment solutions among its portfolio companies, which is regarded as laying the groundwork for an open metaverse economy and future AI agent payments. This side witnesses AI large model camps poaching senior XR terminal leaders from Apple, attempting to reshape the form of "devices" in the AI era; while that side sees Web3 veterans building foundational infrastructure for autonomous economic activities behind AI terminals through unified on-chain payments and settlements. The battles for terminals and payment pipelines progress in parallel over time, structurally intertwining, pointing to the same main line: AI capabilities are no longer confined to cloud computing power but are sinking along two tracks of hardware terminals and on-chain payments. The intersection of AI and cryptographic infrastructure may become the real main battlefield for the next round of layouts.

Apple's XR Veteran Moves, Vision Pro Faces Pressure

If we localize the abstract front of "the war for AI terminals" to a name, on the Apple side, it corresponds to Paul Mead. According to a single source, he has been part of Apple's hardware engineering system since 2010 and is one of the few senior engineering managers who have transitioned from the era of Intel chips all the way to the era of spatial computing. From 2017 onwards, he was transferred to Apple's XR and spatial computing projects, responsible for Vision Pro-related hardware engineering, essentially standing on the front line of this new battle before the product has even seen the light of day. Vision Pro is Apple's first spatial computing device, seen as the company's significant bet in the XR space, and the departure of the veteran responsible for its hardware engineering removes a key piece from the center of this bet.

Public information shows that this person, who has been in charge of hardware engineering for Vision Pro for many years, has recently been reported to be leaving Apple to join OpenAI's hardware department, with the reason for departure not yet disclosed. For Apple, this is not just a name disappearing from the roster but also a vacancy in the XR landscape that needs to be quickly filled: with someone deeply involved in Vision Pro hardware engineering since 2017 leaving, it means that much implicit knowledge about architecture choices, supply chain coordination, and iteration paths will be extracted from the team in a short time. In terms of the XR market, Meta continues to ramp up with the Quest series, while Google is also exploring spatial computing and related devices, with industry competition clearly heating up in the mid-2020s; losing a veteran who has been deeply embedded in Apple's hardware system since 2010 and has been carrying the Vision Pro hardware engineering since 2017 means that every step Apple takes on the XR battlefield will be scrutinized more intensely by competitors.

OpenAI's Bold Move: From Software to Terminal

When a veteran who has been deeply involved in Apple's hardware system since 2010 and has led the Vision Pro hardware engineering work since 2017 is publicly pointed towards joining OpenAI's hardware department, what the outside world truly reads is a declaration of intent written on a resume: OpenAI is not content to be a company that exists only in the cloud and on screens. The undisclosed job title itself is a posture—product form can be put aside, but the four words "hardware department" are enough to indicate that this leading AI company aims to move from software and models to concrete, tangible AI terminals.

For OpenAI, the potential motivation for extending from cloud to terminal is not hard to guess: whoever controls the device is closer to the user's daily scenes and has a better chance to determine the forms and frequencies of AI interactions. Bringing in an experienced engineering manager like Paul Mead, who has honed his skills on complex hardware systems and spatial computing devices, into a hardware team that has not yet publicly announced specific products indicates that OpenAI hopes to directly benchmark its engineering capabilities against traditional hardware giants in terms of structural design, system integration, and long-term iteration rhythm of AI terminals. In the AI wave, major tech companies have increasingly relied on poaching key executives to expand hardware teams, and now even a company as tightly closed and solidified in hardware engineering as Apple faces the reality of its core talent being siphoned off by AI companies; this talent war that extends from software to terminals will directly reshape the power landscape for the next generation of AI devices.

Animoca Bets on AllScale Payment Infrastructure

While talent is being contested by AI giants, capital is also betting on the next generation of infrastructure. Animoca Brands, a long-time player betting on the "open metaverse," has chosen to place its chips on a seemingly mundane pipeline—on-chain payments. Recently, Animoca announced a strategic investment in AllScale, which focuses on anchor asset payment infrastructure, without disclosing the amount or equity details, yet emphasizing its position within its own territory: not a tactical patch for a single project, but the underlying pipeline for the entire Web3 ecosystem.

For Animoca, AllScale is not an isolated puzzle piece. According to a single source, among its more than 600 portfolio companies, Animoca plans to gradually explore integrating AllScale's on-chain payment solutions to consolidate the settlement logic that is originally scattered across different projects into a unified infrastructure. In the official narrative, this pipeline has two clear purposes: first, to facilitate internal value transfer within its own open metaverse ecosystem, allowing payments between games, asset markets, and applications to no longer operate independently; second, to lay the groundwork for future AI-driven automated transactions—when AI agents and smart terminals begin to autonomously initiate payments and settlements on-chain, they will need a stable, programmable, and widely accepted payment network. Echoing the earlier talent war for hardware, while technology and Web3 companies are competing for talent to create terminals on one side, on the other side they are racing against time to build pipelines, Animoca's bet on AllScale is based on the premise that AI agents and the open metaverse will ultimately need a reusable economic artery.

The Dark Line Intersection of AI Terminals and Payment Pipelines

When talents like Paul Mead leave Apple for OpenAI's hardware sector, viewing this transition over a longer timeline reveals that he is not merely changing jobs but moving from "creating terminals" to "creating agent interfaces." OpenAI attracting senior engineering managers to hardware aims to compete for a medium closer to users for AI agents; however, even the most powerful terminal, if it can merely understand instructions and generate content but cannot autonomously complete orders, settlements, and renewals, can only remain a "smart screen," not an "autonomous economy entity." To enable AI terminals and AI agents to possess true operational capabilities, they must be linked to a set of stable, programmable, and widely accepted payment and settlement foundations.

This foundation is being laid by another player on the other end. For Animoca, betting on AllScale means attempting to connect the economic interactions of over 600 portfolio companies into a unified network using an on-chain payment solution anchored to fiat currency within its vast ecosystem, while reserving payment interfaces for future AI agents. In the current Web3 world, this kind of anchored asset plus on-chain settlement has already become one of the few realistically usable cross-border payment paths; once AI agents are allowed to directly utilize this pipeline, they can autonomously purchase services, pay for subscriptions, and engage in value exchanges in games and applications on the open network. This forms a division of labor: Apple and OpenAI enhance "touchpoints" and "computing power" on the terminal and hardware side, while Animoca solidifies "vessels" and "ledgers" on the payment and settlement side, together constituting two sides of the infrastructure in the AI era. Meanwhile, cryptographic assets are being re-embedded into a more concrete application pathway, where their value is no longer just about passive holding but finding new use cases in the high-frequency, automated economic behaviors of AI agents.

The Next Dividend is in Talent and Infrastructure

From Paul Mead's years of deep work in hardware engineering at Apple since 2010 to the recent reports of his shift to OpenAI's hardware team, and Animoca betting on AllScale on the same timeline, these two threads clearly outline the core contradictions in the narratives of AI and Web3 of the mid-to-late 2020s: those who can first "extract" top talent from traditional giant systems to build AI terminals and hardware teams will have the opportunity to occupy the next round of entry points; those who can first pave the way for on-chain payment infrastructure targeting AI agents, allowing machines to autonomously complete settlements in open networks, will have the chance to influence the direction of the new generation of economic pipelines. For readers, what needs to be monitored going forward is not just isolated news points, but the continuous construction of AI hardware teams, the expansion of payment pipelines in more scenarios, and the accompanying movement of executives and capital infusion, which will form a longer trend curve over time. In the medium term, the evolutionary direction of the intersection between AI and crypto is likely to repeatedly reconfigure around "edge computing power + on-chain settlements," but under the still highly uncertain premises of regulation and technological evolution, any assumptions about the scale of returns or timelines for implementation can only be theoretical rather than commitments, and the true dividends of this pathway will favor long-term, ongoing observation and making prudent choices at critical turning points.

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