Track market-moving stories before they get noisy

Updated Jul 23, 2026, 4:15 p.m. Published Jul 23, 2026, 1:00 p.m.

4 min read

Digital surveillance (Getty Images/Victor de Schwanberg/Science Photo Library) The Kids Internet and Digital Safety (KIDS) Act sounds like it’s all about protecting kids from bad things on the internet. In truth, this mishmash of over a dozen privacy-invasive, censorship-friendly requirements and regulations could actually put children — and all internet users — at risk.

The package, which includes a revised version of the Kids Online Safety Act (KOSA), passed the House on June 29 and is now being considered in the Senate. If enacted, it will incentivize platforms to require all users — adults and minors alike — to hand over personal information that links their offline identity to their online activity.

That’s because many different sections of the bill require online providers to establish and enforce policies to prevent children and teenagers from accessing certain types of broadly defined content. Violators can face significant legal action by the Federal Trade Commission and state attorneys general.

To attempt to steer clear of trouble, websites and social media platforms may decide to age-gate all users — that is, verify, guess, or estimate users’ ages.

This will effectively create a new mass surveillance system. Whatever you may think about the state of privacy protections in the U.S., your current online usage is not necessarily linked to your specific identity. If this bill passes, that will likely change.

The fact that lawmakers are even contemplating a bill that would create a surveillance and censorship regime should be a wake-up call for everyone who values privacy and free expression.

This is a privacy pitfall, not just some benign form of digital “carding.” If the bill passes, the bouncer at the door will now be an online entity that will electronically capture your personal information and save it to a database for an unspecified amount of time. Providing this identifying information would be the price that any user must pay to access legal, First Amendment-protected content on the internet or to communicate with others online.

On top of that, once you turn your personal information over, it’s now vulnerable to leaks, data theft, or misuse. This isn’t just a hypothetical: We’ve already seen several breaches of age verification providers.

The KIDS Act contains multiple sections that will lead to age-gating. For example, a provision in the SAFE BOTS Act section mandates that if a service “knows or should have known” that a user is underage, it can’t offer certain chatbot features. The SCREEN Act section requires hosts of sexually explicit content to figure out if users are “more likely than not” underage before
letting them access certain content.

In this bill, platforms are liable for ensuring kids and teenagers are walled off from content targeted by the KIDS Act, but the consequences of this liability don’t just affect minors. It means platforms will be pressured to make adults prove they are adults, underscoring how this legislation will make everyone’s online experience less private.

It will also push online services to create moderation policies against lawful speech to wall off content some legislators believe is harmful to minors. But as we’ve seen many times in the past, while lawmakers may be clear in the debate about what they intend with these restrictions, platforms are notoriously bad about separating discussions about harmful activities from discussions about getting help for harmful activities.

For example, let’s say a 15-year-old expresses concern about a friend’s drinking or 13-year-old seeks information about how to get his parent to stop smoking. These individuals would be engaging in perfectly lawful speech about topics the KIDS Act has labeled as harmful. Those posts aren’t intended to be banned under the bill, but if platforms are supposed to prevent minors from accessing content about alcoholism or cigarette smoking, many will adopt practices
that either remove those topics entirely or restrict them to adult-only spaces. We know from experience that the threat of legal action pushes platforms and content providers to over-remove or restrict content.

Separately, several provisions of the bill also create new rules around encrypted messages, direct messages, disappearing or “ephemeral” messages, and AI chat services. While the text says that KOSA requirements shouldn’t be construed to override strong encryption, the protection may be meaningless because it doesn’t apply to KOSA’s mandate that services “address” content lawmakers have decided is harmful to minors.

Platforms can’t address that content if it’s in messages they can’t see. That creates pressure on them to weaken or limit encrypted messaging. Similarly, other bill provisions target “ephemeral” or disappearing messages — as on Signal or WhatsApp — for the same reasons. But end-to-end encryption and ephemeral messages are not superfluous design features. They are extremely valuable privacy tools for sustaining real-world, back-and-forth conversations online that aren’t accessible by service providers or data brokers or preserved forever in a permanent database.

In short, there are many ways to protect young people online that don’t require everyone to surrender personal information, jeopardize anonymity, and foster government-directed content moderation policies affecting lawful speech. Lawmakers could solve all the problems that this ill- conceived age-gating claims to address by passing a comprehensive federal data privacy law
that gives everyone power over the data that’s collected about them and thus how platforms’ algorithms are deployed against them.

Instead, Congress is seriously considering the KIDS Act, which seeks to protect the children at the expense of privacy and free expression for all internet users. This is not OK. If you agree, let your Senator know.

Note: The views expressed in this column are those of the author and do not necessarily reflect those of CoinDesk, Inc. or its owners and affiliates.

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Crypto Flows, Share and the Selective Rotation

Crypto Flows, Share and the Selective Rotation

Markets repositioned since June, but Binance held share (~55% user funds, ~24% spot) and drew net inflows in early July while the tracked market saw outflows.

Jul 22, 2026

Markets repositioned since June, but Binance held share (~55% user funds, ~24% spot) and drew net inflows in early July while the tracked market saw outflows.

Why it matters:

Markets repositioned since June, but Binance held share (~55% user funds, ~24% spot) and drew net inflows in early July while the tracked market saw outflows.

When it comes to bridging the gap between crypto and tangible assets, Shukyee Ma has become somewhat of a superstar. As the Chief Strategy Officer for Plume Network, Ma will take the stage at Money Frontier 2026, a summit seeking to spotlight actionable developments in the blockchain arena. Her slot on the agenda focuses on integrating real-world assets into on-chain financial products, a key part of Plume Network’s strategy.

Plume’s Plans for the Summit Money Frontier 2026 will unfold over two days—July 27 and 28—in the bustling hub of Hong Kong. Unlike events that concentrate on market trends, this summit emphasizes the real-world applications of blockchain tech. It’s fitting, then, that Ma is discussing how Plume Network, a Layer-1 blockchain known for its focus on Real World Asset Finance (RWAfi), is pioneering the conversion of tangible assets into digitized ones for the crypto-savvy.

Shukyee Ma isn’t new to this. Before joining Plume Network, she co-founded Polyhedra and has shared her insights at prominent industry gatherings like Solana Breakpoint and Devcon SEA. Under her strategy, Plume Network successfully raised $20 million in Series A funding in December 2024, an initiative that pushed its total funding to approximately $30 million. This wave of financial backing underscores market confidence in Plume’s vision.

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Adding to its list of achievements, Plume recently integrated its nBASIS RWA yield vault into Binance Wallet, enabling over 5 million users to access institutional-grade yields. Collaborations with 14 tokenized funds from WisdomTree and plans to tokenize parts of Japan’s massive equity market further cement Plume’s foothold in the RWA space.

The Market Implications But what does all this mean for the crypto market? The activities orchestrated by Ma and her team at Plume are indications of the growing appetite for tokenized assets among institutional players. A text from the financial markets playbook, perhaps: if you build a bridge, investors will cross it. The burgeoning tokenized RWA market, now estimated to have grown to around $25-27 billion, offers a fertile ground for investment opportunities.

By enhancing liquidity and accessibility, Plume Network, through its partnerships and integrations like the one with Binance Wallet, is simplifying the path to on-chain investments for traders accustomed to traditional finance methods. While this rush to tokenize can increase volatility—crypto’s middle name, some would say—it can also invite a broader demographic, seeking newer frontiers in asset yield and diversification strategies.

What Investors Should Watch Still, it’s not all sunshine and rainbows. As tokenization continues to evolve, regulatory factors loom large over its adoption trajectory. The ability of networks like Plume to navigate potential regulations while pushing their tokenization agendas will prove crucial. It’s summits like Money Frontier that provide the platform for achieving this, by fostering discussions that could pave the way for mutual understanding between stakeholders from the crypto and traditional financial sectors.

Those with skin in the game should maintain awareness of ongoing policy discussions that could impact these developments. The involvement of seasoned entities and the excitement of successful funding rounds like Plume’s exemplify an ecosystem that’s eager yet cautious, as it ventures into territories where digital meets everyday finance.

Disclosure: This article was edited by Editorial Team. For more information on how we create and review content, see our Editorial Policy.

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HTX H1 2026 Performance Report: Nearly $900 Billion in Trading Volume

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Sky Frontier Foundation just posted numbers that make the “DeFi is dead” crowd look a little silly. The organization behind the Sky Ecosystem, formerly known as Maker, revealed a $419 million annualized gross revenue run-rate in its June 2026 Financial & Operational Update, published Friday.

The numbers behind the milestone The $419 million run-rate didn’t materialize out of nowhere. Sky Protocol laid the groundwork earlier this year with a strong first quarter, generating approximately $123.79 million in gross revenue during Q1 2026 alone.

The protocol posted a surplus between $46 million and $61 million in Q1. The Sky Frontier Foundation, established in August 2025 specifically to support the broader ecosystem, anticipates the total revenue for the entire Sky Ecosystem to hit $611 million for the full year of 2026. That would represent a significant jump from the $338 million in gross revenues the protocol pulled in during 2025.

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USDS is the engine The growth story here is fundamentally a stablecoin story. USDS, Sky Protocol’s flagship stablecoin product, has become the primary revenue driver, with its combined stablecoin supply sitting near $11 billion currently.

The foundation projects USDS supply will reach $20.6 billion by the end of 2026, more than doubling from the $9.2 billion recorded at the end of 2025. Institutional investors seeking yield have been a meaningful driver of USDS adoption.

From Maker to Sky: the rebrand in context Sky Protocol is the rebranded version of MakerDAO, one of the oldest and most battle-tested protocols in decentralized finance. The rebrand included spinning up the Sky Frontier Foundation as a separate entity to manage grants, treasury operations, and ecosystem development. The foundation also manages resources for autonomous systems called Sky Agents, which support lending and stablecoin activities across the ecosystem.

What this means for investors If USDS supply really does reach $20.6 billion by year-end, it will force other stablecoin issuers to respond. For DeFi-native investors, the protocol surplus numbers matter more than the headline revenue figure. A surplus of $46 million to $61 million in a single quarter suggests the protocol has pricing power and operational efficiency that many competitors lack.

The $611 million full-year revenue projection assumes the current tailwinds persist. There is also the concentration risk inherent in a protocol that derives so much of its revenue from a single product line. USDS is the star, but the $419 million run-rate and $611 million full-year projection both depend heavily on continued institutional demand and stable macro conditions.

Disclosure: This article was edited by Editorial Team. For more information on how we create and review content, see our Editorial Policy.

LTP Launches the World’s First AI Agent Live Trading Championship — 200+ Teams, $300K+ in Prizes

Venture capital firm Paradigm has closed a $1.2 billion fund, marking a clear step in its evolution from a crypto-focused investor into a broader player supporting ambitious projects at the cutting edge of multiple technologies. The announcement, issued on July 8, 2026, positions the new vehicle to deploy capital across cryptocurrency innovations, artificial intelligence, robotics, and other emerging frontiers.

Founded in 2018 by Matt Huang, a former Sequoia Capital partner, and Fred Ehrsam, co-founder of Coinbase, Paradigm built its reputation through early bets in digital assets and blockchain infrastructure.

With this fourth fund overall (its third dedicated venture vehicle), the firm is formalizing an expanded mandate that reflects both the maturation of crypto markets and the rapid rise of complementary technologies.

While crypto remains central—covering areas such as decentralized finance, prediction markets, and blockchain tooling—the capital will also target AI systems and robotics applications where exponential progress is underway.

The firm’s official statement emphasizes a hands-on philosophy: staying close to the technology by researching, building, and partnering directly with founders.

It highlights the need for an adaptable mindset in an era of steep technological curves, where established approaches may no longer apply.

This approach has already produced results in non-crypto domains, including support for Zipline’s autonomous drone delivery network,

True Anomaly’s work in orbital space defense, SendCutSend’s rapid manufacturing capabilities, and Nous Research’s efforts to advance open AI models.

In the crypto space, Paradigm continues to back projects such as Hyperliquid for advanced trading ecosystems, Kalshi in prediction markets, and Tempo, a payments-focused blockchain incubated with Stripe.

Additional activity spans developer tools, agent infrastructure, and security research, including collaborations that bridge blockchain with AI capabilities.

The firm has historically invested from the earliest stages through later growth, and the new fund extends this flexibility across sectors.

The timing aligns with broader market dynamics. Artificial intelligence has attracted massive inflows amid breakthroughs in models and applications, while crypto has navigated cycles of volatility.

By broadening its scope, Paradigm seeks to capture synergies at the intersection of these fields—such as AI enhancing blockchain security, decentralized networks supporting robotic coordination, or robotics enabling new physical-world applications of distributed systems.

Industry reports note that several crypto-native firms are exploring similar overlaps, viewing AI and robotics not as distractions but as natural extensions of frontier technology investing.

With the fund now available for deployment, Paradigm gains fresh firepower to support founders tackling complex technical challenges.

The firm manages substantial assets overall and has demonstrated a track record of identifying high-conviction opportunities early.

Observers expect the capital to flow into both pure-play crypto infrastructure and hybrid projects where AI or robotics intersect with decentralized systems.

This move signals Paradigm’s view that the most transformative opportunities lie where multiple exponential technologies converge. Rather than abandoning its crypto roots, the firm is layering additional focus areas to remain at the forefront of innovation. Ambitious builders in these domains now have another well-resourced partner committed to long-term collaboration.

IO: Distributed GPU Clusters for Frontier AI: Cost, Architecture, and Where to Start

In brief Andy Konwinski, who cofounded Databricks and Perplexity AI, argued this week that concentrating AI power is a safety risk in itself. The essay followed Open Frontier, a working meeting of roughly 100 researchers in San Francisco on June 30. Turing Award winner Yann LeCun replied directly on X, comparing today's closed-lab AI moment to "medieval obscurantism akin to the Ottoman empire banning the use of the printing press for 200 years." Perplexity AI and Databricks co-founder Andy Konwinski thinks the AI safety conversation has a problem: It's being used to concentrate power, not prevent harm. Earlier this week, he published an essay making his case, with Anthropic as the star witness.

The case he builds starts with a decision Anthropic reversed in 48 hours. When Anthropic launched Claude Fable 5 on June 9, a paragraph buried in its 319-page system card disclosed that the model would silently degrade its own responses for anyone it suspected of training a competing AI.

Researchers found it. The internet did not take it well.

Anthropic walked it back, but for Konwinski this makes no difference when analyzing the bigger picture. "The problem isn't that Anthropic made a bad decision," he wrote. "The problem is that they assumed the decision was theirs to make."

His essay, titled "Concentration of power in AI is a risk, not a solution," followed Open Frontier, a working meeting he convened through his nonprofit Laude Institute at San Francisco's Exploratorium on June 30. About 100 researchers showed up.

UC Berkeley dean Jennifer Chayes, who runs the College of Computing, Data Science, and Society, told a funding panel that Berkeley researchers are "all building on Chinese models because we don't have a Western open frontier model"—and that the safety messaging from OpenAI and Anthropic ahead of their IPOs amounted to a "very effective fear campaign."

Konwinski's argument is that centralizing access doesn't neutralize risk; it creates a different one. AI is foundational infrastructure—in the same category as railroads, electricity, and the internet. Those technologies reorganized society around whoever controlled the underlying layer. The same is coming for AI. His alternative: a research commons with frontier-scale compute that lets top researchers reach the frontier without needing permission from a private lab to do it.

LeCun: It's the Ottoman empire banning the printing pressYann LeCun, Meta’s former chief scientist, replied to Konwinski's essay on X with no ambiguity. "I've been disseminating a similar message for years,” he replied on Konwinski’s post. “The concentration of power in AI and the desire for control is by far the biggest danger of AI."

Exactly. I've been disseminating a similar message for years.

The concentration of power in AI and the desire for control is by far the biggest danger of AI. It could lead to a few private companies and/or countries being in control of access to information, access to…

— Yann LeCun (@ylecun) July 3, 2026

He also had a historical comparison ready. "It's a kind of medieval obscurantism akin to the Ottoman empire banning the use of the printing press for 200 years, in part to keep control of the dogma, but also to protect the corporation of the calligraphers and scribes," LeCun wrote.

LeCun’s prediction for where this ends: "Infrastructure wants to be open. Foundation models are becoming an infrastructure and will inevitably become commoditized. Long term, the money is in the application layer."

LeCun left Meta in late 2025 and launched AMI Labs in Paris with $1.03 billion in seed funding in March 2026—his own answer to the question. The company runs on world models and his JEPA architecture, plans to open-source its research, and has no commercial product expected for years.

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Microsoft Commits $2.5 Billion to New AI Deployment Business

Key Highlights Table of Contents

Key HighlightsTech Giant Establishes Frontier Division for Corporate AI SolutionsStrategy Focuses on Multi-Model AI ImplementationShares Rise Amid Intensifying AI Consulting CompetitionGet 3 Free Stock Ebooks Microsoft shares increased 1.86% following the announcement of its Frontier AI business division worth $2.5B.

The division will assist corporate customers in selecting and implementing AI technologies.

6,000 Microsoft employees will be stationed at client locations through this initiative.

The strategy emphasizes adaptable AI frameworks and integration with proprietary client data.

This initiative intensifies Microsoft’s competition in the corporate AI consulting market.

Microsoft (MSFT) shares advanced 1.86% to reach $391.42 as the technology company announced plans to expand its corporate AI offerings. After opening lower, the stock reversed course and maintained gains close to its session peak. The upward movement came after Microsoft revealed its intention to establish a $2.5 billion AI-focused business division.

Microsoft Corporation, MSFT

Tech Giant Establishes Frontier Division for Corporate AI Solutions Microsoft announced the creation of Microsoft Frontier Company, a new operational division designed to assist enterprises in navigating AI technology selection and implementation. The division will serve prominent clients such as Unilever and Novo Nordisk, concentrating on AI frameworks that deliver measurable returns and practical business applications.

The Redmond-based company is allocating $2.5 billion to this initiative as corporate appetite for AI solutions continues expanding. The plan involves deploying 6,000 personnel directly at client sites through a forward deployed engineering model. These deployment teams will comprise technical advisors, customer support professionals, account managers, and vertical market experts.

Rodrigo Kede Lima, previously overseeing Microsoft’s operations across Asia, has been appointed as president of the division. The organization will merge Microsoft’s current AI consulting teams with on-site engineering resources. This shift represents Microsoft’s evolution from merely selling software to actively assisting clients in constructing operational AI infrastructures.

Strategy Focuses on Multi-Model AI Implementation Enterprise organizations increasingly deploy multiple AI frameworks rather than relying exclusively on a single vendor. Numerous corporations now blend Microsoft platforms, third-party models, and open-source solutions tailored to distinct operational requirements. Consequently, AI implementation has become more expensive and complex to administer.

The Microsoft Frontier Company will guide customers through selecting, integrating, and transitioning between various AI frameworks. Additionally, the division will facilitate connections between these frameworks and each organization’s confidential internal information. Importantly, clients will retain ownership of all outputs and associated intellectual property within their own infrastructure.

Microsoft developed this methodology based on lessons learned from Copilot and other enterprise AI offerings. Initially, the company depended substantially on OpenAI’s technology when developing its AI assistant. However, emerging frameworks from Anthropic, Google, DeepSeek, and competing providers have driven demand for platform-agnostic solutions.

Shares Rise Amid Intensifying AI Consulting Competition Microsoft’s equity value increased following the disclosure, though shares have struggled year-to-date. The corporation has allocated substantial capital toward data center expansion and generative AI capabilities. Despite these investments, certain AI products have experienced modest uptake among business customers.

This new division positions Microsoft in direct competition with Amazon, Palantir, OpenAI, Anthropic, Accenture, and EY. Amazon recently announced a comparable $1 billion field engineering program targeting AI customers. Palantir has established expertise deploying engineering personnel to serve government agencies and corporate accounts.

Microsoft currently generates income from enterprise consulting and channel partner programs throughout its software portfolio. The company disclosed approximately $2.1 billion in enterprise and partner services revenue during the March quarter. As such, the Frontier division represents an expansion of proven business practices into the broader AI services marketplace.

Oliver Dale

Editor-in-Chief of Blockonomi and founder of Kooc Media, A UK-Based Online Media Company. Believer in Open-Source Software, Blockchain Technology & a Free and Fair Internet for all. His writing has been quoted by Nasdaq, Dow Jones, Investopedia, The New Yorker, Forbes, Techcrunch & More. Contact [email protected]

Multi-Asset Trading Terminals The integration of traditional equities into crypto venues represents a fundamental paradigm shift in global trading infrastructure. Rather than managing fragmented positions across siloed traditional brokerages and crypto exchanges, modern cross-asset market participants increasingly demand a singular, frictionless point of access. 

This structural convergence between crypto and traditional capital markets is punctuated by the exponential growth of equity derivatives on CEXs. Weekly trading volumes surged to a record high of $11.6 billion during the second week of June 2026, a milestone driven by Binance’s sweeping expansion into stock trading against the backdrop of SpaceX’s Nasdaq listing, the largest IPO in history.

By merging multi-asset capabilities into a single interface, crypto platforms solve critical operational pain points for cross-asset traders:

Unified Interface: Consolidates crypto assets and traditional equities under a single application, eliminating the operational friction of managing multiple apps and accounts. Frictionless Diversification: Enables instant capital reallocation between crypto assets and equities without navigating slow, costly traditional fiat rails and banking bottlenecks. 24/7 Collateral Utilization: Overcomes the rigid constraints of traditional market hours by maintaining equity exposure within a crypto-native framework. This unlocks around-the-clock portfolio visibility and allows assets to be utilized as active, cross-margined collateral. Emerging metrics indicate that benchmark indices, AI- and crypto-related stocks, and oil derivatives command the highest demand among crypto-native user cohorts, directly reflecting the risk-seeking profiles and tolerance for volatility prevalent among crypto-native market participants.

Execution Methodologies To deliver equity access to crypto users, crypto platforms generally deploy three distinct approaches:

Traditional Offchain Routing: Existing brokerage infrastructure integrated directly into the crypto user interface via APIs. This model connects users straight to incumbent underlying liquidity pools while operating entirely within established clearing frameworks. Tokenized Onchain Equities: Real-world assets (RWAs) issued as asset-backed tokens on public blockchains. This framework enables native composability with DeFi ecosystems and instant, 24/7 blockchain-based settlement. Synthetic Equity Derivatives: Perpetual futures contracts that track underlying stock prices via crypto-native order books and dynamic funding payments. This approach provides capital-efficient, high-leverage synthetic exposure while bypassing traditional clearinghouse infrastructure. Top-tier crypto venues are aggressively capturing market share from existing brokerages by deploying these models through varying operational frameworks:

Binance: Leads the multi-asset charge via a comprehensive three-pronged execution architecture. It provides a) direct equity exposure through an API-routed traditional stock and ETF brokerage service, b) tokenized onchain securities via its native bStocks initiative on the BNB Chain, and c) synthetic exposure through stock perpetual futures contracts to users in eligible jurisdictions. Coinbase: Follows Binance’s footsteps by offering a) stock and ETF trading for US residents, b) immediate plans to launch onchain tokenized equities, and c) stock perpetual futures contracts for non-US traders. Hyperliquid: Leverages permissionless onchain order books to offer high-leverage equity perpetual futures contracts.  The business case for integrating equities into a crypto platform rests on expanding monetization vectors and optimizing capital efficiency. Crypto platforms can monetize equity trading through a blend of traditional and crypto-native models:

Transaction Fee: Applying maker/taker fee schedules directly to equity trades executed within the interface. Spread-based Revenue: Monetizing the delta between the buy and sell prices. Asset Management Fee: Charging a management or minting/burning fee for tokenized equity vehicles wrapped directly onchain. The true economic unlock of this convergence lies in cross-collateralization. By allowing users to lock in equities as collateral, platforms enable them to margin trade across a wide array of futures markets, from crypto to equities to commodity derivatives. This dramatically increases capital efficiency, as an investor's equity portfolio no longer sits idle at the traditional market close but actively backs capital strategies and meets margin requirements 24/7.

Binance’s Role in Multi-Asset Trading As the world’s largest crypto exchange by trading volume, Binance occupies a unique position to spearhead the institutionalization of multi-asset trading, a trajectory underscored by the platform’s equity offerings, which rapidly scaled to reach a historic $1 billion in assets under management (AUM) for equities within weeks of launch. 

For Binance, adding access to over 7,000 equities and ETFs goes beyond a basic product line addition; it operates instead as a core capital retention strategy. Crypto markets are cyclical, characterized by intense periods of volatility followed by prolonged consolidation. By offering traditional equities, Binance establishes a structural market-cycle hedge. During crypto bear markets or macro consolidation phases, user capital can remain securely within the Binance ecosystem, rotating seamlessly into traditional equities or commodities rather than exiting the platform entirely.

Binance possesses structural advantages that few traditional or fintech competitors can replicate:

Global Retail User Base: Millions of verified, active users can be sold equity products alongside existing crypto assets with minimal incremental customer acquisition costs. Early adoption has been driven largely by younger demographics in emerging markets, with more than 80% of Binance's stock trading volume coming from these regions. Deep Liquidity Pools: Unrivaled market depth and elevated trading volumes across multiple markets on the platform provide an immediate, frictionless foundation for multi-asset volume generation and competitive spreads. Multi-Rail Asset Funding: A robust global architecture that enables seamless multi-channel inflows, allowing users to instantly fund their multi-asset accounts using local fiat payment rails, stablecoins, or major crypto assets. The ultimate trajectory for leading crypto platforms is the realization of a borderless, comprehensive financial super-app. In this future state, the historical boundaries dividing traditional equities, commodities, fiat currencies, and digital assets are abstracted away behind hyper-optimized, user-friendly interfaces.

With the integration of traditional equities into crypto platforms, users can deploy capital instantly, frictionlessly, and globally into a wide array of asset types, solidifying crypto platforms as the foundational financial terminals of the modern digital economy.

Disclaimer: The Block is an independent media outlet that delivers news, research, and data. As of November 2023, Foresight Ventures is a majority investor of The Block. Foresight Ventures invests in other companies in the crypto space. Crypto exchange Bitget is an anchor LP for Foresight Ventures. The Block continues to operate independently to deliver objective, impactful, and timely information about the crypto industry. Here are our current financial disclosures.

© 2026 The Block. All Rights Reserved. This article is provided for informational purposes only. It is not offered or intended to be used as legal, tax, investment, financial, or other advice.

HP Inc. has joined OpenAI’s Frontier initiative as one of the platform’s inaugural enterprise adopters, a move that positions the hardware giant squarely in the middle of the rapidly accelerating corporate AI race. The partnership focuses on deploying AI agents across HP’s internal operations and customer-facing tools.

What the Frontier platform actually does OpenAI officially launched the Frontier platform on February 5, 2026. It’s an enterprise toolkit that lets companies build, deploy, and manage AI agents that share context, integrations, and permissions across business systems. The shift here is from individual AI productivity, one person using a chatbot to draft emails, to organizational AI deployment, where agents handle interconnected workflows at scale.

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HP is describing these agents as “AI coworkers.” Other early adopters of the Frontier platform include Intuit, Oracle, State Farm, Thermo Fisher Scientific, and Uber. Dozens of additional organizations, including BBVA, Cisco, and T-Mobile, have also explored Frontier’s capabilities through pilot programs.

Why this matters beyond the tech sector OpenAI launched a Partner Network in the middle of 2026, expanding its reach into the corporate world well beyond individual API access. The Frontier platform represents the next evolution, giving organizations tools to move past the “let’s experiment with AI” phase and into full operational deployment.

The absence of any blockchain or token component in the Frontier platform is also telling. OpenAI is building its enterprise AI stack on traditional cloud infrastructure, not decentralized compute. No references to cryptocurrency, tokens, or blockchain have been reported in relation to Frontier.

Disclosure: This article was edited by Editorial Team. For more information on how we create and review content, see our Editorial Policy.

DeFi Maturation: 2020 vs. 2025

Venus Protocol Joins Forces with Fluid to Launch Venus Flux, the First Unified Liquidity Layer on BNB Chain

In brief Frontier AI models are increasingly being used to identify software vulnerabilities. Claude Mythos, Claude Opus, GPT-5.5, and other systems have been deployed in vulnerability research across browsers, operating systems, and open-source software. The technology is beginning to influence crypto and DeFi security, where Claude Opus 4.8 was cited in research that uncovered a critical Zcash vulnerability. The latest generation of frontier AI models are no longer just chatting with users, generating images, or writing code. Researchers are increasingly using systems such as Anthropic’s Claude Mythos and Claude Opus 4.8 and OpenAI’s GPT-5.5 to identify software vulnerabilities, raising concerns about what happens when those capabilities become widely available.

Crypto investors got a wake-up call about the rising threat from powerful AI this week when Zcash developers disclosed that Claude Opus 4.8 helped discover a critical vulnerability that could've enabled an attacker to mint unlimited ZEC. Due to the network's design, there's no current way to know for sure whether counterfeit ZEC was, in fact, minted—and that uncertainty led to the price of ZEC crashing late this week.

Experts warn that many more vulnerabilities could be found in the coming weeks and months as AI software gets more capable—and those tools become more accessible. Here's a look at the growing threat, and how it's already impacted the crypto world.

Early AI models were professionally used as coding assistants, helping developers write, explain, and debug software. As the technology improved, researchers began using the same systems for code review, software auditing, and vulnerability research.

The transition from coding assistant to security tool coincided with a broader shift in how AI was being used inside software development. After the launch of Claude Code in 2025, Anthropic reported a sharp increase in AI-generated code across its engineering teams, reflecting a move from models that suggested code to systems capable of writing and running it.

Security professionals say the implications extend beyond helping developers write code.

"AI is far better at reviewing code than most people and finding potential vulnerabilities in it," Danny Jenkins, CEO and co-founder of ThreatLocker, told Decrypt. Jenkins said current AI systems are already accelerating vulnerability discovery, while newer models such as Mythos could significantly expand those capabilities, calling it an imminent “big problem.”

“It will be only a matter of time until someone bad gets access to it,” he said.

According to Jenkins, AI is also lowering the barriers to entry for vulnerability research, allowing more people to analyze code, identify weaknesses, and develop exploits. As access to increasingly capable systems expands, he expects the pace of vulnerability discovery to increase.

"Pre-AI, cybersecurity threats and exploits were increasing every year,” he said. “Post-AI, it's become even faster, and I think it's become faster for two reasons. One is that you can now use AI to help find vulnerabilities and exploits, and the number of people who have the ability to do this has massively grown. You don't have to be a script kiddie now.”

As AI systems became more capable, companies began applying them to cybersecurity. On Tuesday, Anthropic expanded access to Project Glasswing, giving 150 companies and institutions access to Claude Mythos to help identify and remediate software vulnerabilities before the model is released more broadly.

In April, Mozilla later disclosed that Anthropic's models helped identify hundreds of vulnerabilities that it fixed in the Firefox web browser, while researchers at Calif used Mythos Preview during work that produced one of the first public exploits targeting Apple's M5 chips.

Stanislav Fort, a former researcher at Google DeepMind and Anthropic and now founder and chief scientist of security firm Aisle, said concerns about AI-powered vulnerability discovery are valid, but often misunderstood.

“The naive response is to try to gatekeep access to powerful models. I think this is essentially security by obscurity, and security by obscurity is one of the worst ideas in the field,” Fort told Decrypt. “The capability for zero-day discovery is already widely distributed across models that no one can restrict. Trying to bottle it up at the frontier doesn't eliminate the risk; it just delays it while also slowing down the defenders who need these tools most.”

Fort said the greater risk is that defenders, particularly open-source maintainers, may lack access to the same advanced AI tools available to attackers.

“That imbalance is the real danger,” he said. “The answer isn't restriction; it's democratization of the defensive stack.”

Anthropic is not alone in pushing AI models aimed at cybersecurity. In May, Microsoft introduced MDASH, an agentic vulnerability discovery system that the company said helped identify previously unknown Windows vulnerabilities.

The risk to cryptoCrypto and DeFi are starting to feel the impact of AI-powered bug hunting. Blockchain projects have always been attractive targets because there is a lot of money at stake and much of the code is publicly available. Jenkins said as AI gets better at finding software flaws, open-source crypto projects could become easier targets for both security researchers looking for bugs and attackers looking to exploit them.

In one of the clearest examples of how advanced AI models can help researchers uncover vulnerabilities that had survived years of human review, independent security researcher Taylor Hornby disclosed the critical vulnerability in Zcash's Orchard privacy pool that he discovered with the assistance of Claude Opus 4.8.

The flaw could have allowed an attacker to create unlimited counterfeit ZEC, and had gone undetected for years before being patched. Whether the exploit was actually used currently remains unknown.

"The vulnerability was present from Orchard's activation in May 2022 until the emergency fix was deployed on June 1, 2026," Shielded Labs, the organization behind Zcash development, wrote in a disclosure post. "Due to the privacy properties of Orchard and the nature of the bug, there is no definitive way to determine, using only cryptography, whether such exploitation occurred."

The attack comes as DeFi protocols are already facing one of their worst years for exploits. More than $840 million was stolen from DeFi projects in the first five months of 2026, including more than $600 million in April alone across attacks on projects including KelpDAO, and Drift Protocol.

The rise of so-called 'vibe hacking,’ where attackers use AI coding agents to automate reconnaissance, credential theft, malware development, and other tasks, has raised concerns that AI is lowering the barriers to carrying out sophisticated cyberattacks

According to Natalie Newson, senior blockchain investigator at Web3 security platform CertiK, while April was unusually severe for crypto exploits, the broader trend remains more stable and below the peak number of incidents seen in past years.

“April 2026 was a bad month for crypto exploits; there were only three days without an exploit in which at least $10,000 was taken,” she said. “However, when we take a look at the wider picture, the number of incidents (excluding phishing) has arguably been fairly consistent and still lower than a peak in 2023.”

While AI is making DeFi exploits easier to carry out, according to Blockaid CTO Raz Niv, the bigger risk is not AI replacing hackers but amplifying them, allowing attackers to focus on more sophisticated techniques while AI handles routine tasks.

“The good news is defenders can use the same tools," he said. "AI-assisted monitoring and simulation is becoming essential for security teams trying to keep pace."

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In brief Security researcher Taylor Hornby used Claude Opus 4.8 to discover a four-year-old flaw in Zcash's Orchard privacy pool that could have enabled unlimited counterfeit ZEC creation. Cybersecurity researchers say frontier AI models are increasingly capable of finding cryptographic and logic flaws that previously required deep specialist expertise. Experts warn that capabilities approaching today's most advanced vulnerability-discovery systems could become widely available within months. A security researcher using Anthropic's Claude Opus 4.8 uncovered a critical flaw in Zcash's Orchard privacy pool in a matter of days, exposing a vulnerability that had survived four years of review by leading zero-knowledge cryptographers.

The disclosure sent ZEC tumbling roughly 38% on Thursday and raised a broader concern for the crypto industry around frontier AI models becoming increasingly proficient in finding vulnerabilities than most humans.

"The significance isn't really that AI can find bugs," Ben Goertzel, founder and CEO of SingularityNET, told Decrypt. "It's that the kind of bug it can now find has changed."

Rather than simply flagging obvious coding mistakes, frontier models are increasingly capable of reasoning about whether software behaves the way its designers intended, he said.

In May, Taylor Hornby, a security researcher hired by Shielded Labs, discovered a critical flaw in Zcash's Orchard circuit with assistance from Anthropic's Claude Opus 4.8. Hidden in two lines of code, the bug stemmed from a check that appeared to validate transaction inputs but wasn't actually enforcing the intended rules, potentially allowing an attacker to create counterfeit ZEC inside the shielded pool without detection. Hornby built a working exploit to verify the vulnerability before reporting it to developers. An emergency fix was deployed on June 1.

Adding to the panic that hit Zcash and the broader crypto market on Thursday and Friday is the fact that the flaw had been left undiscovered for over four years.

For Goertzel, the discovery is significant not only because AI found a vulnerability, but also because it points to a new model for security research.

"I think it's an early marker of a shift that's going to be hard to overstate," he said. "The model of security research as a handful of revered human specialists doing slow, artisanal, deeply-expert audits doesn't go away, but it stops being the whole game."

Goertzel said the Orchard flaw belongs to a class of subtle logic bugs that frontier AI models are increasingly capable of finding, including smart-contract errors, access-control failures, and situations where software behaves differently than its designers intended. As those capabilities improve, he added that security research is shifting toward a model in which human specialists oversee continuous AI-driven review that can analyze codebases far more extensively than traditional audits.

The Zcash response itself may offer a preview of that future, Goertzel said.

"Shielded Labs bringing on a researcher specifically to hunt protocol-level flaws with a frontier model before a malicious actor could is, I suspect, the template, not the exception," Goertzel said. "Proactive, AI-augmented, adversarial-by-design review becomes table stakes, and the protocols that don't adopt it will increasingly be the ones learning about their vulnerabilities from the attacker rather than from a friendly."

According to Sean Ren, CEO of Sahara AI and a computer science professor at the University of Southern California, advances in AI are also reshaping the balance between attackers and defenders as frontier models can rapidly test attack strategies, learn from the results, and uncover weaknesses.

"In order to build up better defense, we have to use these frontier AI models as the potential attackers to stress test these systems," Ren told Decrypt.

Ren said blockchain networks are especially exposed because their open-source code can be analyzed directly by frontier AI models, which can rapidly test attack strategies and identify vulnerabilities faster than traditional security reviews.

"If you think about frontier model labs like OpenAI, Anthropic, and Google DeepMind, they have earlier access to the strongest unpublished models and can conduct a lot of experiments on public network systems like blockchains, so they do have the power at hand,” he said. “If someone with malicious intent had access to those capabilities, they could conduct attacks and create vulnerabilities.”

That window may close faster than many expect, and according to Danny Jenkins, CEO and co-founder of cybersecurity firm ThreatLocker, AI-assisted vulnerability discovery is improving faster than many organizations can secure the software they already rely on.

"We have this huge gap that's going to take years and years to get through," Jenkins told Decrypt. "All of this software is going to have all of these vulnerabilities, we're not going to have fixes or updates for it for a long time, and people are going to be able to find those vulnerabilities very quickly."

Jenkins said AI is not fundamentally changing vulnerability research so much as dramatically accelerating it. Tasks that once required security researchers to review code and reverse engineer software manually can now be performed in seconds by modern models.

"Pre-AI, cybersecurity threats and exploits were increasing every year,” he said. “Post-AI, it's become even faster, and I think it's become faster for two reasons. One is that you can now use AI to help find vulnerabilities and exploits, and the number of people who have the ability to do this has massively grown. You don't have to be a script kiddie now.”

Despite those risks, Goertzel argued that crypto may also be better positioned than other industries to adapt because its code is open, and its communities are highly security-focused.

“Crypto is standing closest to the door, but it's also the part of the room that can see the door coming,” he said.

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Dario Amodei Demands Power to Block Unsafe AI a Day After Claude Fable 5 Launch

The Solana Foundation just rolled out the velvet rope for institutional crypto trading. Its new program, Frontier Traders, is an invite-only community designed for hedge funds, proprietary trading firms, and market makers who want front-row access to Solana’s rapidly expanding tokenized equity market, starting with SpaceX.

The barrier to entry is, to put it mildly, steep. The first VIP tier requires between $500 million and $2 billion in trailing 30-day decentralized exchange volume, plus $16 million to $66 million in gross time-weighted open interest.

What Frontier Traders actually offers The program is structured around tiered access, with each level unlocking enhanced infrastructure, data feeds, and liquidity pathways tailored specifically for professional traders.

The centerpiece campaign right now is SpaceX tokenized equity, trading under the ticker $SPCX. The token is designed to provide continuous onchain trading exposure to SpaceX, with shares set to become redeemable when SpaceX eventually makes its public debut on Nasdaq.

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Frontier Traders participants can earn rewards for engaging with $SPCX trading activities, creating an incentive loop that simultaneously drives volume and deepens liquidity for the tokenized product.

The timing is deliberate. SpaceX tokenized shares are planned to trade on Solana on the same day that SpaceX lists on Nasdaq, offering 24/7 trading opportunities that traditional markets simply cannot match.

Solana’s quiet dominance in tokenized equities Solana accounts for over 95% of DEX volume for tokenized equities over the last 30 days.

The groundwork for this dominance was laid through collaborations with firms like PreStocks and Backpack Securities, which have been facilitating pre-IPO onchain exposure for early-stage companies. These platforms turned Solana into the de facto home for tokenized equity trading, and the Frontier Traders program is essentially the Foundation’s attempt to formalize and accelerate that position.

What this means for investors The Frontier Traders program is explicitly not designed for retail investors. The $500 million volume floor makes that abundantly clear.

The SpaceX angle is particularly interesting because it tests a core hypothesis about tokenized equities: can onchain markets compete with, or even complement, traditional IPO processes? If $SPCX generates meaningful volume and price discovery before SpaceX’s Nasdaq listing, it becomes a proof of concept that other high-profile pre-IPO companies will be watching closely.

There are risks worth flagging. Tokenized equities exist in a regulatory gray zone that varies by jurisdiction. The redemption mechanism for $SPCX, tied to SpaceX’s eventual public listing, introduces counterparty risk and depends on an IPO timeline that Elon Musk has historically been in no rush to set. Investors should also consider that the 95% market share figure, while impressive, reflects a still-nascent market where absolute volumes may be modest compared to traditional equity trading.

BlackRock’s tokenized money market fund on Ethereum, for example, has attracted billions in assets. Solana’s lead in tokenized equities is real, but maintaining it will require continued innovation and regulatory clarity that neither Solana nor any other blockchain can unilaterally provide.

Disclosure: This article was edited by Editorial Team. For more information on how we create and review content, see our Editorial Policy.

Key Highlights Table of Contents

Key HighlightsCompany establishes subscription rights frameworkRights program features equity and warrant componentsFrontier investment anchors corporate growth blueprintGet 3 Free Stock Ebooks EOSE continues upward momentum following Frontier Power USA financing announcement.

Company establishes subscription rights offering schedule targeting July 2026.

EOSE shares climb as capital raising framework addresses Frontier JV obligations.

Subscription rights structure draws investor attention to Eos Energy’s joint venture plans.

Eos Energy stock maintains upward trajectory following financing strategy disclosure.

Eos Energy Enterprises (EOSE) saw its shares climb after revealing subscription rights offering details designed to finance its Frontier Power USA joint venture commitment. EOSE finished the session at $6.20, representing a 2.14% increase, before advancing further to $6.35 during pre-market hours. The upward movement builds on recent positive momentum as shares maintained strength near intraday peaks.

Eos Energy Enterprises, Inc., EOSE

Company establishes subscription rights framework Eos Energy Enterprises revealed plans to issue subscription rights to qualifying common stockholders and specific warrant holders. The energy storage manufacturer designated the record date as 5:00 p.m. New York time on July 1, 2026. Additionally, the company confirmed July 2, 2026, as the date when rights will be distributed.

The subscription rights mechanism serves to generate capital for Eos’ previously disclosed investment in Frontier Power USA. This joint venture represents a key component of the company’s comprehensive energy storage market expansion initiative. As such, the capital raise directly supports its long-duration battery storage development objectives.

Qualifying participants comprise common stock shareholders and holders of warrants from specific issuance dates. These warrant issuance dates span April 14, 2023, May 17, 2023, December 19, 2023, and November 21, 2025. The company noted that particular warrant and note holders must receive preliminary notification ahead of the rights distribution.

Rights program features equity and warrant components According to the proposed structure, Eos intends to distribute rights enabling the purchase of investment units. These units will comprise shares of common stock bundled with warrants conferring rights to acquire additional common stock. Complete specifications will be disclosed when the offering commences.

Individual rights will grant qualifying holders the ability to acquire units through a basic subscription entitlement. Eos anticipates the subscription price will incorporate a reduction of approximately 10% to 20%. This discount will be measured against a volume-weighted average market price calculated before the record date.

The calculation window will span 15 to 30 trading sessions preceding the record date. The warrants included within each unit will constitute roughly 25% to 50% of the total offering value. Eos will determine this valuation utilizing a Black-Scholes pricing model.

Frontier investment anchors corporate growth blueprint The rights program will feature an over-subscription option for qualifying participants who completely exercise their initial subscription entitlements. These participants may acquire supplementary units remaining after the expiration of the subscription period. The company indicated certain limitations will govern this over-subscription feature.

The offering will proceed under the company’s active shelf registration statement filed on Form S-3. Eos intends to submit a prospectus supplement prior to launching the offering. This document will incorporate the base prospectus along with additional operational specifications.

Eos develops and produces zinc-based long-duration energy storage solutions domestically within the United States. The company’s technology addresses grid-scale storage requirements as electricity consumption and renewable energy adoption accelerate. The Frontier Power USA financing initiative represents an additional milestone in this expansion trajectory.

Oliver Dale

Editor-in-Chief of Blockonomi and founder of Kooc Media, A UK-Based Online Media Company. Believer in Open-Source Software, Blockchain Technology & a Free and Fair Internet for all. His writing has been quoted by Nasdaq, Dow Jones, Investopedia, The New Yorker, Forbes, Techcrunch & More. Contact [email protected]

Key Takeaways Table of Contents

Key TakeawaysRocket Lab: Comprehensive Space Solutions ProviderPlanet Labs: Commercial Earth Intelligence LeaderAST SpaceMobile: Revolutionary Satellite Connectivity PlayThe 2026 Investment LandscapeGet 3 Free Stock Ebooks Rocket Lab demonstrates robust expansion through its launch operations, satellite manufacturing, and impressive analyst coverage with 10 Buy and 4 Hold recommendations Planet Labs maintains the largest commercial Earth-imaging satellite constellation, reporting increased revenues and a strengthening contract pipeline AST SpaceMobile pursues revolutionary satellite-to-smartphone technology, earning 8 Buy ratings despite its higher risk profile Each company shows momentum through expanding order books and diversified customer bases spanning government and private sectors Anticipated SpaceX public offering is driving heightened investor enthusiasm throughout the space industry The commercial space sector is entering an accelerated expansion period in 2026, fueled by sustained government investment and surging demand for satellite-based services. Three publicly traded companies are capturing significant investor attention as they pursue distinct opportunities in orbital launches, Earth observation, and satellite communications.

Rocket Lab: Comprehensive Space Solutions Provider Rocket Lab operates one of the most comprehensive portfolios among accessible space industry investments.

Rocket Lab USA, Inc., RKLB

The enterprise delivers orbital launch capabilities, manufactures complete satellite systems, and provides aerospace components to military, civil, and commercial clients.

Latest financial results demonstrated impressive revenue expansion alongside a strengthening pipeline of committed contracts. Market observers are particularly focused on the company’s Neutron vehicle development, a medium-lift rocket designed to compete for larger payload missions traditionally dominated by SpaceX.

Analyst sentiment remains overwhelmingly favorable, with Rocket Lab receiving 10 Buy ratings, 4 Hold recommendations, and zero Sell ratings.

Industry experts view Rocket Lab as exceptionally well-positioned within both launch operations and satellite technology as the decade progresses.

Planet Labs: Commercial Earth Intelligence Leader Planet Labs pursues a distinctly different market opportunity. Rather than launching payloads for others, the company operates the planet’s most extensive commercial Earth-imaging satellite network.

Planet Labs PBC, PL

The intelligence and visual data captured by this constellation serves diverse customers including national security organizations, defense contractors, agricultural enterprises, risk assessment firms, and corporate clients worldwide.

Recent quarterly results highlighted accelerating revenue generation and an expanding backlog of signed agreements. The company maintains a solid balance sheet, providing financial flexibility for ongoing technology investments.

Wall Street assigns the stock 6 Buy ratings, 4 Hold positions, and zero Sell recommendations.

While profitability remains ahead, investors increasingly recognize the company as a premier geospatial intelligence provider rather than merely a satellite operator.

As appetite for continuous Earth monitoring intensifies—particularly with artificial intelligence integration—Planet Labs stands positioned as a primary beneficiary of this technological convergence.

AST SpaceMobile: Revolutionary Satellite Connectivity Play AST SpaceMobile represents the highest-risk, highest-potential opportunity among these three companies.

AST SpaceMobile, Inc., ASTS

The company’s ambitious objective involves enabling ordinary mobile phones to communicate directly with orbital satellites without modifications or specialized hardware. Successfully executing this vision could provide connectivity to billions of users worldwide and eliminate coverage gaps across underpopulated regions.

AST has completed successful proof-of-concept demonstrations of satellite-to-mobile connections and secured strategic alliances with leading telecommunications carriers.

Financial analysts support the investment thesis with 8 Buy recommendations, 2 Hold ratings, and zero Sell positions.

Significant execution challenges remain. AST must deploy additional satellites, expand network infrastructure, and demonstrate sustainable revenue generation. Technical setbacks or deployment delays could trigger substantial price volatility.

For risk-tolerant investors, AST represents one of the space sector’s most intriguing high-conviction speculative opportunities.

The 2026 Investment Landscape Rocket Lab, Planet Labs, and AST SpaceMobile each provide distinct exposure to different segments of the emerging space economy.

Among these three, Rocket Lab currently enjoys the strongest analyst support and operates the most balanced business model.

The anticipated SpaceX public offering has generated renewed momentum for space-related equities broadly, potentially lifting interest across all three companies as mainstream investor participation in the sector expands.

A crypto AI agent does not have to fail outright for it to impact your trades. It can stay online, keep the same interface, and still behave very differently after a model switch. The U.S. government’s June 2026 order that forced Anthropic to shut down Fable 5 and Mythos 5 showed how abruptly model access can change. And government action is only one of several possible triggers.

This guide explains model-access risk, why AI geopolitics matters for crypto, and what to check before you trust an agent with funds.

KEY TAKEAWAYS
➤ Crypto AI agents may execute on-chain, but rely on off-chain infrastructure they do not control.
➤ Model-access risk is the chance an AI product loses, changes, or downgrades the model it relies on.
➤ Anthropic disabling Fable 5 and Mythos 5 showed how fast frontier model access can change.
➤ For a DeFAI tool, a model cutoff can become a money problem, not just a feature problem.
➤ Decentralization should be checked across the full stack, beyond the token or smart contract.

Table of Contents

When your agent switches models, the risk changes tooWhat is the off-chain brain problem?What is model-access risk?Why the Anthropic case matters for cryptoHow export controls reach the model layerFive ways a crypto AI agent can get cut offWhy DeFAI raises the stakesSmart contract risk vs. model-access riskDoes decentralized AI solve the problem?What you should check before you trust a crypto AI agentWhat crypto projects should discloseA new gatekeeper?When your agent switches models, the risk changes tooThe problem is not always that the agent goes offline. A well-built crypto AI agent may stay live after its main model gets blocked, shelved, or replaced by routing requests to another model.

That can keep the service running, but it can also change how the agent behaves. A replacement model may assess risk differently, miss context that the original model would catch, work with fewer tools, or follow a different safety setup. From the outside, the product may look unchanged even though the decision layer behind it is not.

On June 12, 2026, that distinction stopped being theoretical when Anthropic said the United States government issued an export-control directive to suspend all access to two of its frontier models, Fable 5 and Mythos 5, for any foreign national inside or outside the country. Anthropic said the net effect was that it had to disable both models for every customer worldwide.

While the Anthropic fiasco involved just one company and its two models, the broader lesson is clear: if access to a leading model can change in an afternoon, then any crypto tool that depends on a single controlled model has a few questions to answer.

What is the off-chain brain problem?The off-chain brain problem is the gap between a crypto agent’s on-chain actions and its off-chain intelligence. Put simply, the hands act on a blockchain, while the brain runs on infrastructure that may be centralized and restricted.

Crypto AI agents use blockchains for the parts that benefit from public verification. That includes holding funds, calling smart contracts, settling trades, enforcing permissions, and recording what happened. Those functions stay on-chain because users need a public record they can check directly.

The decision-making layer is different. The model that reads your prompt, processes data, and chooses the next action usually runs off-chain. Large language models require heavy computing, so they cannot run inside a blockchain transaction. Instead, they operate on servers, and only the final decision reaches the chain.

A typical stack looks like this, from your command down to the on-chain action.

LayerWhat happensWhere it runsUser promptYou type a command or set a strategyYour deviceApp and front endThe interface packages your requestProject serversAI modelA hosted model interprets and reasonsProvider infrastructureAPI and cloudRequests route through keys and cloud regionsProvider and cloudData and RPCPrice feeds and blockchain node access feed the modelExternal providersAgent decisionThe model picks an actionProvider infrastructureWallet or contract callThe action is prepared on-chainBlockchainApproval or executionYou sign, or the agent executes automaticallyBlockchainRead the table top to bottom and the issue becomes clear. Much of the system depends on off-chain layers. The blockchain can keep running while the AI layer above it fails.

Your wallet still works. The rails still work. But the agent that decides what to do with them may be gone or changed.

What is model-access risk?Model-access risk is the chance that an AI product loses, changes, or downgrades access to the model it depends on. The cause can be a government rule, a provider policy update, a cloud restriction, a price change, an outage, a sanction, a region block, or a safety update.

For an ordinary chatbot, model-access risk is mostly an annoyance. A feature disappears, a response gets more cautious, or the app falls back to a weaker model for a while.

For a crypto agent, however, the same disruption can land on something financial. A model change can affect whether a trade executes, how a wallet action is framed, whether a yield strategy continues, or how a security check reads a contract.

Model-access risk is not the same as model error. A model that hallucinates is making a mistake. A model that gets cut off is still capable, but you can no longer reach it. Both can hurt a crypto agent, and the second one is easy to overlook.

That is the key point. The AI layer is a dependency, and any dependency that can affect your funds needs to be checked before you trust it.

Why the Anthropic case matters for cryptoThe Fable 5 and Mythos 5 episode comes as an alarm call because it shows how quickly frontier model access can become subject to government limits, and it shows the shape of the chain that leads to a cutoff.

Anthropic said it received the directive at 5:21 p.m. ET and that the order covered any foreign national, including its own non-citizen employees, per its statement. Because compliance for that group was not practical at the user level, the company said it disabled both models for everyone. Access to its other models was not affected.

The stated concern involved a possible jailbreak. Anthropic said its understanding was that the government believed someone had found a way to bypass a safeguard, and that the demonstrated technique was used to identify a small number of previously known, minor software vulnerabilities.

Anthropic said it disagreed that a narrow potential jailbreak justified recalling a model used by hundreds of millions of people.

The chain of events is the part worth keeping.

TriggerWhat happened1. Government concernA national security worry tied to a jailbreak method2. Export-control directiveA legal order restricting access by foreign nationals3. Access problemCompliance at the user level was not workable4. Provider responseThe company disabled both models globally5. DisruptionEvery customer lost access to those two models Do not over-read this case. It involved one provider, two specific models, and a contested national security claim. It does not mean every AI model faces the same risk. It does prove that access to a frontier model can change fast when a government treats the model as a security issue.

Now apply that to crypto.

If a model can disappear or change in a day, what happens to a DeFAI app, trading agent, or wallet assistant that depends on it? Does it stop, or does it switch to something else? And if it switches, is the new model just as capable and safe?

How export controls reach the model layerThe Anthropic directive did not appear in a vacuum. Governments have spent years building tools to control advanced computing, and those tools increasingly point at AI itself.

In January 2025, the United States published the Framework for Artificial Intelligence Diffusion, often called the AI Diffusion Rule. It described controls on advanced computing integrated circuits and, notably, on model weights for the most capable AI systems. The framework treated both chips and trained models as items that could be subject to export rules.

That specific rule did not stay in place. In May 2025, the Bureau of Industry and Security (BIS) announced it was rescinding the AI Diffusion Rule and would issue replacement guidance. At the same time, BIS said it would strengthen export controls on advanced AI chips and warned that knowledge of items being used to train AI models could trigger license requirements.

The exact rule changed, but the direction did not. Chips, compute, and model access remain inside the export-control conversation. For crypto builders and users, the relevant point is that the AI layer now sits in a policy area that can move quickly and without much warning.

This is where sovereign AI and national AI strategy come in. Countries are increasingly treating compute and frontier models as strategic resources. That backdrop is why a model can be restricted at all.

The details of that competition are a separate topic. What matters here is the effect. A crypto agent may depend on rules that have nothing to do with crypto, and those rules can change how its AI model behaves or whether you can use it at all.

Five ways a crypto AI agent can get cut offA crypto agent can lose its intelligence layer in several ways. Some involve government action, others do not. Lumping them together hides the real risk. Each failure point has its own trigger and impact, so it is worth separating them.

Notice that only the first row is about governments. The other four are ordinary infrastructure and business risks that exist on a normal Tuesday. A billing problem, an outage, a sanctions-compliance step, or a quiet policy update can each change how an agent behaves.

Why DeFAI raises the stakesA broken chatbot wastes a few minutes. A broken financial agent can affect your balance. That difference is the core reason model-access risk deserves attention in crypto.

DeFAI, short for the combination of decentralized finance and AI, uses agents to gather information, interpret it, decide, and execute. When those four steps run with real funds, the quality and availability of the model stop being cosmetic. Consider how a model disruption could land in practice.

An AI trading assistant loses access to its primary model in the middle of an open strategy. An agent wallet quietly falls back to a weaker model that reasons less reliably about risk. A yield bot cannot evaluate protocol risk after a data or API failure. A security assistant loses advanced code-analysis capability right when it is needed. A portfolio agent misreads market data after a forced provider switch. A liquidation-risk tool fails during a volatile window, exactly when timing matters. A DeFAI app stays online and connected to the chain, but its AI decision layer is gone. With normal AI apps, model-access risk can be a productivity problem. With DeFAI, it can become a money problem. The on-chain side may look perfectly healthy while the decision layer that protects your funds is degraded or offline.

Research supports the idea that model capability and tool access matter.

In one experiment, U.S. venture capital firm a16z Crypto tested whether AI agents could reproduce DeFi exploits. Agents succeeded about 10% of the time in a basic setup. When given structured knowledge from real attacks, success rose to 70%.

Even then, the hardest exploits still required economic judgment that the agents struggled with.

This is not a reason to panic, but it is a reason to look a bit closer at what sits behind your agent and how much you can rely on it.

Smart contract risk vs. model-access riskCrypto users already think in terms of risk layers. You probably check smart contract risk, oracle risk, and custody risk without being told. Model-access risk is a newer layer that sits above all of them, and it does not replace the others.

Risk typeWhere it affectsExampleSmart contract riskOn-chain codeBug, exploit, or bad permission in a contractOracle riskData layerBad or manipulated price feedCustody riskWallet and key layerCompromised key or malicious signerModel-access riskAI layerHosted model restricted or downgradedCloud and API riskInfrastructure layerOutage, account block, or rate limitGeopolitical riskJurisdiction layerExport controls, sanctions, or foreign-access rulesThe point is not that AI makes crypto unsafe. The point is that due diligence now needs one more question: who controls the intelligence/decision layer, and how exposed is it? An audited contract and a hardware wallet do nothing for you if the agent’s brain goes dark at the wrong moment.

Does decentralized AI solve the problem?Decentralized AI can reduce single-provider dependence, but it does not erase every chokepoint. It is a meaningful improvement in some places and a trade-off in others, so it deserves a balanced read rather than a slogan.

Several approaches push against centralization, each with limits.

Open-weight models can reduce dependence on a closed API, because the weights can be downloaded and run elsewhere. They may still trail the strongest closed models on hard tasks. Local models can cut provider risk by running on hardware you or the project control. They often offer weaker performance and demand real operational effort. Decentralized physical infrastructure networks (DePIN) for compute can spread reliance across many providers instead of one cloud. Coordination, reliability, and verification add complexity. Decentralized inference can improve resilience by routing work across a network. It can introduce latency, quality variance, verification challenges, and governance questions. Even fully decentralized AI still needs compute, data, model quality, security, and economic incentives to hold up. Spreading out the model layer changes the shape of the risk. It does not remove the need to check it.

So the honest answer is partial. Decentralized AI can make the brain harder to switch off in one move. It does not guarantee that the brain is as resilient, as capable, or as available as the blockchain underneath it.

What you should check before you trust a crypto AI agentBefore you let an agent touch funds, treat the AI layer like any other dependency and ask direct questions. The list below works as a practical due diligence framework. You will not always get every answer, and a project’s willingness to answer is itself a signal.

Which AI model powers the agent, and is that disclosed? Is the model hosted, open-weight, or run locally? Who controls the API key, the project, or a third party? Can the project switch models quickly if one becomes unavailable? Does the fallback model have weaker capabilities, and does the app tell you when it switches? Does the agent actually touch funds, or only provide analysis? Are there spending caps per transaction and per period? Do you approve each transaction, or can the agent execute on its own? Can the agent call any contract, or only an approved allowlist? Does the system log its actions and model outputs for later review? What is the documented behavior if the model fails midway? Does the project disclose its model, cloud, and data dependencies? Does the project explain region-specific limits or restrictions? Is there a manual mode you can fall back to if the AI layer fails? Are the risk controls enforced on-chain, off-chain, or both? The strongest guardrails are the ones written into code rather than a policy page.

Chainlink’s guide on onchain AI agent safety makes a similar point, noting that agents can manage portfolios, execute trades, and interact with smart contracts, and that direct access to digital assets means they need strict guardrails such as spending caps and allowlists to avoid serious loss. On-chain limits matter precisely because they keep working even if the off-chain brain misbehaves.

What crypto projects should discloseBuilders carry the other half of this responsibility. A project that is honest about its dependencies is easier to trust than one that markets an agent as decentralized while hiding a single point of failure in the AI layer. Clear disclosure also strengthens a project’s credibility with users who are learning to ask these questions.

At a minimum, a project running an agent that touches funds should disclose the following.

The model provider, or at least the model class in use. Whether the setup is hosted or based on open-weight models. The cloud dependencies behind the service. A fallback model plan if the primary becomes unavailable. The risk of API rate limits affecting service. Any region restrictions on access. The rules for human approval of actions. The transaction limits enforced by the system. The audit trail and logging policy. The external data sources the agent relies on. What happens during model downtime. Whether the agent can act without user approval, and under what conditions. Disclosure does not remove model-access risk, but it does let you price it. A reader who knows the dependencies can decide how much trust, and how much money, a given agent has earned.

A new gatekeeper?Crypto users already understand why gatekeepers matter. Much of crypto’s history has been shaped by efforts to reduce reliance on centralized exchanges, custodians, and other intermediaries. At its core is a simple question: who has the power to stand between you and your funds?

The gatekeeper may not be where you expect it. In crypto AI systems, it can be the model provider behind your agent, or a rule that reaches that provider. The Fable 5 and Mythos 5 shutdown showed how quickly that control can change.

That said, it does not make every crypto AI tool unsafe. Rather, it changes what you need to check. Your agent may run on-chain, but its decision layer may not. Before you trust it with money, ask whether the AI layer is as resilient as the blockchain beneath it.

Frequently asked questions Yes, and it has happened. In June 2026 the United States issued an export-control directive that led Anthropic to disable two frontier models globally for all users. If your crypto agent depends on a single controlled model, a similar action could affect the AI layer behind it, even though the blockchain layer would keep running.

It describes the gap between an agent’s on-chain actions and its off-chain intelligence. The wallet, contract, and token live on a public blockchain, but the model that makes decisions usually runs on centralized infrastructure. That means the agent can look decentralized while its thinking layer is controlled by one company or restrictable by a government.

It can be. A chatbot losing model access is mostly an inconvenience, while a DeFAI tool losing access can affect trades, yield strategies, security checks, or risk monitoring. Because DeFAI agents can move real funds, a model disruption can shift from a productivity problem to a money problem.

It reduces dependence on a single closed provider, but it does not remove every chokepoint. Open-weight and local models can lower provider risk, yet they may offer weaker performance and still rely on compute, data, and infrastructure. Decentralized inference can improve resilience while adding latency, quality, and governance trade-offs.

Check the AI layer the way you would check a smart contract. Ask which model powers it, who controls the API key, whether there is a fallback model, whether you approve each transaction, and whether spending caps and contract allowlists are enforced on-chain. A project that discloses its model, cloud, and data dependencies is easier to evaluate than one that does not.

Frontier models depend on advanced chips and large amounts of compute, both of which sit inside active export-control policy. The exact rules have changed, with the United States rescinding its 2025 AI Diffusion Rule while strengthening other chip controls. Restrictions at the chip or compute level can shrink access tiers, raise costs, or limit which models a crypto agent can use.

TLDR: Oman launched Omanhash, a mandatory national Bitcoin mining pool for all licensed crypto miners in the country.
Enegix Global built Omanhash’s tech platform, marking its second sovereign mining pool mandate after Kazakhstan.
The pool targets 10 EH/s in its initial phase, pushing Enegix’s combined global hashrate to around 25 EH/s. Oman has invested over $700 million in mining and data center infrastructure in the Salalah Free Zone since 2022. Oman has launched Omanhash, a state-backed national Bitcoin mining pool requiring all licensed miners to participate.

The pool is a joint effort by the Ministry of Transport, Communications and Information Technology and Frontier Technologies LLC.

Enegix Global built the underlying technology platform and liquidity infrastructure. The move brings Oman’s growing mining sector under a centralized regulatory framework, consolidating an estimated 10 EH/s of hashrate in its initial phase.

Omanhash Brings Licensed Miners Under a Single Regulatory Framework Omanhash.om is the sole official mining pool for all licensed cryptocurrency mining companies in Oman. Under the approved regulatory framework, participation is mandatory for every licensed operator in the sultanate.

This gives the government direct visibility into mining revenue, energy consumption, and newly minted Bitcoin. The structure mirrors Kazakhstan’s model, where licensed miners report earnings to tax authorities through an automated system.

Frontier Technologies LLC, an Omani blockchain and Web3 company, manages and operates the pool alongside Enegix Global.

Enegix serves as the technical and liquidity provider, making Omanhash its second sovereign mining pool contract.

The company also operates btcpool.kz in Kazakhstan and 21pool.io internationally. Combined, Enegix’s pool operations now reach approximately 25 EH/s across its full portfolio.

Olzhas Amirov, Chief Business Development Officer of Enegix Global, explained the broader rationale behind the sovereign mandate. “Governments that want to regulate digital mining effectively need a partner who can deliver both the technical infrastructure and the institutional credibility to operate at that level,” Amirov said.

He added that clear licensing frameworks help miners operate legally, avoid punitive taxation, and maintain transparent communication with regulators. Enegix has set a target of growing its combined pool hashrate to 30 EH/s.

Gauhar Kagira, Director of Enegix Mining Pool, described the launch as a milestone for how sovereign states engage with Bitcoin mining as a strategic industry.

“Omanhash.om is a significant milestone — not just for Oman, but for how sovereign states engage with Bitcoin mining as a strategic industry,” Kagira stated.

He noted that Oman is among the first countries in the region to introduce a structured regulatory framework for miners. The technical execution of the launch was led by Enegix Global.

Oman’s $700 Million Mining Push Enters a New Phase Oman has been one of the most active Middle Eastern jurisdictions for industrial-scale mining investment since 2022. The Ministry launched a $370 million hydro-cooled mining facility in the Salalah Free Zone that same year.

A second major facility followed in 2023, pushing total investments in the free zone past $700 million. Alps Blockchain, an Italian firm, also brought a 150 MW facility in Salalah to full operation in mid-2025.

Omanhash represents the next chapter in Oman’s digital infrastructure strategy. Rather than restricting or banning mining, the government has embedded the activity within its broader economic diversification agenda.

The mandatory pool consolidates existing capacity into a transparent, trackable national architecture. This approach contrasts sharply with jurisdictions that have imposed outright bans or heavy tax burdens on crypto mining.

Yersaiyn Nurtoleuov, Chief Product Officer of Enegix Global, addressed the company’s growth targets following the Oman launch. “With this addition, our combined pool hashrate reaches approximately 25 EH/s. Our target is 30 EH/s — and we are actively building the infrastructure and partnerships to get there,” Nurtoleuov said.

He noted that each new sovereign mandate strengthens both capacity and credibility as an institutional-grade operator. Enegix confirmed it is actively pursuing additional partnerships to reach that milestone.

Oman’s regulatory model could serve as a reference point for other resource-rich nations considering structured mining frameworks.

The combination of mandatory participation, transparent reporting, and state-backed infrastructure creates a governed environment for Bitcoin production.

Omanhash positions Oman not just as a mining destination, but as a country formally integrating Bitcoin mining into national economic policy.

Amirov concluded that the Kazakhstan experience proved the model works, and Oman is now the clearest confirmation of that.

By the authority vested in me as President by the Constitution and the laws of the United States of America, it is hereby ordered:

Section 1.  Purpose.  America stands at the cusp of a quantum revolution.  Quantum information science and technology (QIST) will provide transformational capabilities that will drive American innovation, power economic growth, generate high-paying jobs, and bolster national security.  In 2018, I laid the foundation for United States leadership in QIST by signing into law the National Quantum Initiative Act and doubling Federal investment in QIST research and development.  Today, as other nations move quickly to challenge American leadership, the United States must take a cohesive, whole-of-government approach to accelerate deployment and commercialization of quantum computing, sensing, and networking.

In addition to continuing trailblazing quantum research, we must act to solidify the Nation’s position as the world’s QIST superpower and deliver the commercial and research benefits of quantum innovation to the American people.  Equally important, we must protect sensitive technologies and work with allies to ensure adversaries cannot use QIST to undermine national security.

Sec. 2.  Policy.  It is the policy of my Administration to ensure that the United States maintains a strategic technical advantage in QIST and leads the development of a robust and trusted quantum ecosystem across QIST research, manufacturing, commercialization, and application.

Sec. 3.  Updating the National Quantum Strategy.  (a)  Within 180 days of the date of this order, the Assistant to the President for Science and Technology (APST), in coordination with the Secretary of War, the Secretary of Commerce, the Secretary of Energy, the Director of National Intelligence (DNI), and the Director of the National Science Foundation (NSF), and in consultation with the Co-Chairs of the National Science and Technology Council Subcommittees on Quantum Information Science (SCQIS) and Economic and Security Implications of Quantum Information Science (ESIX), shall update the National Quantum Strategy (Strategy) with policies intended to support the maturing QIST ecosystem, including promoting commercialization and deployment of QIST, supporting the quantum-enabling technology ecosystem, and encouraging partnerships with United States industry.

(b)  Within 30 days of the date of the publication of the updated Strategy, relevant executive departments and agencies (agencies) shall each submit to the APST and the Director of the Office of Management and Budget (OMB) a summary of steps taken to align their processes, policies, and programs with the Strategy.

Sec. 4.  Harnessing Quantum Computing for Scientific Applications.  (a)  There is hereby established the Quantum Computer for Application Development and Discovery Science (QC-ADDS) Effort, which shall be coordinated by the APST.  This national effort shall pursue development of a quantum computer at a scale intended to initiate the era of quantum-enabled scientific discovery, with the intent to deliver at least one such computer to a Department of Energy facility and, to the extent possible, make it available to the scientific community.

(b)  The Secretary of War, the Secretary of Commerce, the Secretary of Energy, the DNI, the Director of NSF, and the heads of other relevant agencies as appropriate, in consultation with the Director of OMB, shall ensure that relevant capabilities, manufacturing infrastructure, and expertise are made available to support the QC-ADDS Effort to the extent practicable, and shall deploy these resources towards exploration of quantum-computer-enabled capabilities for commercial, government, and national security applications.  Additionally, the APST shall coordinate with the Administrator of the National Aeronautics and Space Administration (NASA), the Director of the National Security Agency (NSA), and the heads of other relevant agencies to identify additional actions to enhance the QC-ADDS Effort.

(c)  Within 90 days of the date of this order, the Secretary of Energy, in coordination with the APST and the heads of other relevant agencies, shall identify the technical specifications required for a QC-ADDS to perform transformative scientific applications that are on a path towards economically significant applications and beyond current classical computer capabilities, and shall publicly release a summary of those specifications, as appropriate.

(d)  Within 180 days of the date of this order, the Secretary of Energy, in consultation with the Director of OMB, shall explore potential private-sector partnership models to understand the potential cost, scope, and time frame for delivery of at least one QC-ADDS as described in subsection (a) of this section.  Further, the Secretary of Commerce shall develop a plan, potentially including advance market commitments, to encourage contributions to the QC-ADDS Effort from commercial quantum computing companies.  Finally, the Secretary of War shall establish or designate activities and programs to develop the tools and capabilities necessary to advance readiness for national security applications of quantum computing, potentially including the establishment of a center for such purpose.

(e)  To provide for the robust assessment of the QC-ADDS’ and other quantum computing systems’ capabilities, within 180 days of the date of this order:

(i)   the Secretary of Energy, in consultation with the Secretary of War and the Secretary of Commerce, shall establish a national center to develop the tools and capabilities required to accurately assess the performance of quantum computing systems; and

(ii)  the Co-Chairs of the ESIX Subcommittee shall recommend to the APST a mechanism to facilitate information-sharing between relevant agencies to improve the Government’s ability to assess commercial quantum computing capabilities.

(f)  The DNI and the Secretary of War, in coordination with the Co-Chairs of the ESIX Subcommittee and in consultation with the Secretary of State, the Secretary of Commerce, and the Secretary of Energy, shall identify the national security implications of the increasing scale and performance of commercial quantum computers, such as the implications for the migration to post-quantum cryptography.

Sec. 5.  Deploying Quantum-Enabled Sensors and Networks.  (a)  Within 60 days of the date of this order, the Secretary of War shall identify at least three next-generation quantum sensor projects to prioritize in order to field these sensors by September 30, 2028.

(b)  Each of the following heads of relevant agencies shall develop a 5-year plan for advancing quantum sensing and networking as follows:

(i)    the Secretary of Commerce shall develop a plan for advancing commercial readiness of quantum sensing, quantum-sensor manufacturing technology, and quantum-network-enhanced timing;

(ii)   the Secretary of Energy shall develop a plan for using quantum sensing and imaging to measure and characterize complex systems, and for using quantum networking to enable distributed quantum computing;

(iii)  the Director of NSF shall develop a plan for basic science research to identify applications of quantum sensing and networking, develop novel systems-level concepts, and improve QIST manufacturing science; and

(iv)   the Administrator of NASA shall develop a plan for developing and extending civilian quantum sensing and networking for space applications.

(c)  The heads of relevant agencies shall prioritize research, development, testing, and evaluation of applications and hardware for quantum sensing and quantum networking.

Sec. 6.  Bolstering the Domestic Ecosystem for Quantum Supply Chains.  (a)  The Secretary of Commerce, in consultation with the Secretary of Energy and the heads of other relevant agencies, shall develop a plan to strengthen the QIST ecosystem through analyzing QIST supply chains, encouraging private sector adoption of QIST-related standards, and supporting research and development pathways that advance quantum-enabling technologies and eliminate QIST manufacturing barriers.

(b)  Within 120 days of the date of this order, the Secretary of War, the Secretary of Commerce, the Secretary of Energy, and the Director of NSF shall develop a plan, with coordination from the APST and the Director of OMB, to encourage and partner with the private sector, potentially using prize challenges or advance market commitments, to develop quantum-enabling component technologies in the United States, and to identify any changes to statutory or regulatory authorities required to address quantum-specific market hurdles.

(c)  All relevant agencies shall take steps to share, to the maximum extent possible, information regarding quantum computing supply chains, such as that generated by the Defense Advanced Research Projects Agency Quantum Benchmarking Initiative, with the Departments of War, Commerce, and Energy and with the APST and the Assistant to the President for National Security Affairs (APNSA), to inform Government-wide decision making.

(d)  Within 180 days of the date of this order:

(i)   the Secretary of War, in consultation with the heads of relevant agencies, shall take steps to increase domestic access to Department of War-sponsored QIST-relevant foundry resources, and strengthen efforts, as appropriate, to improve access to critical QIST supply chains; and

(ii)  the Director of NSF shall take steps to issue grants for establishing QIST user facilities through the National Quantum and Nanotechnology Infrastructure program.

(e)  Within 210 days of the date of this order, to support the reconstitution of the National Quantum Initiative Advisory Committee (NQIAC), as provided in section 104 of the National Quantum Initiative Act of 2018, as amended, and pursuant to Executive Order 14073 of May 4, 2022 (Enhancing the National Quantum Initiative Advisory Committee), the APST shall recommend a revised NQIAC membership list and shall task the NQIAC to develop recommendations for stimulating the development of quantum-enabling technologies in the United States.

Sec. 7.  Protecting Quantum Technology.  (a)  The APST and the APNSA, in consultation with the Co-Chairs of the ESIX Subcommittee, shall coordinate with the relevant agencies to ensure that QIST activities and policies maintain robust and balanced security controls to safeguard critical information and protect national security interests, while not unduly impacting quantum innovation in the United States.

(b)  The Director of the Federal Bureau of Investigation, in coordination with the Secretary of State, the Secretary of War, the Secretary of Commerce, the Secretary of Energy, the Secretary of Homeland Security, the DNI, and the Director of the NSA, shall propose to the APST, the APNSA, and the Director of OMB staffing requirements to expand the Quantum Information Science and Technology Counterintelligence Protection Team (QCPT) to improve and coordinate protections against adversarial threats to the QIST ecosystem, including cybersecurity threats, coordinate public messaging and outreach related to those threats, and enhance sharing of threat information with Federal, industry, and academic QIST research and development entities.  Relevant agencies shall coordinate and deconflict with the QCPT on all outreach to QIST industry and academia related to quantum-specific security guidance and threat information.

Sec. 8.  Expanding and Retaining the Quantum Workforce.  (a)  Within 90 days of the date of this order, the Director of the Office of Personnel Management, in consultation with the APST and the Director of OMB and in coordination with the Secretary of War, the Secretary of Commerce, the Secretary of Energy, the DNI, and the Director of NSF, shall develop a Government-wide QIST recruitment and retention strategy, potentially including special pay rates and increased limits for recruitment and retention incentives.  This strategy should complement existing efforts to build a strong national security quantum-workforce.

(b)  Within 120 days of the date of this order:

(i)   the Secretary of Labor shall ensure that QIST-relevant industry needs are prioritized in workforce training efforts related to Executive Order 14278 of April 23, 2025 (Preparing Americans for High-Paying Skilled Trade Jobs of the Future), and the implementation of America’s Talent Strategy where possible, including related to the expansion of registered apprenticeships for relevant occupations; and

(ii)  the Secretary of Labor and the Director of NSF, in coordination with the Co-Chairs of the SCQIS Subcommittee, shall develop an approach to tracking labor statistics for assessing the needs of the United States quantum ecosystem, including developing a definition for “QIST-relevant occupations”, and associated skills and credentials.

(c)  Within 180 days of the date of this order:

(i)   the APST shall engage with United States industry and academic institutions to promote the expansion of post-secondary training opportunities for supporting skillsets that will lead Americans into rewarding QIST industry jobs, such as by prioritizing hands-on training with QIST systems or concepts; and

(ii)  the Director of NSF shall take steps to initiate a network of National QIST Workforce Development Institutes to enhance QIST training opportunities and coordinate training efforts across Federal, State, and local agencies.

Sec. 9.  Engaging with International Partners.  (a)  The Secretary of State and the Secretary of Commerce, in coordination with other relevant agencies as appropriate, shall align their respective international engagements in ways designed to:

(i)    ensure that United States quantum and quantum-enabling technology companies have access to strategic markets and capital from like-minded countries;

(ii)   maintain an international ecosystem of quantum-enabling technology companies with access to trusted supply chains, through, for example, harmonizing investment restrictions with international allies and partners;

(iii)  prevent countries of concern from acquiring critical quantum-enabling technologies, through, for example, harmonizing research security and export control policies with international allies and partners;

(iv)   promote and enhance research and development collaboration and the flow of people and ideas across like-minded countries in support of the interests of the United States quantum industry; and

(v)    develop, promote, and coordinate effective quantum research and technology protection efforts with like-minded countries.

(b)  The Secretary of Commerce, in coordination with the United States Trade Representative, shall identify and provide recommendations to the President, through the APST, to address foreign trade barriers, discriminatory treatment, and other policies that limit the competitiveness of American QIST companies.

(c)  Within 120 days of the date of this order, the Secretary of State shall provide recommendations to the APNSA and the APST on how to align existing bilateral and multilateral international engagements, including Pax Silica, to advance the priorities of this order.

Sec. 10.  Reports.  (a)  Reports shall be submitted to the President, through the APST and the Director of OMB, regarding the actions directed in:

(i)   section 6(a) of this order within 90 days of the date of this order; and

(ii)  section 5(b) of this order within 120 days of the date of this order.

(b)  Reports shall be submitted to the President, through the APST and the APNSA, regarding the actions directed in:

(i)   section 7(b) of this order within 60 days of the date of this order; and

(ii)  section 9(a) of this order within 180 days of the date of this order.

(c)  Reports shall be submitted to the President, through the APST, the APNSA, and the National Cyber Director, regarding the actions directed in section 4(f) of this order within 1 year of the date of this order, and annually thereafter.

Sec. 11.  General Provisions.  (a)  Nothing in this order shall be construed to impair or otherwise affect:

(i)   the authority granted by law to an executive department or agency, or the head thereof; or

(ii)  the functions of the Director of the Office of Management and Budget relating to budgetary, administrative, or legislative proposals.

(b)  This order shall be implemented consistent with applicable law and subject to the availability of appropriations.

(c)  This order is not intended to, and does not, create any right or benefit, substantive or procedural, enforceable at law or in equity by any party against the United States, its departments, agencies, or entities, its officers, employees, or agents, or any other person.

(d)  The costs for publication of this order shall be borne by the Department of Energy.

                             DONALD J. TRUMP

THE WHITE HOUSE,

    June 22, 2026.