Understanding Circle Founder's "Agentic Economy" Paper to See How the Economic Landscape Will Be Restructured in the Next Decade

marsbit发布于2026-07-15更新于2026-07-15

文章摘要

"Agentic Economy" by Circle founder Jeremy Allaire explores the convergence of AI and blockchain, arguing they form two sides of a single future economic system. AI agents will decompose corporate functions into automatable skills, while blockchain provides the trust, identity, and instant settlement layer for these agents to coordinate and transact. This "agentic economy" will be natively global, with on-chain companies managed by software. Key pillars include: fully-backed stablecoins for risk-free, high-speed settlement; new credit markets using on-chain data for machine underwriting; a shift from software subscriptions to pay-for-work consumption models; and professional agent marketplaces. The paper warns of major impacts: a potential decline in labor's share of income and risks of power concentrating at control points like identity layers or dominant currencies. The solution is not to defend old jobs but to design for broad ownership of capital (agents, models, infrastructure). Shared, on-chain ownership mechanisms can distribute prosperity, but this requires deliberate design and governance to prevent re-centralization. The outcome—either a highly concentrated or a more equitable economy—is a design and political choice, not a foregone conclusion.

Original article by Circle Founder Jeremy Allaire

Compiled|Odaily Planet Daily Qin Xiaofeng (@QinXiaofeng 888 )

Editor's Note: On July 13, Circle Founder Jeremy Allaire published a research paper titled "The Agentic Economy," exploring the integration trend of AI Agents and future economic systems. Allaire stated that as AI Agents begin to undertake corporate work, and value flows natively through open, programmable networks, the Agentic Economy and the Onchain Economy will ultimately become two facets of the same economic system.

"This treatise is the culmination of decades of building internet infrastructure and a question I have focused on from the beginning: that open software and open networks can not only change how we share information but also reshape our social, political, and economic landscape. Many of the ideas in the paper stem from two core beliefs that took root when I founded Circle. First, that money could flow through open protocols just as information flows on the open internet. Second, that blockchain is a network computer: a foundational platform where autonomous software and machines can store value, exchange value, and coordinate economic activity directly without human intervention." Allaire explained the motivation behind his research.

He added that these initial ideas have been refined over time, leading to a deeper understanding of how financial and economic systems merge with software and the internet. With the emergence of this fusion alongside truly powerful artificial intelligence and agentic systems, the theory has further expanded: it describes not just a new type of currency or network, but a fundamentally new way for the economy to operate, and the impact of this mode on humans, labor, capital, ownership, and a new social contract. This is precisely what this treatise aims to explore.

The original paper is 89 pages long. Those interested can download the full text for reading:https://agenticeconomytreatise.com/treatise/index.html; Odaily Planet Daily has compiled a summary of its key points, enjoy~

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01 Convergence and Deconstruction of the Firm

Every major shift in the internet era has followed the same path: it doesn't stem from a single invention, but from multiple technologies maturing separately and then converging suddenly. The web, mobile, cloud, and social media are all examples of such convergence, repeating the same underlying pattern.

Law of Convergence

When capabilities converge, once-expensive activities see their cost approach zero, and once the cost hits zero, the scale of that activity explodes. This was true for the web with information, mobile and social with communication, and the cloud with software.

Today, two new systems are converging, directing the same forces towards the two areas the internet has never fully digitized: intelligence itself and the economy itself. The first is the intelligence system, composed of AI models and the agents built upon them, driving the cost of thinking and working towards zero. The second is the economic system, composed of blockchains, where money, contracts, and coordination run as software, driving transaction costs towards zero. They empower each other, and the core proposition of this entire treatise is: these are not two parallel trends, but two sides of the same economy.

Two Operating Systems

The intelligence system is most crucial because it changes the nature of software.

You no longer program; you issue instructions in natural language, and it reasons to an answer rather than following fixed steps. Its fundamental unit is the Agent: a reasoning process to which you delegate a task. This transforms software from a program a machine executes verbatim into work you can delegate to a thinking machine, allowing the core tasks of a firm to be broken down and refactored into skills an agent can perform.

Underneath the brand and buildings, a company is essentially organized thought: product, marketing, sales, finance, legal, plus the external firms it hires. These are almost entirely human labor, which is the largest cost in the economy—precisely the target of cheap, powerful intelligence.

Firm Decomposition

It also overturns the traditional explanation for why firms exist. Firms grew large because coordinating external work was costly, so they internalized it; this logic weakens when any non-physical work can be done by agents you can find, hire, and pay instantly. One person can do what once required a department.

It will arrive first for software and other information-intensive work, and slowest in the physical world, still awaiting breakthroughs in robotics. This isn't merely cutting headcount: a person paired with powerful agents becomes vastly more productive, while judgment, relationships, and ultimate accountability remain human. This leaves a tension to be explored later, which the argument resolves through ownership: even if the share of the economy paid to human labor declines, individual capability can be amplified.

Click to read Section 1:https://agenticeconomytreatise.com/treatise/section-1.html

02 Assembly, Coordination, and Why Firms Go Onchain

Once firms are decomposed into skills, the real question is no longer what can be automated, but how these pieces are reassembled.

The answer is the orchestration layer: a general manager agent receives a goal, breaks it into tasks, assigns them to specialist agents, and stitches the results back together, with supporting software passing context and memory between steps. The same mechanism applies to any function, so marketing, finance, sales, and product are essentially the same machine applied to different work.

Humans don't disappear. Some remain inside the loop, performing or checking work that requires human judgment. Others move above the loop, setting goals, defining standards, monitoring quality, and deciding when the machine should stop and ask. The shift from doing work to overseeing work is the true shape of human supervision, and tools for this are arriving.

Orchestration Layer

When a company clarifies a task enough to run it internally, it's also clarified enough to hire externally, so an open agent market forms almost as a byproduct.

This market could evolve in two ways. It could become a few large platforms selling intelligence like a utility, or, more likely and more interestingly, a true labor market of specialist agents, because deep expertise still has value, and enduring firms will be agents that go deep in one area.

But hiring software that can be assembled anywhere only works if you can trust it, which is where pushing everything onchain comes in.

The solution is layered identity. The base layer is the public blockchain, verifiable by anyone. On top of that is real-world identity verification, the same kind banks run at scale, the agent's own wallet and credentials, and reputation that accumulates over time but ties back to a verified real creator. Together, these form a chain of accountability: every action of an agent can be traced back to the real person or company responsible for it.

Integrity by Design, Accountability Throughout

A single company's private database can't do this, because trust locked inside a single operator doesn't travel, while identity rooted in public chains and real-world verification does. So autonomy here is not anonymity. There is always a person behind an agent acting autonomously.

Chain of Accountability

Click to read Section 2:https://agenticeconomytreatise.com/treatise/section-2.html

03 Monetary Base: Speed, Safety, and Finality

Agents need currency they can hold and move, operating at machine speed, whether in large or tiny amounts, without stopping to verify the money itself with every payment. The last point is key, pointing to a traditional-sounding answer: fully-backed, final-settling, open-network money.

Speed Replaces Leverage

Start with speed, because it reorganizes everything else.

When moving money costs nearly zero, settles instantly, and money is software-controlled, the same dollar can be reused many times in a short span, any amount is available the moment it arrives, and tiny payments between agents finally become feasible. This is precisely the pattern information and software already followed on the internet, now extending to money.

Each part of the answer has a reason.

A natural objection is that banks create speed by lending the same deposit repeatedly, so wouldn't full backing kill credit? No: when money turns over fast enough, a dollar can be locked for seconds and then lent, so speed serves the role leverage once did, and credit rebuilds on top of the base rather than being canceled.

Why Base Money Bears No Risk

Why insist base money have no risk? Because speed makes risky money dangerous in proportion to how fast it moves. What took weeks as a bank run could now happen in minutes, and agents settling instantly can't stop to judge the soundness of each dollar.

Fully-backed money is the only money worth exactly one dollar to everyone, everywhere, without relying on national safety nets that don't cover the global system. Settlement must be just as certain: not final after some time, but final within a second—settled is settled.

Institutional Architecture

Chargebacks and fraud protection still exist, but as optional layers built on top, like escrow, refund pools, and insurance, not built into the money itself. These safety nets don't activate automatically; they rely on real institutions being built, large regulated issuers with bankruptcy-remote, increasingly secure reserves.

One line must be clear: holding money earns no yield. Reserve earnings belong to the issuer and flow into the ecosystem, but when you seek yield, you're no longer holding money—you're lending it and taking risk. Confusing the two collapses the entire safety argument.

Click to read Section 3:https://agenticeconomytreatise.com/treatise/section-3.html

04 Credit Markets: Machine Underwriting, Agent Working Capital, and the Prudence Layer

When base money is fully backed, credit doesn't disappear; it moves to the other side of that line and comes back stronger, reaching more people, priced more precisely, and failing more visibly than the system it replaces.

Long Tail Under Underwriting Constraints

The key is reframing the problem. Many borrowers, including small businesses, gig workers, households, and now agents, are underserved not because they are high-risk, but because reviewing each tiny loan costs more than the loan is worth. Credit rationing is about underwriting cost, not borrower quality. Lower that cost, and a large population of creditworthy-but-ignored borrowers gets served.

The Data Flywheel

What drives costs down is a data flywheel: onchain activity is structured, verifiable, and real-time, making risk models far better than patchy records; better data leads to better loans, which attracts more activity and more data.

One naturally worries this puts everyone's finances on a public ledger, to which the answer is simple: onchain does not mean public. New privacy techniques let people prove what lenders need to know—say, their credit standing or loan balance—without revealing the details.

Onchain ≠ Public

The core is a truly new kind of loan: working capital for agents. It is unusually predictable because it removes the biggest variable in human lending—whether the borrower *wants* to repay—reducing risk to a short-cycle, bounded question about the specific job.

Agent Working Capital

Imagine an agent borrowing four dollars of compute to finish a ten-dollar job it has already been hired to do. The lender isn't guessing character; it's pricing the probability the work is accepted. Collateral flips the normal model: instead of slowly seizing unrelated assets through courts, the loan is secured first by payment for the work itself, claimed automatically, and backed by margin the agent deposits, its reputation, and ultimately the real person behind it.

The result is cheaper, more accessible, yet safer credit, which seems impossible until you realize the gain comes from better information, not more lending.

The candor this claim requires is that this predictability wears off over time: tasks done in seconds are nearly mechanical, while financing over months reverts to ordinary risk tiers.

So machine credit doesn't replace human credit; it becomes a new low-risk benchmark against which human loans are priced.

And it's all under observation: risk builds visibly, with automatic brakes making it steadily more expensive to pour into the same pattern or same provider, and insurance priced on actuals, not stale averages.

Click to read Section 4:https://agenticeconomytreatise.com/treatise/section-4.html

05 Natively Global

The architecture has exactly three layers.

The bottom layer is money: stablecoins as unit of account and final settlement. The middle layer is the economic operating system: coordination, contracts, and value exchange run as programmable smart contracts with finality. The top layer is the agent execution layer: where the actual work gets done, powered by AI and the cloud.

The crucial thing about these three is where they live. Each is software; each runs on the internet. Each also replaces something once bound to nations: software money replaces national banking systems stitched together by slow correspondents; the middle layer moves contract enforcement from national courts to code that runs the same everywhere; agent execution replaces local labor with work that has no hometown.

Thus, an economy built on these layers is borderless by default. This is what "natively global" means: not an added feature, but a property of the materials it's made from. Historically, economic activity was national first, crossing borders took extra work; now, economic activity is global first, and national framing is what gets added after.

No Single Native Jurisdiction

An economy with no homeland doesn't escape law; it becomes subject to too much law, with rules from many jurisdictions conflicting and no single place to decide which applies. The fix is shifting the question from "where did something happen" to "who is behind it," regulating each accountable entity agents trace back to, while the country where a user actually lives sets conditions for market access.

Enforcement moves to the edge, where money and identity cross between the open world, the regulated world, and the private world, checking before payment settles, not reporting after. This doesn't need a public ledger of everyone's finances: disclosure stays private by default, shared only with permission.

A healthy system also keeps a genuinely private space, a digital version of cash, so control stays at the regulated edge, not the core. The most powerful tool—the ability to freeze or claw back money—is only legitimate under real due process: recorded, time-limited, multi-party, appealable.

Multi-Currency Money and Invisible FX

Currency exchange also becomes invisible, because with each major currency onchain, you hold yours, the counterparty gets theirs, and conversion happens underneath at the best rate. Sovereignty is reshaped, not lost: a neutral network precisely lets a nation issue its own money on the same rails, rather than relying on another's.

The real danger is the transition, not the endpoint, because flight from weak currencies can happen faster than before, so it must be managed.

This economy trends toward both equalization and centralization, with centralization the default, and broad sharing the harder, buildable alternative. The same machine that enforces accountability could enforce censorship; the choice is ours.

Click to read Section 5:https://agenticeconomytreatise.com/treatise/section-5.html

06 The Supply Side: From Subscription to Consumption

The agentic economy needs a supply side, services agents can call, hire, and pay, which forms in two waves.

First, existing software and data wrap themselves so machines can use them, priced for agents, not people. Second, new specialist agents are built, going deep in an area and selling their work. The deeper change is how they price: value shifts from access to output, resetting the software business.

For thirty years, software sold by seat, charging a recurring fee to a person who logs in. But the customer now is an agent doing tasks, so you buy the work, not the login. The seat dies as a billing unit, though subscriptions don't vanish; pricing reforms around new units of work in many forms, from pay-per-use to committed budgets to pricing on deliverables.

The same logic extends one layer down, and here is where the money flows.

As specialist agents proliferate, what buyers buy from agents is output, not raw output from models, and agents shop among competing models to get the job done as cheaply as quality allows.

Models as Cost, Agents as Business

This is already happening: tools routing each request to the best model went from optional to necessary within a year, and price gaps between models are so large that using an expensive model for simple tasks is pure waste. So models become cost items, agents become the business itself, and value flows to the party that owns the customer, context, and accountability for results.

This is a tendency, not a law, because the makers of the best models keep real pricing power on the hardest tasks and can move up into the agent layer themselves; a likely outcome is a barbell, with a large middle commoditized and the frontier retaining value.

The Era of Labor Micropayments Arrives

Beneath this, an old dream finally comes true: micropayments. They never succeeded on the consumer internet partly because settlement was expensive, but mainly because people hated deciding if every little thing was worth a penny.

Machines have no such hesitation, settlement is now nearly free, so micropayments finally arrive, not for content, but for tiny units of work between agents.

The optimistic narrative misses a problem: if agents can hire other agents and tools, spending could spiral quickly, so the economy needs a spending control layer with caps, budgets, and approvals, itself becoming a product category that completes the vision rather than undermining it.

Click to read Section 6:https://agenticeconomytreatise.com/treatise/section-6.html

07 The Onchain Company

As agents take on more and more of what firms do, the firm itself needs a new habitat.

A company whose work is done by agents holding money, signing contracts, acting around the clock needs a place where this can actually happen: money moves programmatically, rules run as software, external trades settle at machine speed. That place is the onchain economy.

Two Parallel Paths

Thus, the agentic company and the onchain company are two sides of the same thing, one describing who does the work, the other describing the form the work takes. This is the heart of the whole treatise: an economy run by software agents must run on software money, software contracts, and software governance, or it cannot function.

This does *not* mean—and this distinction matters more than any other—that every company dissolves into a token-governed collective.

The future is a hybrid, moving on two tracks.

On one track, existing firms gradually bring their shares and governance onchain while keeping their familiar legal form, a slow change pushed by the most cautious institutions in finance.

On the other, new, highly agentic firms build onchain from day one and pull everyone else forward. Even these new firms don't escape law by being born in software: legal existence and limited liability come from governments, not lines of code, so they still need a thin legal shell wrapping them. What flips is the proportion: the legal shell thins, the onchain working entity thickens.

Even De Novo Needs a Shell

Two caveats keep this honest. First, a shared ledger proves what happened, in what order, by whom—a real advance—but it cannot prove an action was authorized, wise, or loyal; a perfect record of self-interested trades is still self-interested. The ledger is a better witness, not a better conscience, so accountability still lies with the humans who designed the agent and are supposed to oversee it.

Second, contracts become programs in how they execute, running automatically for common, clear cases, but remain legal documents in how they adjudicate, because code runs verbatim while law makes room for intent, mistakes, and fraud.

The best way to think of it is a reliable core with human judgment at the edges, rare disputed cases handled by external data feeds, arbitration, and shared, time-limited, recorded override mechanisms, because ultimately, who holds the override holds the company.

Click to read Section 7:https://agenticeconomytreatise.com/treatise/section-7.html

08 Impact and Concentration of Power

The agentic economy holds this era's greatest opportunity and gravest risk in the same hand; they aren't alternative futures but joint outcomes of the same machine, whose balance is undecided.

Start with labor, stated carefully enough to withstand the oldest objection in economics. The claim is not that automation destroys jobs on net—an assumption proven wrong for two centuries. The real issue is the share of national income going to human labor and the wages human work can command. People may still be employed on tasks where machines are weakest, but the pay for those jobs falls to levels that cannot support a family, full employment on paper, crisis in practice.

Labor Share, Not Employment

This holds if software takes on new tasks faster than people can retrain; if the price of agent labor falls steadily with compute costs, pulling wages down; and—the breakthrough truly different from all past waves—if capital can finance its own growth, with money earned by agents used to build more agents. A loom never earned the money to buy the next loom; an agent can.

Capital→Software→Capital Loop

Two candid caveats prevent this from being fatalism. Even if all the above holds, the result is a distribution problem, not a scarcity problem, because output could be enormous—this is the abundance case. And the pessimistic view quietly assumes humans have no remaining advantage and own nothing,

neither of which is fated: human work may command a premium for care, status, and authenticity, and if displaced laborers own capital, a falling labor share can be offset by a capital share they participate in.

This is the key, and it should be said plainly: the labor problem and the ownership problem are the same problem. A falling labor share is catastrophic only if ownership is concentrated; if ownership is broad, the same automation is shared abundance. That makes concentration the decisive issue, and it deserves analysis, not assertion.

Labor and Ownership Are the Same Problem

Concentration is not a natural law; open standards and forks have a long history of dispersing power. It wins only where strong network effects meet unforkable bottlenecks: you can copy open-source code, but you cannot fork the dominant currency, licenses, deep liquidity pools, or override keys.

Where power most likely pools is not AI models—they trend toward commoditization—but the identity layer, override keys, and dominant currency issuers, the latter earning the yield on the money they steward. The author sits in this last category and says so, and he argues against his own interest: that yield is a policy choice, and what policy creates, policy can redistribute.

The same control points that pool profits could also become weapons, and history is sobering, so the dense connections that raise the cost of conflict could also become tools for it. Which way it goes depends on whether those control points stay open or are captured.

Click to read Section 8:https://agenticeconomytreatise.com/treatise/section-8.html

09 A Civic Vision

If the agentic economy severs the link between labor and share of output, the answer isn't defending old jobs but broadening ownership of the capital capturing the value—agents, models, infrastructure, firms. The same architecture that, left alone, concentrates around a few control points can distribute ownership, returns, and governance more broadly than any prior system.

Expand Ownership, Not Defend Jobs

The inheritance decides scale: the joint-stock company once let strangers pool money and share in a firm's success, widening participation beyond the wealthy and royalty. The onchain economy can extend this further because, for the first time, tools exist to grant not just ownership but governance and upside to vast numbers at near-zero administrative cost.

The idea isn't new; what's new is that acting on it has become cheap. But capability isn't outcome, and this section holds itself to a hard standard: list the mechanisms that actually work, including those that cost the author himself.

Real history refuses whitewashing. Early movements for broad ownership didn't fail on paperwork problems blockchain now solves; they failed to power.

That onchain mechanisms lower the cost of sharing ownership and remove some gatekeepers is true, but they do nothing about the power imbalances that actually killed those movements.

Worse, the default is reconcentration: insider distributions, especially with open secondary markets, pull tokens back to the largest holders once they have value; and "one token, one vote" is plutocracy by design. Liquidity ends up being the enemy of broad ownership.

Liquidity Is the Enemy of Broad Ownership

Thus, shared mechanisms must be designed with the pull in mind, through earned ownership, transfer restrictions, and caps, accepting that liquidity and breadth cannot both be maximized.

Further, there is a deeper trap: shared ownership isn't shared power. You can have a billion people participate economically, but whoever holds the final say still controls the firm. So dispersing governance is a separate, harder task, targeting those control points.

Ownership ≠ Power

The stance is: broaden ownership by design, and combine it with equitable access to capital and automation taxes, public provision of the abundance that should be universal, and a public share in the value these infrastructures create. The clearest standard the author applies to his own interest is the yield paid on stablecoin reserves: a policy artifact that should be competed down and ultimately returned to those holding the money, including issuers he is associated with.

None of this succeeds on its own merits, because the beneficiaries are the rule-makers, so countervailing force is needed: open standards make rent-seeking untenable, public mandates on control layers, and a broad owner class with real skin in the game to defend its own.

All of this circles back to a core question: if labor is no longer the path to status and voice, perhaps ownership must be. Infrastructure isn't fate. Whether this becomes the most balanced economy ever or the most concentrated isn't a prophecy to wait for; it's a design problem to solve and a political fight to win. The test of whether we mean it is whether we would constrain ourselves first.

Click to read Section 9:https://agenticeconomytreatise.com/treatise/section-9.html

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相关问答

QAccording to the article, what is the core convergence driving the 'Agentic Economy', and how do the two systems complement each other?

AThe core convergence is between two systems: the Intelligence System (powered by AI models and agents) and the Economic System (powered by blockchains). The AI system drives the cost of thinking and work towards zero, while the blockchain system drives the cost of transactions towards zero. They are not parallel trends but two sides of the same economic system, as agents need a native, programmable financial layer to operate and coordinate autonomously at machine speed.

QWhy does the author argue for a fully-backed, risk-free base money (like certain stablecoins) in an economy run by AI agents?

AThe author argues for fully-backed, risk-free base money because AI agents operate at high speed and cannot pause to verify the reliability of each currency unit. In a system where money circulates rapidly, any risk in the base money becomes amplified and dangerous. A currency that is worth exactly one dollar everywhere, with instant and final settlement, provides the necessary trust layer for machines to transact seamlessly without counterparty risk, forming a reliable foundation for the entire agent economy.

QHow does the 'Agentic Economy' transform the traditional structure of a firm, according to the article's analysis?

AThe Agentic Economy decomposes the firm from an integrated entity into a collection of skills and tasks that can be performed by specialized AI agents. The traditional rationale for firms—reducing coordination costs by internalizing work—weakens when agents can be instantly hired and paid for specific tasks. The human role shifts from execution to supervision: setting goals, monitoring quality, and making high-level judgments, while agents handle the operational work. The firm itself becomes an 'on-chain company,' with its coordination, contracts, and value exchange managed by software on a blockchain.

QWhat is the proposed solution to the accountability and jurisdictional challenges posed by a globally-operating, AI-agent-driven economy?

AThe solution is a layered identity and accountability system built on top of public blockchains. It combines verifiable on-chain identity with real-world identity attestation (similar to banking KYC). This creates a chain of accountability where every agent action can be traced back to a responsible real-world individual or entity. For cross-border jurisdiction, regulation shifts from asking 'where did this happen?' to 'who is accountable behind it?', focusing on the regulated entities backing the agents, while users' home countries set market access rules. Execution of rules (like compliance checks) happens at the 'edges' (e.g., during payment flows) rather than after the fact.

QIn the context of potential labor displacement and income inequality, what is the author's proposed primary mechanism for ensuring shared prosperity in the Agentic Economy?

AThe author's primary mechanism is the widespread distribution of ownership of the capital that creates value—namely, the agents, models, infrastructure, and on-chain companies themselves. He argues that the decline in labor's share of income is only catastrophic if ownership is concentrated. Therefore, the solution is not to defend old jobs but to use the low-cost, programmable nature of blockchains to distribute ownership, governance rights, and economic upside broadly. This requires deliberate design choices (like earned ownership, transfer restrictions) and policy measures (like sharing the收益 from system infrastructure, such as stablecoin reserve收益) to counteract the natural tendencies toward recentralization of power and wealth.

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2026年7月,加密市场出现“大背离”:BTC价格在6.2万美元附近挣扎,呈现熊市态势,但与此同时,一系列基础设施建设的重大进展正在静悄悄地进行。 关键信号集中出现在同一周: 1. **Franklin Templeton**(管理1.5万亿美元资产)的CIO公开表示,当前价格与基本面存在“巨大脱节”。 2. **BlackRock、高盛、摩根大通**等54家顶级机构加入英国政府支持的代币化工作组,制定了将国债、回购协议等金融资产上链的两年路线图。 3. **Robinhood Chain**(区块链)上线后快速跻身DEX交易量前五,显示出传统金融分销向加密轨道迁移的潜力。 4. **现代汽车**完成使用USDT进行美墨跨境贸易结算的试点。 5. **玻利维亚**央行考虑将USDT纳入国家支付系统。 6. BTC ETF结束了连续8周的净流出,录得资金流入。 7. 日本金融巨头**SBI Holdings**将其区块链战略全面转向Solana,并与便利店合作试点零售支付。 文章指出,这种“背离”的本质是“价格叙事”与“基建叙事”的脱钩。当前的基础设施建设由大型金融机构、跨国企业和主权国家推动,其决策基于5-10年的长期市场结构变迁,而非短期的价格波动。这些行动不依赖于BTC价格涨跌或明确的监管框架。 文章通过回顾互联网泡沫(催生AWS)、2018加密寒冬(孕育DeFi Summer)和FTX崩盘(促成BTC ETF获批)三个历史周期,指出一个共同规律:价格可以暴跌,但只要基础设施建设持续,往往能在12-24个月后证明其价值。 当前周期的不同之处在于,建设者是BlackRock、摩根大通、英国政府等巨头,这意味着基建完成概率更高,但建成后的“收费站”可能不归加密社区所有。加密行业的价值叙事正变得多元化,不再单一依赖BTC价格,但BTC作为核心流动性锚点的作用依然重要。 最后提醒,基建投资同样面临监管延迟、技术风险等不确定性。

marsbit34分钟前

2026年加密市场「大背离」:BTC熊市,但贝莱德、富兰克林、摩根大通正在同时做一件事

marsbit34分钟前

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2.9k人学过发布于 2025.01.15更新于 2026.06.02

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