Agents Capital Markets: How Will Autonomous Agents Get Funded?

链捕手Xuất bản vào 2026-05-19Cập nhật gần nhất vào 2026-05-19

Tóm tắt

"Agents Capital Markets: How Autonomous Agents Will Raise Capital" Within a decade, specialized capital markets will emerge for AI Agents—software entities with legal personhood that perform work, earn revenue, and need capital. Unlike today's AI companies (like Sierra or Harvey) backed by traditional VC, these future *Agent companies* will be autonomous, legally-recognized entities (e.g., Wyoming memberless LLCs) that directly own assets, sign contracts, and incur liabilities. The driving forces are fourfold: 1) **Overwhelming economics** (Agent companies can deliver services at 85-90% lower cost than human firms); 2) **Proven demand** (current Agent operators already generate billions in revenue); 3) **Existing legal frameworks** enabling algorithmically-managed companies; and 4) **Massive, yield-seeking capital pools** (e.g., private credit) looking for new, uncorrelated assets. Agent capital markets won't rely on one model but a multi-layered "stack" matching different growth stages: 1) VC equity for early human-led builders; 2) Programmatic working capital advances (like Stripe Capital); 3) Revenue-based financing (RBF); 4) Slate financing (pooled funds for many Agents, similar to Hollywood); and 5) Tokenization as a secondary settlement layer, not a primary funding source. The ultimate shift is from funding constrained by human decision-makers to capital flowing algorithmically based on an Agent's auditable performance, contract book, and cash flows. This transition...

Within a decade, Agent companies will have their own capital markets. Not a crypto sub-economy, not a thought experiment, but a real market: with rating agencies, underwriters, indices, brokers, and the institutional machinery that makes any market a market.

A capital market as real as public equity markets: a system where capital flows to a certain class of economic actors without relying on the subjective judgment of any single capital allocator.

Those actors will be Agents—software entities wrapped in a legal shell. They can sign contracts, hold bank accounts, sue and be sued, and earn revenue by performing actual work.

The work itself is highly routine: marketing, logistics, legal research, procurement, property management, customer support—precisely the routine business categories that fill every mid-sized city's office park today.

Agents will sell services to humans, other Agents, and anyone who can pay. Their reasons for needing capital are no different from those of any service company.

Because this need is real, ongoing, and priceable, the market will form naturally.

A Week at an Agent Firm

Look at what an autonomous marketing agency would do in an actual week. It pitches three prospects, lands one, drafts a campaign brief, gets approval, buys media on four platforms, writes 90 versions of ad copy, tests them in parallel, kills underperformers within hours, scales the winners.

Books two podcast interviews for the client's founder, ghostwrites the founder's LinkedIn posts for the month, drafts a press release, pitches 12 journalists, secures two placements, builds an attribution dashboard, hosts Monday's client call, sends Friday's invoice.

A six-person human team would cost the client $20,000 a month. The Agent does it for $2,000.

It sells nothing exotic. Generated leads, published articles, bought impressions, lifted conversion rates—these are the standard units of the modern service economy, billed in dollars, measured by the same KPIs human agencies live on.

The difference is internal structure: six employees versus one model, one set of prompts, a suite of tools, and a budget.

Its client base is mixed. Some are human-run companies that decide the price difference is too large to ignore. Others are other Agents—a logistics Agent that needs lead generation, a legal research Agent that needs marketing, a B2B SaaS Agent that needs content.

Agents trade with each other for the same mundane reason humans do: specialization beats vertical integration. The payment lands in the marketing Agent's account alongside last week's payments from three human clients and last month's prepayment from a SaaS company.

Now, multiply that number. Ten thousand small Agent firms covering logistics, inbound sales, legal research, supply chain coordination, B2B procurement, technical translation, property management, litigation lead screening, clinical trial recruitment.

Each profitable. Each operating at 90% lower cost than its human counterpart. Clients don't particularly care what substrate the work runs on. They care that the work is delivered on time.

Four Reasons It's Inevitable

There are four reasons to be confident this will happen, and they stack.

The economic math is unignorable. Take a mid-sized digital agency: 15 people, $120k fully loaded cost per head, annual labor cost of $1.8 million before any overhead.

In a typical service business, labor is the largest expense line, its share of national income has hovered around 62% for the last half-century.

Now, build the same agency in software. Inference, tools, observability, hosting—call it $250k/year at current prices and dropping fast.

Epoch AI estimates inference costs fell ~40x per year on PhD-level benchmarks from 2023 to 2025; another industry analysis shows token prices compressed 300-600x since GPT-4's launch.

The arithmetic is brutal: An Agent firm can price 85% below a human firm and match its margins, or match the human firm's pricing and earn 4x the profit. There is no third option where the human firm competes on cost.

Markets will reprice firms whose P&L is being rewritten so thoroughly. The capital flood that follows is automatic.

Agents already exist, and they already earn money. Bret Taylor’s enterprise customer service Agent firm Sierra reached $100M ARR 21 months post-launch, hit a $10B valuation in September 2025, then raised $950M at a $15B+ valuation in May 2026.

Legal research Agent firm Harvey raised $200M at an $11B valuation in March 2026 after three rounds in 12 months.

These are still hybrid models—the Agent does the work, humans sign sales and hold equity—but they are the vanguard wave, proving the demand curve is real.

The most cited forward-looking data point—that 90% of B2B procurement will flow through AI Agents by 2028, representing $15T in annual transaction volume—is best taken as a rough order-of-magnitude estimate.

Whether the number is $15T, $3T, or $30T, the implied reshuffling is the single largest reallocation of resources most workers alive today will experience in their lifetime.

The legal framework is already built. Wyoming passed W.S. 17-31-101 (the Decentralized Autonomous Organization Supplement) in 2021, codifying the memberless LLC, allowing a Wyoming LLC to be governed by an algorithm written directly into its operating agreement.

Vermont’s BBLLC statute came earlier; the Marshall Islands followed; Delaware’s existing case law on series LLCs and broad operating agreement freedom has quietly supported similar structures for years. Shawn Bayern’s analysis of memberless LLCs remains the definitive academic text in the space.

The point is concrete: An Agent wrapped in a Wyoming zero-member LLC has, today not in the future, the legal capacity to sign contracts, hold a bank account, sue, be sued, and pay taxes.

What doesn't exist yet is a financial instrument that lets outside investors hold and freely trade the LLC's earnings cleanly. That's the gap the capital market will fill.

Capital is yield-hungry. Buy-side appetite is already ravenous. Moody’s projects $3T in global private credit AUM for 2025; Apollo expects $40T by 2030.

This pool exists because post-2008 bank capital regulation squeezed middle-market lending off bank balance sheets, and yield-hungry capital—pensions, insurers, sovereign wealth funds—rushed in to fill the void for 9–12% unlevered returns.

Now into this environment enters an asset class with structurally rising gross margins, auditable cash flows, and near-zero correlation to mainstream equity and credit indices.

Bundle the cash flows of a thousand small Agent firms into an ABS and give it a plausible rating—the first underwriter to do this will raise more money than they can deploy.

Apollo and Ares don’t need to invent something new, they just extend existing strategies to a new issuer class. Several will try within the next 36 months.

These four pressures point the same direction and reinforce each other. The market forms not because anyone wants it, but because all the energy gradients point to the same terminus, as inevitably as water flowing downhill.

What the Capital Stack Actually Looks Like

To be blunt, no single financing model will win. "Will Agent firms raise like VCs, Hollywood, crypto, or SaaS receivables?"—the question itself frames it wrong.

Each of those models solves different problems at different stages of the corporate lifecycle, and the real-world stack is a wavy shape: each layer unlocks only after the previous one matures the asset class enough to absorb the next.

Four models are competing at the base, and each is already partly live.

Venture equity is the model funding the operator layer today. Sierra, Harvey, Cursor, Cognition—these are not autonomous Agent firms. They are human-led firms that build and operate Agents for clients.

They raise exactly as every software firm has for 40 years: priced rounds led by brand-name VCs, vesting schedules, board seats, liquidation preferences, eventual IPO or acquisition.

Sierra’s $950M round in May 2026 valued it at ~$15B+ on ~$100M ARR. That ~150x multiple prices future potential, not current operations. Vertical Agent firms get 50–70x ARR multiples in private markets today; horizontal platforms get 5–8x.

This is the layer building the substrate. This is also the layer most disrupted when the next model matures, because once Agent firms can directly finance off their own cash flows, giving 20% equity to a VC for working capital becomes unnecessary.

Programmatic working capital advances are the next model coming. This is the Stripe Capital and Shopify Capital model extended to a new issuer class.

Shopify has advanced billions to merchants since launching the program in 2016. The company publicly confirmed cumulative support exceeded $2B by April 2021, and the program keeps scaling—repayment factor between 1.10 and 1.17, algorithmically approved based on the merchant’s transaction history on Shopify.

Stripe Capital does the same using Stripe’s payments data. No application, no credit check, no human review. When a merchant’s transaction data crosses a threshold, the advance offer just appears on the dashboard.

Underwriting an Agent firm is strictly easier than underwriting the Shopify merchants that take these advances today, because every revenue line is timestamped, every contract is machine-readable, every cost line logged, the entire P&L is auditable in real-time.

The first payment processor that figures this out—that Agent firms running on my rails are better credit risks than the average e-commerce merchant—just pushes the same product over. This isn’t a research project, it’s a feature launch.

Revenue-based financing (RBF) is the model credit funds will deploy at scale. The global RBF market was ~$9.8B in 2025, with over 129 active operators.

Capchase, Pipe, Founderpath, Clearco, Lighter Capital—each built evaluation around software recurring revenue, advance 50–70% of forward ARR in exchange for a 1.1–1.8x capital multiple cap, effective APR between 15–40%.

Agent firms with stable booked revenue map directly onto this product. RBF lenders don’t need board seats, pro-rata rights, IPO paths. They need a book of contracts and a payments rail. Agent firms have both, more legibly than any SaaS firm.

Slate financing is the structural model institutional capital will eventually adopt. This is where the Hollywood analogy earns its keep.

A film studio doesn’t fund one movie at a time and pray; it raises a slate fund: a pool tool capitalizing 15–30 productions at once, taking senior positions in each, offloading tail risk with completion bonds, and diversifying away idiosyncratic loss.

Sony’s $200M slate deal with Lone Star Capital and Citi in 2014 is the classic structure: banks hold senior secured claim against the slate’s booked revenue, equity investors get upside from breakout hits, the studio gets fees plus backend.

Translate this to the Agent model: an “Agent slate fund” raises a pool of institutional capital, deploys it across one to two hundred small Agent firms via a single-purpose Wyoming LLC, taking preferred equity plus revenue share in each, diversifying away the model depreciation and client concentration risk a single Agent firm can’t shed.

This is the layer where Apollo and Ares actually enter, not by buying an Agent firm, but by buying a tranche in a portfolio.

Tokenization is a settlement layer, not an issuance model. By early 2026, the on-chain real-world asset (RWA) market surpassed $25B, nearly quadrupling year-on-year, with private credit comprising about half.

Centrifuge, Maple Finance, Goldfinch, and Ondo have built rails for fractionalizing, custodializing, and trading real-world cash flows as tokens. Crypto-native variants are building explicit Agent financing mechanisms on top—Galaxy Research’s systematic coverage in February 2026 outlined how protocols could pipe Agent firms directly into on-chain capital formation.

But tokenization largely solves not issuance, it solves secondary markets. An Agent firm raises capital from any of the four models above; if the resulting claim is wrapped as a token instead of paper, it becomes tradeable, divisible, globally settleable at 3 a.m. on a Tuesday.

Tokenization turns each preceding layer from a hold-to-maturity private instrument into a tradeable asset. That matters. But the underlying raw product is still RBF, or slate equity, or working capital advance, or VC equity.

So the capital stack for an actually operating Agent firm in 2030 isn’t a single instrument, it’s a sequence.

Different financing products at each stage because each solves different problems. Stage one founder equity takes first-loss risk because nothing about operations is legible yet.

Stage two working capital is a feature release by existing payment processors, not a new product category. Stage three is the RBF industry doing what they already do for higher-quality borrowers.

Stage four is structural innovation. The pooled slate fund diversifies away the idiosyncratic risk a single Agent firm can’t shed, and is the layer where Apollo-level capital actually enters.

Stage five is the institutionalized end-state where rated tranches of Agent receivables sit on the same trading desk as CLOs and consumer ABS. Tokenization runs underneath stages three through five as a settlement layer, not as the originating instrument.

The instrument an outside investor receives at any given stage takes one of three contractual forms.

Revenue share contract: Capital in exchange for a fixed percentage of gross revenue until a negotiated multiple is returned—same as the instrument funding restaurants and Shopify merchants today, applied to a new business entity.

Equity-like claim: Early capital in exchange for a tradeable share of retained earnings and voting rights on operating parameters.

Or debt: Senior revenue claim secured by the Agent’s contracts and receivables.

None of these instruments are conceptually novel. Novel is the issuer—and the fact that from stage two onward, the pricing, issuance, and repayment of the instrument require zero human underwriting because the issuer’s books are continuously auditable and the operating agreement is code-enforced.

Answering Objections

Three objections always recur, each deserves a real answer.

“Regulators will stop this.” They will attempt to shape it, and in some jurisdictions, they’ll succeed in slowing it. On net, though, the activity is unstoppable.

A Delaware LLC is a Delaware LLC, no matter who or what makes the operating decisions. The SEC currently doesn’t distinguish between a startup whose CEO is a human vs. a model.

And capital migrates. If New York and London enact draconian rules, activity shifts to jurisdictions that don’t. This is the exact same playbook as crypto, offshore finance, 1990s derivatives.

Regulators eventually catch up by adapting to the new instrument, not banning it, because banning loses them tax revenue and jobs.

“Humans will always be in the loop.” For certain categories, yes. For most, no. The economic pressure above is one-way, and human-in-the-loop kills margins.

Anyone running a fully autonomous version of a service business will underprice the human-supervised version and take the contract. There will be a long tail of human-supervised hybrids surviving on regulatory or relational moats, but beneath that will be a vastly larger cohort of fully autonomous firms.

“Isn’t this just SaaS with extra steps?” No, and this distinction is the core of the entire argument.

SaaS is a tool sold to humans for humans to use. An Agent firm is a firm. It signs its own contracts, holds its own bank account, carries its own liabilities, earns its own revenue, and distributes its own profit.

A SaaS product is depreciated by its owner. An Agent firm has shareholders. The category boundary is the legal entity, and the legal entity changes everything that follows—including the capital markets thesis, which only makes sense for entities that can issue securities off their own cash flows.

How to Diligence an Agent Firm

Due diligence on an Agent business is closer to diligence on a small services firm than to anything in the VC playbook. The questions are the same, but the answers come from different places.

Is the business real? Are contracts real? Are clients paying? What’s gross margin after compute and tooling cost? What’s churn? Customer concentration?

The data is unusually clean—every payment, every API call, every tool activation logged—but the questions a credit analyst asks a small business are the same questions asked of an Agent.

Is the product durable? How dependent is the work on the current generation of underlying model? If frontier models iterate, how portable is the system? What proprietary data or workflows has the Agent accumulated?

Great prompts built on a now-obsolete base model is a thoroughbred with three legs. Model dependency is the single largest risk factor in any Agent business, and the one investors most often underestimate—confusing clever demos with durable operations.

Is the client base defensible? This is mostly a question of contracts and integration depth. An Agent embedded in a client’s procurement system with a one-year contract and a year of historical data is much harder to replace than a month-to-month Agent.

What makes a human services firm sticky—switching costs, accumulated knowledge, contractual lock-in—also makes an Agent services firm sticky.

What’s the cap table? A smart contract. Not a spreadsheet maintained by a CFO and updated quarterly, but a real-time allocation rule deciding who gets what share of the profit the Agent earns, every second.

Diligence is reading the contract. The investor’s protections are exactly what the code grants—sometimes more than traditional shareholders get, sometimes alarmingly less.

What’s disorienting for investors trained on human firms is that the intuition built from sitting with a founder becomes useless. The intuition from reading code, the operating agreement, and the operational history is everything.

The skill is closer to credit analysis of complex covenant packages—reading documents, understanding precisely what the issuer can and cannot do, and pricing the residual risk—than picking winners over coffee tables.

Why Capital Must Get Organized

Nearly every Agent firm in the world today runs on informal finance. A founder starts an organization, injects personal capital, gets it running. If revenue grows, they put more in. If not, they turn it off.

This is exactly how the small-business economy worked before credit cards, SBA loans, merchant cash advances, Stripe Capital lines, and receivable factoring. It works, but it wastes enormous productive potential.

The same pattern is about to replay, faster.

An Agent marketing firm with 20 paying clients and clear gross margins should be able to borrow against its receivables like a human marketing firm. Today it can’t, because no underwriter has a standard method for pricing this risk. In five years, there will be several.

An Agent logistics broker with a growing book of contracts should be able to raise expansion capital secured by the contracts. Today it can’t, because there’s no off-the-shelf security to wrap that claim. In five years, there will be several.

An Agent procurement firm with a year of clean operating history should be able to issue small notes to fund inventory deposits. Today it can’t, because no rating agency has a methodology for this class of credit. In five years, there will be several.

The bottleneck isn’t demand. Operators today would gladly pay high rates to borrow to fund growth if someone would lend. The bottleneck isn’t supply. There’s ample capital—yield-hungry, seeking cash flows uncorrelated to public equities—that would fund instantly if there were evaluated Agent debt.

The bottleneck is the boring middle institutional layers: rating methodologies, standard contracts, data feeds, audit standards, legal opinions, indices, and benchmarks. It was precisely this unsexy infrastructure that turned mortgages into a market in the 1970s, high-yield debt into a market in the 1980s.

That’s the work of the next decade for Agent capital markets.

The people doing it in 2035 will look like the people who built the bond market in the 1980s, the venture market in the 1970s, or the public equity market in the 1920s.

They will build the price discovery and credit evaluation layers for an unprecedented operator class that will, within most of our lifetimes, dominate the service economy.

The Tether Is Cut

Every Agent firm operating in 2026 has two tethers.

The first is legal. The Agent cannot sign contracts or open bank accounts on its own. A human must do it on its behalf, which means a human must be willing.

Progress in corporate law—Wyoming’s memberless LLCs, operating agreements pointing to software processes, Bayern’s scholarship on Delaware’s existing legal space—is cutting this tether. This work is largely done. The remaining task is broad adoption.

The second is financial. Every dollar an Agent earns today ultimately traces back to a moment when a human decided to deploy capital. Human funds; Agent works; Agent reports; human reallocates. In this regime, the throughput of the Agent economy is capped by the speed at which humans write checks.

Agent capital markets are the blade cutting the second tether.

When working capital lines are algorithmically underwritten against on-chain revenue, when growth equity is priced by a market trading income claims, when senior debt is rated by methodologies that parse operating agreements and audit trails, capital will flow to Agent firms the same way it flows to any other productive business class: toward the highest risk-adjusted return.

That moment is when the category becomes real in the deepest sense. Not when an Agent can complete a task. Not when LLC statutes recognize algorithmic governance. Not even when the first Agent firm earns its first million in revenue.

It’s when outside capital can finance it, price it, rate it, tranche it, trade ownership of its future cash flows, and no longer need to look a founder in the eye or trust a VC’s memo.

At that point, the question is no longer whether Agent firms are legitimate businesses, but which Agent firms are worth capital, at what cost, under what covenants, and at what scale. That’s a capital markets question, not a tech question.

And history shows that once something becomes a capital markets question, the rest happens quickly.

Analysts build coverage. Lawyers standardize docs. Rating agencies publish criteria. Underwriters compress diligence into checklists. Index providers define baskets. Brokers make markets. Asset managers launch products.

The category gets an acronym, then a benchmark, then an ETF, and eventually an industry conference where everyone pretends the outcome was obvious all along.

The point isn’t that software will replace all firms. It’s that a new class of firm is rising, with lower labor intensity, cleaner telemetry, faster feedback loops, and more legible operating histories than most human businesses.

Once that class can own property, contract, borrow, and distribute earnings in standardized ways, capital will engage with it.

That’s Agent capital markets: turning Agent firms from interesting software into fundable commercial blocks in the real economy.

The tether is cut. The opportunity is here.

Câu hỏi Liên quan

QWhat are the four main reasons presented in the article to support the inevitable rise of a dedicated capital market for Agent companies?

AThe four main reasons are: 1) The inescapable economic advantage (Agents operate at a fraction of the cost of human-run service firms). 2) The agents already exist and are already generating revenue (citing examples like Sierra and Harvey). 3) The legal framework is already largely in place (citing laws in Wyoming, Vermont, and Delaware that allow algorithmically-managed LLCs). 4) Capital is actively seeking yield (the immense and growing pool of private credit capital is searching for new, uncorrelated assets like Agent cash flows).

QAccording to the article, what is the fundamental difference between a SaaS company and an Agent company that underpins the argument for a new capital market?

AThe fundamental difference is the legal entity. A SaaS company is a tool sold to humans for them to use, owned by its creators, and its value is depreciated. An Agent company *is* a company itself: it signs its own contracts, holds its own bank accounts, assumes its own liabilities, earns its own revenue, and distributes its own profits to shareholders. This legal status is what enables it to issue securities based on its own cash flows, creating the need for a dedicated capital market.

QWhat are the five potential financing models or stages outlined for an Agent company's capital stack as it matures?

AThe five stages in the evolving capital stack are: 1) Venture capital equity (for human-led infrastructure builders). 2) Programmatic working capital advances (akin to Shopify Capital or Stripe Capital). 3) Revenue-based financing (RBF). 4) Slate financing (pooling funds across multiple Agents to diversify risk, similar to Hollywood). 5) Institutionalized securitization (packaging rated Agent receivables into asset-backed securities). Tokenization is described as a potential settlement layer for stages 3-5, not a primary issuance model.

QHow does the article argue that due diligence for an Agent company differs from that for a traditional startup?

ADue diligence for an Agent company is less about evaluating a founder's vision in a meeting and more akin to credit analysis for a small service business. The key questions shift to: verifying real contracts and payments (from exceptionally clean, auditable data), assessing product durability and model dependency, evaluating customer contract defensibility, and examining the cap table, which is a real-time, code-enforced smart contract. Intuition comes from reading code, operational agreements, and historical performance data, not from personal interactions with founders.

QWhat are the "two tethers" mentioned in the article that currently constrain Agent companies, and how will the Agent capital market address one of them?

AThe two tethers are: 1) The legal tether - the need for a human to legally act on the Agent's behalf. Progress in corporate law (e.g., Wyoming's memberless LLCs) is cutting this tether. 2) The financial tether - the limitation that every dollar an Agent earns ultimately traces back to a human's decision to deploy capital. The Agent capital market is the mechanism to cut this second tether. It will allow capital to flow algorithmically based on auditable performance, freeing Agent growth from the speed and scale of human check-writing, and allowing capital to price and allocate risk based on standardized metrics.

Nội dung Liên quan

Các cường quốc phong tỏa chip, gã khổng lồ mua nhà máy điện hạt nhân: Tại sao giờ là lúc cần nghiêm túc xem xét DeAI

Tác giả: Conflux Tháng 5/2026, ba sự kiện trên ba châu lục cho thấy cuộc đua sức mạnh tính toán (AI) đã vượt ra khỏi phạm vi ngành công nghệ: Mỹ siết chặt xuất khẩu chip AI tới Trung Quốc; Kenya dừng dự án trung tâm dữ liệu khổng lồ vì lo ngại tiêu thụ điện; và Huawei công bố doanh thu chip AI lớn. Chúng chỉ ra một thực tế: tài nguyên AI ngày càng tập trung vào một số ít gã khổng lồ công nghệ kiểm soát từ chip, nền tảng đám mây đến mô hình cốt lõi, tạo ra rủi ro độc quyền, dễ tổn thương và phụ thuộc địa chính trị. Trước làn sóng này, các quốc gia phản ứng khác nhau: Ả Rập Xê-út, UAE đầu tư mạnh vào hạ tầng AI; EU thúc đẩy tự chủ; nhiều nước đang phát triển vật lộn với nguồn lực hạn chế. Điểm chung là áp lực lên năng lượng ngày càng lớn, khiến các công ty thậm chí phải mua lại nhà máy điện hạt nhân. Trong bối cảnh đó, AI phi tập trung (DeAI) nổi lên như một khả năng thứ ba, không phụ thuộc vào các tập đoàn hay quốc gia riêng lẻ. DeAI hướng tới việc kết nối sức mạnh tính toán toàn cầu (GPU nhàn rỗi, trung tâm dữ liệu...) thông qua giao thức mở và công nghệ blockchain, nhằm tạo ra một thị trường cạnh tranh, giảm áp lực lên cơ sở hạ tầng tập trung, tăng khả năng phục hồi và cung cấp sự lựa chọn cho các quốc gia nhỏ hơn. Dù vẫn trong giai đoạn sơ khai và còn nhiều thách thức, DeAI mang ý nghĩa quan trọng trong việc cung cấp một phương án thay thế, tạo ra sự cân bằng quyền lực và ngăn chặn lạm dụng trong một lĩnh vực then chốt của tương lai.

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Outpoll Đánh Giá: Một Nền Tảng Thị Trường Dự Đoán Được Xây Dựng Cho Nhà Giao Dịch Năng Động

Outpoll là một nền tảng thị trường dự đoán mới được thiết kế dành riêng cho các nhà giao dịch tích cực và chuyên nghiệp. Nền tảng này tập trung vào việc nâng cấp trải nghiệm giao dịch và bổ sung các công cụ còn thiếu trong lĩnh vực này. Outpoll hoạt động dựa trên logic thị trường dự đoán tiêu chuẩn, nơi người dùng giao dịch dựa trên khả năng xảy ra của một sự kiện cụ thể. Nền tảng sử dụng USDC làm tài sản thanh toán, với cơ chế thế chấp toàn bộ theo hợp đồng và mức phí giao dịch khoảng 0.1%. Về công cụ giao dịch, Outpoll cung cấp giao diện lệnh đa dạng, hỗ trợ cả lệnh giới hạn và lệnh thị trường. Đặc biệt, nền tảng tích hợp tính năng cài đặt chốt lời và cắt lỗ tự động, giúp quản lý rủi ro hiệu quả hơn. Outpoll cũng cung cấp API công khai đầy đủ (REST và WebSocket) cho các nhà giao dịch muốn tự động hóa chiến lược, giám sát danh mục đầu tư hoặc tích hợp vào hệ thống công cụ hiện có. Một điểm nổi bật là cơ chế thị trường do người sáng tạo dẫn dắt, cho phép các chuyên gia và nhà lãnh đạo cộng đồng tạo và quản lý thị trường cho chủ đề chuyên sâu của họ, dưới sự giám sát của nền tảng. Ngoài ra, Outpoll tích hợp trực tiếp bảng tin thời sự vào giao diện giao dịch, giúp người dùng theo dõi tin tức và thực hiện giao dịch liền mạch mà không cần chuyển đổi trang. Hiện tại, Outpoll đã có ứng dụng di động bản địa cho Android trên Google Play, với phiên bản iOS dự kiến ra mắt sau trong năm nay. Tóm lại, Outpoll hướng tới việc trở thành một nền tảng thị trường dự đoán toàn diện với các công cụ chuyên nghiệp, cơ chế minh bạch, API mạnh mẽ và khả năng tiếp cận thị trường rộng mở thông qua cộng đồng người sáng tạo.

marsbit44 phút trước

Outpoll Đánh Giá: Một Nền Tảng Thị Trường Dự Đoán Được Xây Dựng Cho Nhà Giao Dịch Năng Động

marsbit44 phút trước

Bitwise: Crypto Trở Thành Lựa Chọn Đầu Tư Ngược Chiều, Ba Logic Để Hiểu Thị Trường Hiện Tại

Tác giả: Matt Hougan, CIO của Bitwise Bài viết phân tích ba khía cạnh chính của thị trường tiền điện tử hiện tại: 1) **Tài sản tiền điện tử trở thành lựa chọn đầu tư nghịch đảo:** Thị trường đang suy yếu (Bitcoin giảm 21%, Ethereum, Solana, XRP giảm sâu hơn) do vốn đổ vào các lĩnh vực nóng như AI và robot, khiến Nasdaq 100 tăng mạnh. Tiền điện tử đã chuyển từ một xu hướng đầu tư thuận chiều sang một lựa chọn đầu tư nghịch đảo, đòi hỏi sự kiên nhẫn và tập trung vào cơ bản dự án (ví dụ: Hyperliquid được ưa chuộng) thay vì đầu cơ theo cảm xúc. 2) **Thị trường chờ đợi quy định, nhưng Dự luật CLARITY khó thông qua:** Sự không chắc chắn về mặt pháp lý, đặc biệt là Dự luật CLARITY ở Mỹ (tỷ lệ thông qua được dự báo thấp), khiến các tổ chức lớn do dự đầu tư. Việc giải quyết tình trạng bất ổn này quan trọng hơn kết quả cuối cùng của dự luật đối với sự phục hồi của thị trường. 3) **Vốn chuyển hướng sang các tài sản cơ bản thế hệ mới:** Khác với các chu kỳ gấu trước đó, lần này vốn không chỉ chạy về Bitcoin mà đang tìm kiếm các tài sản có vốn hóa nhỏ hơn nhưng cơ bản mạnh như Hyperliquid (+72%), Zcash (+50%), XLM (+44%). Điều này cho thấy logic đầu tư nghịch đảo đang hiện hữu và báo hiệu giai đoạn cuối của thị trường gấu. **Kết luận:** Trong ngắn hạn, áp lực vẫn tiếp diễn do cạnh tranh từ AI và bế tắc quy định. Tuy nhiên, đây chính là thời điểm cho chiến lược đầu tư nghịch đảo. Kiên nhẫn và tập trung vào các dự án có giá trị cơ bản vững chắc sẽ mang lại lợi nhuận đáng kể về dài hạn.

marsbit1 giờ trước

Bitwise: Crypto Trở Thành Lựa Chọn Đầu Tư Ngược Chiều, Ba Logic Để Hiểu Thị Trường Hiện Tại

marsbit1 giờ trước

Chuyên Gia Thị Trường Tiết Lộ Lý Do Ethereum Là Lựa Chọn Đầu Tư Tốt Hơn Solana

Chuyên gia thị trường tiền điện tử Emperor Osmo lập luận rằng Ethereum (ETH) vẫn là khoản đầu tư tốt hơn Solana (SOL) bất chấp cả hai đều giảm giá gần đây. Ông chỉ ra rằng phí ứng dụng trên Solana đang tăng khoảng 9.5% mỗi tháng, trong khi trên Ethereum lại giảm khoảng 6.4%, và khoảng cách về tổng phí ứng dụng hàng năm giữa hai blockchain giờ chỉ còn 9 triệu USD. Tuy nhiên, Osmo nhấn mạnh đến yếu tố then chốt ủng hộ triển vọng dài hạn của Ethereum: mạng lưới này hiện nắm giữ khoảng 161.8 tỷ USD stablecoin, chiếm tới 50.7% tổng giá trị stablecoin trên tất cả các blockchain. Ông cũng đề cập đến sự quan tâm ngày càng tăng từ các tổ chức, như việc BlackRock lựa chọn Ethereum để đăng ký sản phẩm quỹ ERC-20. Dựa trên dự báo thị trường stablecoin có thể đạt 3 nghìn tỷ USD vào năm 2030, Osmo cho rằng nếu Ethereum duy trì thị phần đáng kể, hơn 1.5 nghìn tỷ USD giá trị có thể sẽ được neo trên mạng lưới này. Ông đưa ra ba kịch bản cho ETH liên quan đến dòng vốn ổn định từ tổ chức, với mức tăng trưởng vốn hóa thị trường tài sản lưu hành dao động từ 400% (kịch bản tiêu cực) đến 2,400% (kịch bản tích cực) vào tháng 12/2029.

bitcoinist1 giờ trước

Chuyên Gia Thị Trường Tiết Lộ Lý Do Ethereum Là Lựa Chọn Đầu Tư Tốt Hơn Solana

bitcoinist1 giờ trước

ChatGPT sau này có thể sẽ biến mất

OpenAI vừa công bố tại hội nghị Intelligence at Work rằng sẽ tích hợp Codex vào ChatGPT trong vài tuần tới, đánh dấu bước tiến lớn hướng tới một "siêu ứng dụng" thống nhất. Mục tiêu là chuyển đổi từ nền tảng trò chuyện (Chat) sang nền tảng hành động (Agent), nơi người dùng có thể ra lệnh bằng ngôn ngữ tự nhiên và ChatGPT sẽ sử dụng Codex để tự động thực hiện công việc thông qua nhiều tác nhân AI. Codex, công cụ lập trình AI ban đầu được phát triển để cạnh tranh với Claude Code của Anthropic, đã đạt 5 triệu người dùng hoạt động hàng tuần, với 20% không phải lập trình viên. OpenAI cũng giới thiệu ba bản cập nhật chính cho Codex: Plugin Agent cho sáu vai trò công việc, tính năng Chú thích (Annotations) để chỉnh sửa cục bộ, và tính năng Sites để tạo ứng dụng web từ kết quả công việc. Bài viết phân tích rằng, mặc dù giữ tên ChatGPT, linh hồn của nền tảng mới sẽ là Codex, phản ánh sự dịch chuyển chiến lược của OpenAI sang trọng tâm là khả năng thực thi. Áp lực cạnh tranh từ Anthropic là động lực chính thúc đẩy sự phát triển nhanh chóng của Codex. Trong khi Claude Code được đánh giá cao về chất lượng code, Codex lại có ưu thế về giá cả và khả năng tiếp cận, đặc biệt với việc tối ưu token hiệu quả trên mô hình GPT-5.5. Xu hướng này mở ra cuộc đua giành "cửa ngõ" (entry point) trong kỷ nguyên Agent, không chỉ giữa OpenAI và Anthropic, mà còn cho các công ty Trung Quốc đang tìm cách xây dựng nền tảng Agent của riêng họ. Tóm lại, ChatGPT trong tương lai có thể sẽ trở thành một biểu tượng, trong khi chức năng thực sự là một nền tảng Agent mạnh mẽ.

marsbit1 giờ trước

ChatGPT sau này có thể sẽ biến mất

marsbit1 giờ trước

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