一个新项目或协议应该关注什么?

区块创新Block ChangePublished on 2024-01-30Last updated on 2024-01-30

Abstract

让我们来看看 Curve(CRV)的结构。 实质上,Curve 为 LP 提供激励,通过他们的代币经济学鼓励参与者参与治理。而对于 Convex 来说,这里的终极目标是获得尽可能多的 veCRV 以最大化 CRV 奖励。 在明确设定目标之后,项目的创始人应该进一步研究代币的实际价值主张,持有该代币的参与者可以从中获得什么价值?比如: 质押 治理 价值存储 还有更多。如今,看到创始人提出由多种价值主张组成的代币是很常见的。当然,这可能导致对代币的更高需求。 一个完美的例子是 GMX,该代币具有多个价值主张,如治理(启发参与者的真实偏好的能力)、认领(将托管的 GMX 在一段时间内转换为 GMX 的能力)和持有(接收协议收入)。 随着这些价值主张,还有功能参数,这与决定代币的文字功能的变量有关,最简单的例子是转移或销毁。对于团队来说,确保代币的功能参数与其价值主张不冲突是绝对关键的。例如,一个用于价值转移的代币的目标和价值主张应该具有确保其可替代性的功能。以下是代币的一些功能参数: 可转让性(可转让 + 不可转让):分别是 GMX 和 esGMX。 可销毁性(可销毁 + 不可销毁):分别是 BNB 和 SBTs。 可替代性(可替代 + 不可替代):分别是 ERC20 和 ERC721(NFT)。 汇率(浮动 + 固定):分别是 MKR 和 DAI。 有时,团队故意决定一个代币被分配了冲突的价值主张或功能。在这种情况下,代币可以被分为两种或更多种类型。AXS 的著名案例就是一个最好的例子,从最初的单代币模型转变为多代币模型。 最初,AXS 有 3 个价值属性:价值转移、治理和持有。这里的冲突源于参与者如果决定在游戏内进行 AXS 的价值转移,就意味着放弃治理和持有的权益,这对游戏经济造成了问题。为了解决这个问题,他们发布了一个「新」代币 SLP,然后成为游戏内的首选价值转移工具。你可能还记得 STEPN 的 GMT 和 GST 中的同样的双系统。 然而,实施双代币系统可能使代币经济学设计过于复杂,并且有时考虑将外部代币作为辅助代币可能是重要的,以确保更顺畅的交互。一个典型的例子是 ARB,主要用于治理。 为了确保更顺畅的交互,ARB 使用 ETH 作为支付交易费用的手段,因为发生在 L2 上的交易被捆绑在一起并发送到 L1 状态。如果没有引入此外部代币(ETH)作为支付交易费用的手段,将发生以下情况:ARB 用于支付交易费用(gas 费),运营商然后必须将 ARB 兑换成 ETH 以在 L1 上进行验证并在进一步的 gas 费中损失,为 ARB 的增长创造了一种矛盾。 在上述部分,我已经介绍了代币经济学的一般动态和团队应该考虑的各种推动因素,现在让我们来看看代币供应。因为这直接影响代币价格(这是 degen 们想要的)。代币供应的结构如下: 最大供应量 分配百分比(销售、投资者、团队、市场营销、国库等) 分配的分布:分配给初始、归属和奖励发行。 最大供应量很重要,因为这决定了团队是否能够发行代币的最大上限,未限制的代币可能没有很好的价格分布。这不直接影响价格,但是影响发行速率的因素,以及代币是否通货紧缩或通货膨胀是影响价格的因素。 对于有限的最大供应量,例如 CRV(30 亿代币),价格可以上涨。因为随着网络的增长,对代币的需求增加,形成了一个供应有限的高需求区域,这种类型的最大供应的问题在于,如果代币分发不迅速,未来的新贡献者也很难提供激励。 另一方面,拥有无限最大供应可以避免关于未来激励耗尽的问题,当然...

让我们来看看 Curve(CRV)的结构。

实质上,Curve 为 LP 提供激励,通过他们的代币经济学鼓励参与者参与治理。而对于 Convex 来说,这里的终极目标是获得尽可能多的 veCRV 以最大化 CRV 奖励。

在明确设定目标之后,项目的创始人应该进一步研究代币的实际价值主张,持有该代币的参与者可以从中获得什么价值?比如:

质押

治理

价值存储

还有更多。如今,看到创始人提出由多种价值主张组成的代币是很常见的。当然,这可能导致对代币的更高需求。

一个完美的例子是 GMX,该代币具有多个价值主张,如治理(启发参与者的真实偏好的能力)、认领(将托管的 GMX 在一段时间内转换为 GMX 的能力)和持有(接收协议收入)。

随着这些价值主张,还有功能参数,这与决定代币的文字功能的变量有关,最简单的例子是转移或销毁。对于团队来说,确保代币的功能参数与其价值主张不冲突是绝对关键的。例如,一个用于价值转移的代币的目标和价值主张应该具有确保其可替代性的功能。以下是代币的一些功能参数:

可转让性(可转让 + 不可转让):分别是 GMX 和 esGMX。

可销毁性(可销毁 + 不可销毁):分别是 BNB 和 SBTs。

可替代性(可替代 + 不可替代):分别是 ERC20 和 ERC721(NFT)。

汇率(浮动 + 固定):分别是 MKR 和 DAI。

有时,团队故意决定一个代币被分配了冲突的价值主张或功能。在这种情况下,代币可以被分为两种或更多种类型。AXS 的著名案例就是一个最好的例子,从最初的单代币模型转变为多代币模型。

最初,AXS 有 3 个价值属性:价值转移、治理和持有。这里的冲突源于参与者如果决定在游戏内进行 AXS 的价值转移,就意味着放弃治理和持有的权益,这对游戏经济造成了问题。为了解决这个问题,他们发布了一个「新」代币 SLP,然后成为游戏内的首选价值转移工具。你可能还记得 STEPN 的 GMT 和 GST 中的同样的双系统。

然而,实施双代币系统可能使代币经济学设计过于复杂,并且有时考虑将外部代币作为辅助代币可能是重要的,以确保更顺畅的交互。一个典型的例子是 ARB,主要用于治理。

为了确保更顺畅的交互,ARB 使用 ETH 作为支付交易费用的手段,因为发生在 L2 上的交易被捆绑在一起并发送到 L1 状态。如果没有引入此外部代币(ETH)作为支付交易费用的手段,将发生以下情况:ARB 用于支付交易费用(gas 费),运营商然后必须将 ARB 兑换成 ETH 以在 L1 上进行验证并在进一步的 gas 费中损失,为 ARB 的增长创造了一种矛盾。

在上述部分,我已经介绍了代币经济学的一般动态和团队应该考虑的各种推动因素,现在让我们来看看代币供应。因为这直接影响代币价格(这是 degen 们想要的)。代币供应的结构如下:

最大供应量

分配百分比(销售、投资者、团队、市场营销、国库等)

分配的分布:分配给初始、归属和奖励发行。

最大供应量很重要,因为这决定了团队是否能够发行代币的最大上限,未限制的代币可能没有很好的价格分布。这不直接影响价格,但是影响发行速率的因素,以及代币是否通货紧缩或通货膨胀是影响价格的因素。

对于有限的最大供应量,例如 CRV(30 亿代币),价格可以上涨。因为随着网络的增长,对代币的需求增加,形成了一个供应有限的高需求区域,这种类型的最大供应的问题在于,如果代币分发不迅速,未来的新贡献者也很难提供激励。

另一方面,拥有无限最大供应可以避免关于未来激励耗尽的问题,当然,这里的缺点是从长远来看可能会有代币价格下降,因为实质上存在无限供应,除非使用外部模型减少流通(例如:质押、销毁等),否则长期内只能存在下降趋势,而不管其增长如何。

在分配方面,通常是基于最大供应的百分比,实际上确定了每个类别应该分配的最大供应的百分比。主要的类别有:团队(包括创始人、开发者、市场营销等,实际上是负责建设项目的个人),投资者(参与早期/种子/私募轮的人员),国库(运营成本,如研发、储备等),社区(空投、LP 奖励、挖矿奖励等),公开销售(ICO、IDO、IEO、LBP 等)和营销(包括顾问、意见领袖、代理等)。

这些是项目考虑的一些关键要素,然而这些要素对每个项目来说基本上是独特的,可以根据它们的「战略」简化或进一步细分类别。

值得注意的是,在 2020-21 年 DeFi 崛起时,团队意识到通过允许更高奖励给他们的社区,或通过空投增加初始持有者的浮动量,可能会导致网络增长和可持续代币经济的繁荣。

最后,分发。初始供应是在「启动」时立即释放到开放市场的初始浮动量,或者有些人称之为 TGE。分配到这个类别的分配通常是国库、公开销售和我们到处都能看到的臭名昭著的空投的一部分百分比。

对于待解锁的代币,这些通常会被锁定 x 个月/年,通常适用于投资者、国库、团队代币,他们可以自行决定持续时间和何时开始解锁,通常解锁防止大规模的代币抛售,特别是因为这个部分的参与者通常是以低于上市价的估值购买的投资者。

那么,这一切为什么重要呢?

简单来说,代币需求和价值捕获意味着理论上市场参与者应该通过持有代币来获得价值。

Trending Cryptos

Related Reads

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

In three days, Google lost two AI legends. On June 18, Noam Shazeer, co-author of the seminal "Attention is All You Need" paper and Gemini co-lead, left for OpenAI. Just 48 hours later, John Jumper, 2024 Nobel laureate and AlphaFold lead, departed DeepMind for Anthropic. This follows Andrej Karpathy joining Anthropic in May. These moves highlight a structural trend: top AI talent is concentrating at mission-driven, pre-IPO firms like OpenAI and Anthropic, while Google becomes a primary source. The exodus stems from a core mission mismatch. Google's ad-centric model often subordinates AI research to product and revenue goals, creating friction for pioneers like Shazeer, who returned in 2024 only to leave again. In contrast, OpenAI and Anthropic offer singular focus on pushing AI boundaries, whether towards AGI or safety-aligned models, which deeply appeals to top researchers like Jumper. Financial incentives amplify the pull. With both OpenAI and Anthropic nearing IPO, employees stand to gain immensely from equity, an upside Google's mature stock cannot match. Furthermore, the 2023 merger of Google Brain and DeepMind, intended to consolidate strength, has instead created cultural tension and slowed the path from research to product, as evidenced by Gemini's pace. This talent redistribution is reshaping the AI landscape. While Google retains vast data and compute resources, its true crisis is the quiet, continuous loss of the people who define the field's future. The real moat in AI is not infrastructure, but the concentration of brilliant minds—a battle Google is currently losing.

marsbit11m ago

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

marsbit11m ago

Behind the AI Report Card, Lies a Chinese 'Exam Setter'

Beyond the familiar performance charts like MMLU-Pro and MMMU, which major AI models strive to ace, stands a key "examiner": Chinese-Canadian researcher Wenhu Chen. An assistant professor at the University of Waterloo and founder of TIGERLab, Chen addresses the crucial need for more rigorous AI evaluation. As models like GPT-4 began scoring near-perfect results on older benchmarks like MMLU, it became difficult to distinguish their true capabilities. In response, Chen introduced MMLU-Pro in 2024, featuring harder, more reasoning-focused questions with more answer choices, successfully reintroducing meaningful performance gaps. His work extends to multi-modal evaluation with MMMU and its enhanced version, MMMU-Pro. These benchmarks test a model's ability to understand and reason with complex information from images, charts, and text across diverse academic subjects, exposing the significant challenges even top models face in genuine comprehension. Chen's background in complex QA, table reasoning, and his experience at Google DeepMind on projects like Gemini inform his approach. He understands that effective benchmarks must anticipate how models might "cheat" by memorizing data or avoiding visual analysis. His lab also actively researches video understanding and generation models (e.g., UniVideo, Vamba), ensuring his evaluation work is grounded in practical model-building challenges. Now at Meta's Super Intelligence Lab, Chen continues his focus on multi-modal data and evaluation, representing the deep yet often unseen contributions of Chinese talent in shaping the fundamental tools of the AI industry.

marsbit23m ago

Behind the AI Report Card, Lies a Chinese 'Exam Setter'

marsbit23m ago

Alliance Co-founder's Letter to Entrepreneurs: Written at the Moment Cursor Sold for $600 Billion

Alliance Co-founder's Letter to Entrepreneurs: On Cursor's $60 Billion Sale Many aspiring founders see massive exits like Cursor's $60B sale and wonder why they can't achieve the same, often concluding opportunities are exhausted. But great companies aren't built in obvious, crowded spaces. Cursor, like Stripe, Figma, and Shopify before it, started with a non-consensus belief about the future. Before ChatGPT, they believed AI would transform knowledge work. They focused on a genuinely exciting domain, became their own customer, and obsessed over power users. Their journey involved years of "glass-chewing" effort before the market was ready. The pattern is consistent: identify a long-term technological shift, find a missed entry point, and execute for years before the trend becomes obvious. First-generation products (PayPal, Adobe, Amazon) prove a market exists. Second-generation winners (Stripe, Figma, Shopify) rebuild that market around new insights, technology, or changing customer behaviors. Founders must identify their phase in the cycle. Early entrants like Coinbase or Cursor focus on making new technology usable for power users. Later entrants find the "yin" to the established "yang"—the blind spots incumbents miss as they grow distant from individual users. The key is deep market immersion. Use every product in your space. Talk to users. Build an audience. Stop looking for ideas and start *seeing* them everywhere. Then, choose one. The idea must offer a 10x improvement or solve a "hair-on-fire" pain point—something severe enough that users are already crafting workarounds. When building, avoid feature bloat. Ask: why would someone switch? Great startups rarely force new behaviors; they improve familiar workflows with drastically lower friction (e.g., Cursor forked VS Code instead of creating a new editor). Distribution is the underestimated moat. Before product-market fit, achieve distribution-market fit. How do customers discover new tools? Founders like those at Airbnb, Stripe, and Cursor did unscalable, manual work to recruit early users. The final, unteachable ingredient is resilience. Cursor built for years pre-market, faced rejection, and persisted. So did Airbnb, Nvidia, and Rain (which launched post-FTX collapse). The lesson isn't that these founders were smarter, but that they stayed in the game long enough for their insights to compound. Framework: Spot technological cycles. Cultivate unique insight. Obsess over your market. Talk to customers. Find a hair-on-fire problem. Build the simplest wedge. Win your distribution channel. Above all, don't quit when it gets hard. Most people won't do these things consistently. The few who do build the next generation of great companies. Go build.

marsbit27m ago

Alliance Co-founder's Letter to Entrepreneurs: Written at the Moment Cursor Sold for $600 Billion

marsbit27m ago

Weekly Editor's Picks (0613-0619)

Weekly Editor's Picks (0613-0619): Market Insights & Analysis This weekly digest curates in-depth analysis often lost in the information flow, focusing on key insights across macro trends, investment, and technology. **Macro & Geopolitics:** With the Strait of Hormuz reopening and military conflict shifting to negotiation, markets are pivoting from "war shock" to "supply restoration." Trades include shorting crude risk premiums, longing airlines/tourism, Asian energy importers, and bond duration, while shorting inflation expectations. LNG, fertilizer, and chemical chains are also being repriced. **Investment & VC:** Ray Dalio advises against betting on concentrated AI giants dominating indices, advocating for diversified portfolios of high-quality, low-correlation assets instead. Analysis covers the 4-year crypto cycle, predicting the core surviving product by 2029 will be asset trading markets. Current BTC metrics suggest a potential bottoming zone, presenting a patient accumulation window. SpaceX's high-profile IPO at a $2.1T valuation faces scrutiny over fundamentals, with key watchpoints being its likely inclusion in the Nasdaq index and Q2 earnings. Concerns are raised about potential "gamma squeeze" and systemic risks if its narrative-driven valuation gets amplified by passive index funds. Robinhood (HOOD) is noted for breaking its high correlation with crypto, bolstered by its stock trading and new underwriting business. **Web3 & AI:** A warning highlights ~$1.8T in off-balance-sheet AI infrastructure commitments (purchase commitments, leases) as a potential systemic risk if AI monetization lags. AI models are being used for World Cup predictions, adding a new layer for betting markets. A cost breakdown of a $20 AI subscription reveals the supply chain from model companies to cloud, GPUs, and power. **Prediction Markets:** The emergence of prediction market "concept stocks" is noted, with Robinhood developing its own platform, Rothera, signaling a shift from market competition to a "channel war" for user access. **CeFi & DeFi:** The SpaceX IPO tested perpetual contract mechanisms for pre-IPO assets, highlighting challenges in handling corporate actions like stock splits on-chain. The de-pegging of STRC (Strategy's preferred share) to ~$89 reflects market concerns over MicroStrategy's capital structure and BTC-backed leverage model. BlackRock's covered-call Bitcoin ETF (BITA) offers yield but caps upside, appealing to yield-seeking institutions. **Ethereum:** An opinion piece argues Ethereum's core strength is its vast developer community and composability, solidifying its role as the default operating system for the financial internet. **Weekly Hot Topics:** Include the US-Iran deal reopening the Strait of Hormuz, Fed's hawkish hold, Anthropic restricting model access, SpaceX acquiring Cursor, and a humorous stock surge for "Liuliumei" due to its "LLM" ticker.

marsbit31m ago

Weekly Editor's Picks (0613-0619)

marsbit31m ago

Alliance's Co-Founder's Letter to Entrepreneurs: Written on the Occasion of Cursor's $60 Billion Sale

In this letter to entrepreneurs, Alliance reflects on the success of Cursor's $60 billion sale to Elon Musk, using it as a case study to counter the misconception that opportunities in crowded fields like AI or crypto are exhausted. The piece argues that great companies like Cursor, Stripe, Figma, and Shopify are not built by geniuses with perfect ideas, but by founders who start with a non-consensus belief about the future and build for years before that future becomes obvious to everyone. They identify long-term shifts, find overlooked entry points, and execute relentlessly. The framework for success involves: 1. **Identifying your place in the technology cycle**: Early-stage opportunities focus on making new tech usable for power users (e.g., Coinbase, Cursor). Later-stage opportunities involve finding the "yin" to an existing "yang"—the blind spots of first-generation players (e.g., Stripe vs. PayPal, Figma vs. Adobe). 2. **Cultivating unique insights**: Immerse yourself deeply in the market. Use every product, talk to users, and build an audience. Insights will emerge naturally from deep engagement. 3. **Finding a "hair-on-fire" problem**: Look for a 10x improvement or a severe, urgent pain point. The strongest signal is people already building clumsy workarounds. 4. **Building a focused MVP**: Don't just add features because you can. Ask why users would abandon their current tool for yours. The best startups rarely force new behaviors; they improve familiar workflows with drastically lower friction. 5. **Winning a distribution channel**: Distribution is often the moat. Before product-market fit, achieve channel-market fit. Find where your customers are and build an engine to reach them, even through unscalable, manual efforts initially. 6. **Persistence**: The final, unteachable ingredient is resilience. Success stories like Cursor, Airbnb, and Nvidia involved years of grinding, rejection, and perseverance when the path forward seemed unclear. The conclusion is that there is no secret. Most people fail to consistently execute these steps over the long term. The few who do build the companies that define the next era. The world is yours to create.

链捕手37m ago

Alliance's Co-Founder's Letter to Entrepreneurs: Written on the Occasion of Cursor's $60 Billion Sale

链捕手37m ago

Trading

Spot
Futures

Hot Articles

How to Buy CRV

Welcome to HTX.com! We've made purchasing Curve DAO Token (CRV) simple and convenient. Follow our step-by-step guide to embark on your crypto journey.Step 1: Create Your HTX AccountUse your email or phone number to sign up for a free account on HTX. Experience a hassle-free registration journey and unlock all features.Get My AccountStep 2: Go to Buy Crypto and Choose Your Payment MethodCredit/Debit Card: Use your Visa or Mastercard to buy Curve DAO Token (CRV) instantly.Balance: Use funds from your HTX account balance to trade seamlessly.Third Parties: We've added popular payment methods such as Google Pay and Apple Pay to enhance convenience.P2P: Trade directly with other users on HTX.Over-the-Counter (OTC): We offer tailor-made services and competitive exchange rates for traders.Step 3: Store Your Curve DAO Token (CRV)After purchasing your Curve DAO Token (CRV), store it in your HTX account. Alternatively, you can send it elsewhere via blockchain transfer or use it to trade other cryptocurrencies.Step 4: Trade Curve DAO Token (CRV)Easily trade Curve DAO Token (CRV) on HTX's spot market. Simply access your account, select your trading pair, execute your trades, and monitor in real-time. We offer a user-friendly experience for both beginners and seasoned traders.

5.1k Total ViewsPublished 2024.03.29Updated 2026.06.02

How to Buy CRV

Discussions

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

活动图片