深度调查 100+ 小时:探索 90% 项目 TGE 失败的真正原因

marsbit2025-11-13 tarihinde yayınlandı2025-11-14 tarihinde güncellendi

在过去两年中,我与超过30个处于TGE(代币生成事件)前阶段的项目合作,我发现了3个导致大多数代币在TGE时惨败的、意想不到的原因。

那些筹集了数百万美元的项目,却在重复着同样的错误。这就是我发现的规律:

  • TGE 失败的项目不会公开分享这些,因为他们正忙着互相指责。
  • TGE 成功的项目也不会分享,因为他们想独占所有功劳。

这使得新项目方(创始人)陷入了一个不知道究竟该怎么做的尴尬境地。

那么,究竟什么是 TGE 最重要的部分?如果没有它们,你的 TGE 必败无疑——因此你也最应该把时间花在这些事情上?

作为一家营销公司的创始人,说出这个事实很伤人,但答案不是营销

营销能放大良好的基本面,但如果没有这个根基,整个纸牌屋终将倒塌。

以下是3个在 TGE 时扼杀项目、但却鲜为人知的因素:


1. 做市商 (Market Makers)

选择做市商基本上就是在玩俄罗斯轮盘

  • 最好情况: 他们与你有共同的激励机制,并分享利润(如果有的话)。
  • 最坏情况: 他们在背后**“Rug”你(坑你)**,你几年的心血将付诸东流。

这种信息不对称非常可怕,因为他们只会分享成功案例,绝口不提失败的。

那你该如何选择做市商?

99.9%的情况下,他们必须是由某个项目方、或某个你信任且与他们直接合作过的人强烈推荐的。

不要相信随便什么人,因为他们能从做市商那里拿到丰厚的推荐费(返佣),所以即使做市商很烂,他们也有动力去推荐。

请记住: 如果你失败了,那是的问题,不是他们的问题。

你可以拥有有史以来最好的营销、社区和团队,但如果做市商把你的K线砸了50%,你将束手无策。


2. 代币经济模型 (Tokenomics)

同样的原则也适用于代币经济模型,因为你和你的团队大概率没有操盘过50个代币模型并亲眼见过它们的结果。

不能简单地复制粘贴一个成功项目的代币模型,并指望它对你同样有效。

投资者的目标和“胃口”在变,如果你想吸引买压(buying pressure),你必须随之改变。

在这里,你的顾问同样只会向你展示他们最成功的案例,而那些已经归零的一个也不会让你看见。

额外附送一个“辣评”(Hot take): 如果当前的代币经济模型注定要让你的项目完蛋,你就应该立刻修改它

我才不管:

  • 空投“羊毛党”会不会生气
  • 推特时间线上那群“喷子”会不会不爽
  • 种子轮投资者会不会发疯

如果代币模型的现状意味着一周后下跌90%,他们依旧会不爽,唯一的区别是,你的公司将在三个月内倒闭。

显然,从一开始就避免陷入那种境地是最好的解决方案,但正如一句古老的拉丁谚语所说:

“非常时期,需行非常之策” (Desperate times call for desperate measures)


3. 交易所上币 (Exchange Listings)

这是我最“喜欢”的一条。

如果说做市商和代币模型只是在 TGE 之后才让你痛苦,那么与交易所打交道是 TGE 之前最痛苦和最危险的活动。

为什么痛苦:

  • 他们很难沟通
  • 很难在统一的时间线上协调一致
  • 你经常不得不推迟 TGE,因为他们在最后一刻改变了主意

为什么危险:

  • “掠夺性”的条款会毁了你的项目
  • 很多人被“假代表”诈骗
  • 花费数百万美元,换来的只是抛压(selling pressure),而不是买压(buying pressure)

解决这个问题最快的方法,是认识在这些交易所有内部人脉的人,并掌握一个成本基准(benchmark),这样你才不会被当成“冤大T头”(ripped off)。

由于这种信息不对称,许多团队在简单的谈判中就浪费了数十万美元。


结语

每个人都在等待更好的市场行情(market conditions)再进行 TGE,但如果你在上述三点上失败了,没有任何市场行情能让你的代币起死回生

作为创始人,你应该主要操心这三点,同时监督优秀的团队成员在其他垂直领域执行。

İlgili Okumalar

Nearly a Hundred Players Rush into Embodied Data: With 4.47 Billion Yuan in Financing in One Year, Who Can Really Make Money by 'Selling Data'?

The domestic embodied AI data industry has attracted nearly 100 players, with 70 focused on data collection and 27 on data infrastructure. In the past year, 15 independent embodied data service providers raised approximately 4.47 billion yuan. Despite this growth, the sector remains early-stage, fragmented, and faces significant challenges. Data collection methods are diverse, categorized into four main routes: teleoperation of real robots, human demonstration without a robot (using motion capture, exoskeletons, etc.), simulation synthesis, and distillation from internet videos. Most companies (43%) adopt hybrid approaches, combining multiple routes, as no single method can meet all training needs. Teleoperation alone is pursued by 31% of players, often by state-owned platforms and robot companies, while newer firms favor asset-light, no-hardware human demonstration. Independent data service providers now form the largest player group (40%), indicating the emergence of a distinct industry segment rather than just a subsidiary function for robot makers. Two-thirds of all players are "embodied-native" startups, while one-third are companies that pivoted from fields like AI data annotation, which are more prevalent in the data infrastructure layer. Current annual industry capacity is estimated at 1.6-1.8 million hours plus 70-80 million data points, with a short-term goal to increase this 15-20 fold within 1-3 years. Data collection factories are spread across 20 provinces in China, concentrated in the Yangtze River Delta, Beijing-Tianjin-Hebei, and Pearl River Delta regions. Financially, the 4.47 billion yuan raised in the past year pales compared to the 43.8 billion yuan raised by the broader embodied intelligence sector in just the first half of 2026, highlighting that data remains a less "sexy" bet for investors. The 15 funded independent providers show clear stratification: a top tier led by a unicorn (Lightwheel Intelligence, 3.1 billion yuan), a middle tier of 11 firms raising tens to hundreds of millions, and an early-stage tier of 3 companies. Sixty-nine investment institutions have participated, but none have made concentrated bets, reflecting uncertainty about viable business models. Over half of these funded companies are less than a year old, most are at pre-A or A rounds, and profitability remains largely unproven. In summary, the embodied data industry has become an independent track creating jobs and local economic activity. However, it is still nascent, with unformed consensus, unsolved problems, and unproven business models. The coming 1-2 years will be a critical validation window to see if companies can build sustainable, profitable businesses purely by "selling data."

marsbit52 dk önce

Nearly a Hundred Players Rush into Embodied Data: With 4.47 Billion Yuan in Financing in One Year, Who Can Really Make Money by 'Selling Data'?

marsbit52 dk önce

Dialogue with Multicoin Partner: The Crypto Market Has Bottomed Out, Favoring Three Cryptocurrencies in This Cycle

In a recent interview, Multicoin Capital managing partner Tushar Jain shared his views on the crypto market. He believes the market has bottomed and is at an inflection point, citing that negative news no longer causes significant price declines and application adoption continues to grow. Jain remains highly bullish on Solana, viewing it as the correct architectural choice for internet capital markets, particularly for spot and tokenized security trading. He is also positive on Hyperliquid, noting its leadership in decentralized derivatives trading. His investment approach focuses on concentrating capital in top convictions rather than equal allocation. A distinct opportunity he highlights is Zcash (ZEC), which he sees as a return to the industry's cypherpunk ethos and a potential top-five asset by market cap. For assets like Zcash without cash flows, his valuation framework is based on relative market cap ranking. Regarding investment strategy, Jain employs a "three-part" entry method to avoid timing pitfalls and emphasizes long-term "active management" over "active trading." He outlines four sources of investment edge: informational, analytical, behavioral/psychological, and structural. On portfolio management, the fund uses Bitcoin as its "cash," selling assets into Bitcoin during market euphoria to reduce beta risk and using Bitcoin to buy dips. Sales occur only if a better opportunity arises, the investment thesis breaks, or valuations become excessively overheated. While respectful of Ethereum's resilience, he questions its unclear scaling roadmap. Finally, Jain reaffirms his commitment to the thesis that blockchains will form the foundational architecture for future capital markets.

marsbit1 saat önce

Dialogue with Multicoin Partner: The Crypto Market Has Bottomed Out, Favoring Three Cryptocurrencies in This Cycle

marsbit1 saat önce

İşlemler

Spot
活动图片