Ansem: I Disagree That Crypto is Over, Bullish on AI and Small Team Startups

marsbitОпубликовано 2026-06-08Обновлено 2026-06-08

Введение

Crypto analyst Ansem argues that crypto is maturing, not dying, despite poor performance of major tokens like BTC and ETH. Key structural trends with staying power are stablecoins, perpetual contracts, and tokenization, as proven by projects like Hyperliquid. BTC's current stagnation is attributed to temporary issues like its "pyramid-like" tendencies from corporate strategies and quantum computing concerns, not industry failure. Ethereum and other L1s struggle as their tokens rely on "future growth" narratives rather than capturing real revenue from applications built on them. However, Ansem sees strong reasons for optimism. Regulatory improvements are lowering barriers for crypto entrepreneurs, while traditional firms like Robinhood and Stripe are adopting blockchain. Although AI and tech stocks have recently outperformed crypto, several crypto tailwinds are underestimated: the rise of competitive open-source AI, easier startup creation for small teams using software, and blockchain/stablecoins being superior infrastructure for AI agent transactions. Combined with improving regulation and potential for renewed retail speculation, these factors suggest a future with more, not fewer, crypto experiments and token innovations.

Author: Ansem

Compiled by: Deep Tide TechFlow

Deep Tide Guide: When market sentiment is low, BTC consolidates at highs, and ETH remains under pressure, voices proclaiming crypto is 'finished' are once again growing louder. In this thread, renowned trader Ansem offers a rebuttal: poor performance of major coins ≠ industry decline. Stablecoins, perpetual contracts, and tokenization are the real structural narratives. For investors still hesitating on how to allocate assets, this is a long-term framework worth serious consideration.

Disagree. Crypto is simply going through a maturation phase.

Themes like stablecoins, perpetual contracts, and tokenization will continue to penetrate the global economy, and many successful crypto startups will emerge.

Hyperliquid is just the first, a great example of how powerful the combination of open blockchains and business tokenization can be—there will be many more.

The core of the current crypto market sentiment issue lies in the poor performance of mainstream large-cap coins. BTC went from $0.01 to $100,000 per coin in less than twenty years; in resisting the sustained decline of the US dollar's purchasing power, it has actually accomplished its mission quite successfully. The problem Bitcoin faces now is the 'Ponzi-esque' tendency brought about by Saylor's strategy, which is temporary. I believe BTC will not see significant trending gains again until this issue is resolved. Furthermore, quantum computing concerns are real. These two points, plus the exit liquidity from institutions, are sufficient reasons for BTC OGs to derisk their excessive liquidity—we have already seen specific cases, like the large OTC trade handled by Galaxy (completing a $9 billion sale for a single entity in 2025). There are many similar individuals whose holdings are already in a state of infinite profit.

But after outperforming every asset on Earth for over a decade, BTC underperforming for a few more years does not mean crypto is dead—that's an absurd notion.

Ethereum is also suffering for its own unique reasons. I feel I've talked enough about this, but indeed, it's being competitively suppressed by new entrants and has also failed to turn ETH into a good long-term holding asset. All L1s are struggling on the demand side because historically, the story for these tokens was 'future growth,' not real revenue. But now Hyperliquid has tangibly proven that a business can be directly linked to an L1 token, which puts previous L1s in a passive position—they capture too little revenue from applications built on their infrastructure. Ethereum's situation is worse because it also outsources execution activity to Rollups.

But this, likewise, does not mean there won't be more successful crypto startups.

There is a very clear trend of improving crypto regulation, which will significantly lower the barrier for entrepreneurs to build crypto businesses. At the same time, existing tech companies are also acknowledging the advantages of blockchain, as evidenced by Robinhood and Stripe/Tempo.

AI has captured a massive amount of attention that originally belonged to crypto, and since the late 2022 bottom, tech stocks have performed far better than crypto. As a trader, allocating time between stocks and crypto is extremely wise. In the past, if you were willing to take risks, it was reasonable to overweight crypto—it was an emerging industry experiencing supernormal returns as it went mainstream.

Looking ahead, as AI models progress exponentially in the coming years, there are three underestimated crypto tailwinds:

1) Open-source AI will become more competitive with closed-source AI.

2) Small teams will find it easier to build successful startups using software.

3) Stablecoins and blockchain are superior infrastructure for AI agents to transact.

The convergence of these trends means you might see more, not fewer, crypto experiments and token innovations—especially against the backdrop of continuously improving regulation and retail speculation becoming the next major trend.

Связанные с этим вопросы

QWhat are the three long-term structural narratives in crypto that Ansem identifies as continuing to penetrate the global economy?

AAnsem identifies stablecoins, perpetual futures contracts, and tokenization as the three structural narratives that will continue to permeate the global economy.

QWhat two specific issues does Ansem mention as reasons for Bitcoin's lack of a clear upward trend?

AAnsem mentions two issues: the 'ponzi-fication' tendencies resulting from actions like those of Michael Saylor, and concerns about quantum computing.

QWhy does Ansem believe the current poor performance of major cryptocurrencies does not signal the end of crypto?

AHe believes it is a phase of maturation. The underlying structural narratives like stablecoins and tokenization are still advancing, regulatory clarity is improving, and new successful crypto startups will emerge, exemplified by projects like Hyperliquid.

QWhat three underestimated crypto tailwinds does Ansem link to the exponential progress of AI models in the coming years?

AThe three tailwinds are: 1) Open-source AI becoming more competitive with closed-source AI. 2) Small teams finding it easier to build successful startups using software. 3) Stablecoins and blockchains being superior infrastructure for AI agents to conduct transactions.

QAccording to Ansem, what is the fundamental problem with the traditional Layer 1 (L1) token narrative that Hyperliquid's success exposes?

AThe traditional L1 narrative was based on 'future growth' promises rather than capturing real revenue. Hyperliquid demonstrated that a business can be directly linked to an L1 token, making other L1s passive as they capture too little revenue from applications built on their infrastructure.

Похожее

AI Investors' 2026 Anxiety: When Models Devour Everything, What Moat Is Left for Startups?

In 2026, a wave of investor anxiety questions the defensibility of AI startups as models improve, fearing that most companies are just "thin wrappers" destined to be absorbed by foundation models or chipmakers. The author argues against this despair, positing that true moats lie not in benchmark performance but in areas models cannot easily reach. The logic of despair is that if models excel at all measurable tasks, only compute and cutting-edge model weights hold lasting value. However, the essay contends that the most valuable work is inherently "untrainable." Benchmarks measure what can be measured and thus optimized for, but real-world correctness often resides in private, complex systems. Examples include legacy codebases, intricate legal transactions, or hospital workflows. This kind of correctness is proprietary, costly to establish, and cannot be validated quickly—it requires time and trust within an organization. As models commodify visible, measurable tasks from both above (labs absorbing scaffolding) and below (saturation by cheaper models), value shifts to "untrainable ground." This encompasses work where correctness is a private truth, locked behind integration barriers, licenses, liability frameworks, and entrenched user habits. Trust and adoption are slow, human-centric processes that smarter models cannot accelerate. Successful companies defend their position by embedding deeply into client operations, owning the definition of "good" within a specific domain (e.g., Harvey in law, OpenEvidence in medicine), and pricing on outcomes rather than tokens. While labs compete fiercely, they are incentivized to keep the application layer vibrant. The future belongs not to those competing on generic benchmarks but to those navigating unscoreable terrain, doing the "unsexy work" of translation between models and messy human realities. The most cited benchmark scores are thus maps of territory about to become worthless, signaling who will lose the right to define what counts as good.

marsbit29 мин. назад

AI Investors' 2026 Anxiety: When Models Devour Everything, What Moat Is Left for Startups?

marsbit29 мин. назад

Trump's Crypto Empire: A $2.3 Billion Wealth Transfer Experiment

In June 2026, Reuters investigations revealed that since Donald Trump's return to the White House, his family has accumulated roughly $2.3 billion in profits from four core crypto ventures: World Liberty Financial (WLFI), the $TRUMP meme coin, American Bitcoin, and ALT5 Sigma (later renamed AI Financial). Coincidentally, overall investor losses in these projects were estimated to be a similar amount. The businesses, spanning DeFi, stablecoins, meme coins, Bitcoin mining, and digital payments, largely relied not on technological innovation but on converting the political influence and notoriety of the Trump brand into financial assets sold to the market. This marks a dramatic shift from Trump's earlier skepticism of cryptocurrencies. The ventures operated on a similar logic: leveraging the Trump name to generate market hype and trust, attracting investment through token sales or public listings, and enabling the family to capture profits upfront through equity, token allocations, and fees, while later entrants often bore the brunt of the risk as markets cooled. WLFI, the most profitable venture, generated an estimated $1.6 billion for the family, primarily through sales of its locked, illiquid governance token and its USD1 stablecoin. The $TRUMP meme coin, a direct monetization of the presidential IP, brought in over $600 million for Trump-linked entities before its price crashed nearly 97% from its peak. American Bitcoin gained a "Trump stock" premium for its mining operations, and ALT5 Sigma/AI Financial combined Trump, AI, and crypto themes for a temporary valuation surge. The episode underscores how political influence can be packaged into financial assets, creating substantial wealth for promoters while highlighting the risks for investors who base decisions on hype and brand allegiance over fundamental business models and cash flows.

marsbit1 ч. назад

Trump's Crypto Empire: A $2.3 Billion Wealth Transfer Experiment

marsbit1 ч. назад

CFTC Proposes New Rules for Prediction Markets, Redefining Which Events Can Be Listed and Who Can Participate

The U.S. Commodity Futures Trading Commission (CFTC) has proposed new rules to establish a clearer regulatory framework for prediction markets. The proposal aims to modify how "event contracts" are reviewed, creating a structured process to determine if contracts involving terrorism, assassination, war, or illegal activities violate the public interest. This moves away from a blanket ban toward a case-by-case assessment of whether a contract's subject matter is acceptable for financial trading. A key focus is distinguishing between predicting the impact of risks and predicting the occurrence of harm. The proposal suggests that many sports-based prediction markets—such as those on game outcomes, scores, or season standings—may be permissible as they can provide price discovery and meaningful information. However, markets on easily manipulated events like specific player injuries, referee calls, or outcomes of youth sports would face stricter scrutiny. The rules directly target insider trading and manipulation risks, highlighting cases where individuals with non-public information or the ability to influence an event's outcome could unfairly profit. This underscores a shift toward ensuring market fairness. The proposal does not end the regulatory debate, particularly with state gambling regulators who argue that sports prediction markets are essentially sports betting and should fall under state jurisdiction. Nonetheless, the CFTC's action signals a move toward formalizing prediction markets, pushing the industry from a phase of rapid, often unregulated expansion into a more institutionalized, rule-based environment that more closely resembles traditional financial markets.

marsbit1 ч. назад

CFTC Proposes New Rules for Prediction Markets, Redefining Which Events Can Be Listed and Who Can Participate

marsbit1 ч. назад

Торговля

Спот
Фьючерсы

Популярные статьи

Неделя обучения по популярным токенам (2): 2026 может стать годом приложений реального времени, сектор AI продолжает оставаться в тренде

2025 год — год институциональных инвесторов, в будущем он будет доминировать в приложениях реального времени.

1.8k просмотров всегоОпубликовано 2025.12.16Обновлено 2025.12.16

Неделя обучения по популярным токенам (2): 2026 может стать годом приложений реального времени, сектор AI продолжает оставаться в тренде

Обсуждения

Добро пожаловать в Сообщество HTX. Здесь вы сможете быть в курсе последних новостей о развитии платформы и получить доступ к профессиональной аналитической информации о рынке. Мнения пользователей о цене на AI (AI) представлены ниже.

活动图片