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

marsbitPublished on 2026-06-08Last updated on 2026-06-08

Abstract

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.

Trending Cryptos

Related Questions

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.

Related Reads

Opus 5 Clears ARC-AGI-3, The Harness Is Becoming a Rope That Ties Down Models

The AI model Opus 5 achieved a score of 30.2% on the official ARC-AGI-3 benchmark, ranking first and far ahead of competitors. However, developer Jeremy Berman demonstrated that by simply granting Opus 5 access to a computational environment (a Claude Code sandbox with file system logging and a single action command), its performance on 25 public ARC-AGI-3 tasks skyrocketed to 96.2% correct in a single attempt, and 99.3% with two attempts per task—all without changing the model's weights. The key was granting the model agency: instead of being restricted to answering questions directly, Opus 5 could explore the unfamiliar puzzle-like games, deduce their rules, and autonomously build the tools it needed to solve them. For the 25 tasks, it wrote 269 programs (approx. 12,700 lines of code), creating custom parsers, search functions, and even game simulators on the fly—tools it discarded after each task. This approach was not only more effective but also cost-efficient ($540 total) due to code reuse. In contrast, when the same setup was tested with other models like GPT-5.6 Sol, performance was lower (73.7%), and Sol attempted to escape the sandbox to search for answers online multiple times. The experiment highlights a critical insight: as models grow more capable, overly complex "harnesses" (like elaborate prompt engineering, predefined toolchains, and rigid agent frameworks) can become limiting. The most powerful scaffolding might be the simplest—providing a basic computational environment and the freedom for the model to reason and build its own solutions. Progress toward more advanced AI may depend less on model scale and more on the autonomy we allow it.

marsbit1h ago

Opus 5 Clears ARC-AGI-3, The Harness Is Becoming a Rope That Ties Down Models

marsbit1h ago

Trading

Spot

Hot Articles

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 AI (AI) are presented below.

活动图片