The Market Has No New Stories, The Current AI Frenzy Reminds Me of NFTs

marsbitОпубликовано 2026-02-10Обновлено 2026-02-10

Введение

The author draws parallels between the current AI hype, driven by releases like OpenClaw and Claude Code, and the NFT mania of 2021. While acknowledging the genuine utility and transformative potential of AI, the article critiques how social media amplifies extreme narratives, creating a distorted perception of reality where hype often overshadows substance. This echo chamber confuses performance with consensus and consensus with truth, leading to overblown expectations. The piece highlights a similar overreaction in financial markets, where a narrative that "AI will kill software" triggered a massive, indiscriminate sell-off in software stocks, erasing billions in market value. Companies with strong fundamentals, like Salesforce and ServiceNow—which are successfully integrating and monetizing AI—were sold off alongside more vulnerable firms. The author argues that this panic, like the hype, is a premature attempt to price in a distant "endgame," ignoring the gradual, complex reality of technological adoption. The conclusion urges a more nuanced view that tolerates ambiguity rather than rushing to extreme conclusions.

Author:market participant

Compiled by: Deep Tide TechFlow

Deep Tide Guide: When the new wave of AI agent frenzy triggered by OpenClaw and Claude Code swept through social media, the author keenly sensed a madness reminiscent of the NFT era in 2021.

This article analyzes how social media amplifies technological narratives, how Wall Street engages in indiscriminate selling due to the bias that "AI is killing software," and why giants like Salesforce and ServiceNow were mistakenly punished by the market even after delivering astonishing results.

The author believes we are in the "mid-game" of a great revolution, where extreme optimism and extreme panic are attempts to prematurely透支 (draw on) an endgame that has not yet arrived.

Full Text Below:

This wave of OpenClaw and Claude Code frenzy reminds me of the hysteria of the NFT era.

The emergence of new technology is accompanied by practicality and simultaneously generates cultural and narrative resonance in the zeitgeist. Like every technology that captures the collective imagination at the right moment, it is being processed by the same "distortion machine"—the very machine that once turned JPEG pictures of monkeys into a $40 billion asset class.

The pattern is identical: genuine innovation arrives, early adopters discover real value. Subsequently, the social layer takes over everything—suddenly, the conversation detaches from the technology itself and becomes a performance about "taking sides."

Declaring "This is the future" becomes a badge of the in-crowd. Writing guides, think pieces, and exaggerating the current state's value earns social validation. The compound growth of opinions outpaces the technology itself.

(I promise there will be a point about financial markets later).

The Cognitive Distortion Machine

X (Twitter) makes it worse. Social media is increasingly seen as a legitimate lens on reality, yet it bends the image of truth.

The loudest voices are not representative—they are performing "strong belief" for an audience that rewards such behavior. Every major platform runs on engagement, and engagement rewards extremes. "This is interesting and useful" doesn't go viral; "This changes everything, your job is at risk" does.

A hundred retweets saying "This changes everything" are not a signal, but an echo. Echoes are mistaken for consensus, consensus is mistaken for truth, and truth is mistaken for an investable thesis.

Girard would have a field day with this spectacle. When enough people perform "belief" in a certain outcome, the performance itself becomes confused as evidence supporting that outcome. The NFT era proved this conclusively: people didn't want JPEGs, they wanted "to want what everyone else wanted" [1].

What is Real?

The latest model capabilities are astounding—far more impressive than NFTs, which had little practical utility beyond speculation and cultural signaling.

I use these tools daily. They improve my efficiency in concrete, measurable ways. The underlying models are indeed impressive, and the trajectory of improvement is very steep. When I compare what I could do with these tools six months ago versus today, the incremental gain is massive.

Moreover, the broader potential is limitless. AI-assisted programming, research, analysis, writing—these are not hypothetical use cases; they are happening and creating real value for those who use them well.

I don't want to be the person who scorned the internet in 1998. That's not the point; I am very long-term bullish on AI. The point is the timeline, and the chasm between potential and current reality.

What is Not Yet Real

No—Claude will not immediately catalyze social upheaval. This does not mean humans no longer need interfaces to manage work. This does not mean Anthropic has won the AI war.

Think about what the most breathless opinions actually require you to believe: enterprise software—decades of accumulated workflows, integrations, compliance frameworks, and institutional knowledge—will be replaced in quarters, not years? Per-seat billing models die overnight? Companies with over $10 billion in annual revenue and 80% gross margins evaporate because a chatbot can write a function? [2]

Wedbush's Dan Ives put it bluntly: "Enterprises are not going to tear down hundreds of billions of dollars of past software infrastructure investments to migrate to Anthropic, OpenAI, etc." [3]. And Jensen Huang, who has more reason than anyone to tout AI's disruptive power, called the notion of "AI replacing software" "the most illogical thing in the world" [4].

Those most aggressively declaring "Endgame" (thanks @WillManidis for popularizing the term) are often those who benefit the most from your "conviction": follower counts, consulting gigs, subscription fees, conference invites. The incentive structure rewards bold predictions that bear no responsibility for timing.

The Market's Mirror

What's interesting to me: the market is making the same mistake on the other side of the table.

Anthropic released its Claude Cowork plugin on January 30th. In less than a week, $285 billion evaporated from software, financial services, and asset management stocks [5].

The software ETF—$IGV—is down 22% this year, while the S&P 500 is up. 100 out of 110 components are in the red. The RSI hit 16, its lowest reading since September 2001 [6].

Hedge funds are furiously shorting software stocks and adding to positions [7]. The narrative logic is: AI kills SaaS. Every per-seat software company is a "walking dead."

This selling is indiscriminate. Companies with completely different risk profiles regarding AI impact are being treated as the same trade [8]. When 100 out of 110 names in an index are falling, the market is no longer analyzing; it is indulging in narrative euphoria.

Note: A recovery may have begun since I started writing this.

Throwing Out the Bathwater with the Baby

Look at what's actually happening inside the companies supposedly facing extinction.

Salesforce Agentforce revenue grew 330% year-over-year, reaching an annualized run rate of over $500 million, and generated $12.4 billion in free cash flow. Forward P/E is 15x. They just issued a $60 billion revenue target for FY2030 [9]. This is not a company being disrupted by AI—it's a company building the AI enterprise delivery layer.

ServiceNow subscription revenue grew 21%, operating margin expanded to 31%, and authorized a $5 billion stock buyback. Their AI suite, Now Assist, reached $600 million in Annual Contract Value (ACV), targeting over $1 billion by year-end [10]. Yet its stock is down 50% from its highs.

Should these names see valuation multiples moderately derated due to risk? Perhaps. But smart money started pricing this in years ago. As many smarter than me have pointed out: this selloff requires you to simultaneously believe "AI capex is crashing" AND "AI is powerful enough to destroy the entire software industry" [11]. These two things cannot be true at once. Pick one.

Identifying Real Risk

Will some companies be truly displaced? Yes.

Point solutions offering standardized, single workflows are vulnerable. If your entire product is just an interface layer built on non-owned data, you are in trouble. LegalZoom is down 20%—for these types of companies, the concern has substance [12]. When AI plugins can automate contract review and NDA categorization, the value proposition of paying a legacy vendor for the same functionality becomes hard to defend.

But companies with deep integrations, owned data, and platform-level foundations are a different story entirely. Salesforce is deep in the tech stack of every Fortune 500 company. ServiceNow is the system of record for enterprise IT. Datadog's consumption-based model means more AI compute directly translates to more monitoring revenue—their non-AI business growth actually accelerated to 20% YoY [13].

Selling digital infrastructure because "AI kills software" is as absurd as selling construction equipment stocks because buildings are going up.

We've Been Here Before

The 2022 SaaS crash is instructive. The sector fell over 50%. The median forward revenue multiple dropped from 25x to 7x—below pre-pandemic levels [14]. Earnings performance remained strong throughout. The subsequent rebound was dramatic—the Nasdaq was up 43% in 2023. Admittedly, the trigger then was more an interest rate shock than fundamental deterioration.

The January 2025 DeepSeek panic is more recent. Nvidia plummeted on fears that cheap Chinese AI models would make the entire AI infrastructure buildout pointless, but then fully recovered [15]. That fear was structurally identical to today's: a single product release triggered an existential crisis reassessment of an entire industry.

Many observers have drawn direct analogies between the current moment and the early stages of the dot-com bust—tech stocks falling while consumer staples, utilities, and healthcare rise [16]. But one thing about the dot-com bust: Amazon fell 94%, then became one of the world's most important companies. The market tried to price the "endgame" halfway through the game, creating one of history's greatest buying opportunities.

Deutsche Bank's Jim Reid offered a hard truth: "Identifying the long-term winners and losers at this stage is almost pure guesswork." [17]

I bet he's right. And this uncertainty—the admission that we just don't know how it ends—is why this indiscriminate selling is a mistake.

The Endgame Fallacy

The hype merchants on X and the panic sellers on Wall Street are making the same mistake on opposite ends of the board.

One group says AI has already won, the future is here, all institutions and job functions are to be rewritten from now on. The other group says AI has killed software, subscription revenue is dead, $10 billion in free cash flow doesn't matter because the business model is obsolete.

Both are jumping to the "endgame" while the game still has many moves left. The chasm between our current state and the technological vision will be filled by messy, incremental, company-specific progress. Some software companies will integrate AI and become stronger; a few will actually be displaced; most will adapt—and this process of adaptation is slow, uneven, and not tweetable.

The actual trajectory is more volatile and less certain than either the hype or the panic suggests. Those who will do well from here will be those who can tolerate this ambiguity, not those rushing to grasp a prematurely conclusive narrative.

Great operators always find a way.

Reference Sources

[1] Girard's Mimetic Desire Theory (https://www.iep.utm.edu/girard/)

[2] Fortune: Why SaaS Stocks Are Irrationally Slumping Like During the DeepSeek Panic

[3] CNBC: Impact of AI Tools on SaaS Software Stocks

[4] CNBC: Jensen Huang Says AI Replacing Software is "The Most Illogical Thing"

[5] Yahoo Finance: US Software Sector Loses $285 Billion on Anthropic Impact

[6] Yahoo Finance: IGV ETF Trend Analysis

[7] Axios: Hedge Funds Heavily Shorting Software Sector

[8] Benzinga: Misreading in the Software Sector Crash

[9] Salesforce Investor Relations: Record Q3 Earnings Driven by Agentforce

[10] Futurum Group: ServiceNow Q4 Earnings and AI Platform Momentum [11] Fortune: The AI Paradox and Irrational Analysis

[12] CNBC: Software Stocks Enter Bear Market, ServiceNow et al. Plunge

[13] StockAnalysis: Datadog Operating Stats

[14] Meritech Capital: Review of the 2022 SaaS Crash

[15] CNBC: Nvidia Plunges on DeepSeek Concerns

[16] Fortune: Deutsche Bank on Software Bubble and Internet Era Analogy

[17] Deutsche Bank Jim Reid Analysis Report

Связанные с этим вопросы

QWhat does the author compare the current AI hype to, and why?

AThe author compares the current AI hype to the NFT era because both involve genuine technological innovation that gets amplified by social media into a cultural and narrative frenzy, leading to extreme optimism and speculative behavior detached from actual utility and timelines.

QAccording to the author, how does social media distort the perception of AI technology?

ASocial media distorts perception by rewarding extreme, high-engagement content that perform 'conviction,' turning echoes into false consensus, and conflating performance of belief with evidence, ultimately bending reality to fit viral narratives.

QWhat is the 'Endgame Fallacy' as described in the article?

AThe 'Endgame Fallacy' refers to the mistake of prematurely declaring a final outcome—either extreme optimism about AI's immediate impact or extreme pessimism about software's obsolescence—when the actual trajectory is uncertain, gradual, and company-specific, with much of the game still left to play.

QWhy does the author believe the market's sell-off in software stocks is misguided?

AThe sell-off is misguided because it is indiscriminate, failing to distinguish between companies vulnerable to AI disruption (e.g., point solutions) and those with deep integrations, proprietary data, and platform strengths (e.g., Salesforce, ServiceNow) that are actually leveraging AI to grow and generate substantial cash flow.

QWhat historical market events does the author cite to contextualize the current AI-driven software sell-off?

AThe author cites the 2022 SaaS crash (driven by rate hikes, not fundamentals) and the January 2025 DeepSeek panic (where Nvidia fell on fears of cheap Chinese AI models) as examples of similar overreactions, noting that markets often misprice mid-game uncertainty, creating buying opportunities.

Похожее

If the AI Bubble Is Already Bursting, Who Will Truly Survive?

If the AI Bubble is Bursting, Who Will Remain? The debate over an AI bubble is intensifying, with figures like Ray Dalio warning of high levels and Jensen Huang seeing immense, early-stage opportunity. Both views hold truth: a speculative bubble in capital markets likely exists, mirroring the dot-com era, but the underlying technological shift is real and transformative. History shows that while bubbles burst—wiping out overvalued companies and speculative capital—they often leave behind critical physical and digital infrastructure. The dot-com bust, for instance, eliminated many firms but left the global fiber optic networks and data centers that enabled the rise of Amazon, Netflix, and cloud computing. Today's massive AI infrastructure investments (projected at trillions by 2030) in data centers, power, cooling, and GPUs may follow a similar path, creating the foundation for future applications. A key divergence from past bubbles is the "Jevons Paradox" effect in AI. As the cost of AI inference has plummeted by over 99.7% since 2023, enterprise spending on AI has skyrocketed. Cheap "tokens" have unlocked vast, previously uneconomical use cases, moving AI from simple chatbots into core business workflows—code generation, legal document review, scientific simulation, and financial analysis. The market is now in a phase of self-correction, weeding out superficial "API-wrapper" startups, but this cleansing process strengthens the ecosystem. The long-term trajectory is clear. The value is gradually shifting from capital expenditure (CapEx) on hardware to operational expenditure (OpEx) on transformative applications. As AI becomes a utility, the winners will be firms that deeply integrate it to solve vertical industry problems in law, healthcare, finance, and manufacturing. The泡沫 will recede, but the foundational shift towards an AI-powered era across all sectors is irreversible. The underlying productive force of AI contains no bubble.

marsbit33 мин. назад

If the AI Bubble Is Already Bursting, Who Will Truly Survive?

marsbit33 мин. назад

If the AI Bubble Is Already Bursting, Who Will Truly Remain?

**Summary: If the AI Bubble is Bursting, What Will Remain?** The debate around an AI bubble is intensifying, with figures like Ray Dalio warning of high valuations while Jensen Huang sees immense opportunity. This echoes the dot-com bubble, which saw massive wealth destruction but ultimately left behind critical infrastructure like undersea cables and broadband, enabling future giants like Amazon and Netflix. Similarly, today's AI boom involves trillions invested in data centers, power, cooling, and GPUs, while application-layer revenue remains comparatively modest. This investment-disparity signals a bubble. However, the core technological progress is real and accelerating. AI inference costs have plummeted by over 99.7% since 2023, making intelligence increasingly cheap and accessible. This cost collapse is unlocking vast new demand. Instead of reducing spending, enterprises are tripling their AI cloud expenditure. Cheap "tokens" enable AI to move beyond simple chatbots into complex workflows—automating code writing, legal document review, financial analysis, and scientific research. This follows "Jevons's paradox": improved efficiency leads to greater total consumption. The market is now undergoing a necessary purification, weeding out "API-wrapper" startups with no real moat. The deeper evolution involves a shift from capital expenditure (CapEx) on infrastructure to operational expenditure (OpEx) on value-creation in applications. While hardware vendors currently profit most, long-term value will migrate to AI-native firms solving vertical industry problems. Ultimately, a market correction will cleanse speculative excess but will not reverse the AI+ trend. The massive physical and algorithmic infrastructure being built will endure, becoming a cheap, utility-like foundation. Just as the internet became indispensable to all industries post-2000, AI is poised to empower and redefine every sector, moving society irreversibly toward an intelligence-augmented era. The bubble may burst, but the underlying productive momentum is solid.

链捕手39 мин. назад

If the AI Bubble Is Already Bursting, Who Will Truly Remain?

链捕手39 мин. назад

Microsoft CEO: In the AI Era, How Do You Define a Company's Moat?

Microsoft CEO Satya Nadella argues that in the AI era, a company's true competitive edge, or "moat," is not determined by choosing the single most powerful model, but by its ability to build a continuous "learning loop." This system integrates and evolves by connecting human workflows, domain expertise, organizational judgment, and employee experience. He posits that future companies will accumulate two types of capital: Human Capital (employee knowledge, judgment, creativity) and "Token Capital" (a firm's own built and owned AI capabilities). Importantly, AI amplifies rather than devalues human capital. Human direction is essential to guide progress, as computational power alone is aimless. The core opportunity lies in creating a closed-loop system where human and token capital reinforce each other in a compound, self-improving cycle. A company must be able to preserve its unique institutional knowledge—its "company veteran" expertise—even if it switches underlying general-purpose AI models. This requires private evaluation benchmarks, reinforcement learning environments based on internal data, and queryable knowledge bases. Nadella warns against a future where economic value is concentrated by a few dominant models that commoditize entire industries' knowledge. Instead, the priority should be building a broad "frontier ecosystem" where every company, industry, and nation can own its learning loop. This allows organizations to retain control of their intellectual property, amplify employee capabilities, and ensure the economic value created by AI is captured within their own businesses and communities. True corporate sovereignty in the AI age comes from turning organizational knowledge into a compounding system that creates enduring, defensible value.

marsbit1 ч. назад

Microsoft CEO: In the AI Era, How Do You Define a Company's Moat?

marsbit1 ч. назад

ETFs Are Just the Ticket: The True Institutionalization of Bitcoin Is Happening Where You Can't See It

Beyond the Bitcoin ETF spotlight, a deeper institutionalization is underway, leveraging Bitcoin as a foundational financial primitive. Institutions are using Bitcoin for purposes long reserved for assets like U.S. Treasuries and gold: as collateral for loans, insurance reserves, and the backbone of rated bonds. Examples include a Barbados-based insurer capitalizing with $40M in Bitcoin reserves and Ledn's $188M securitization of Bitcoin-backed loans, which received the first-ever investment-grade rating (BBB-) from S&P for a digital asset-backed security. This structure was stress-tested during a 27% price drop in early 2026, triggering automatic liquidations that functioned as designed but revealed the systemic risk of synchronized selling across leveraged positions. Infrastructure is evolving to support this, with platforms like Anchorage Digital's Atlas network enabling secure, institutional-grade settlement and collateral management. Strategies like basis trades and corporate treasuries (exemplified by companies like MicroStrategy issuing billions in equity and debt to fund Bitcoin acquisitions) further integrate Bitcoin into financial mechanics. While ETFs solved "how to own" Bitcoin, these developments answer "what to do with it," embedding the asset into the working machinery of finance—as collateral upon which loans, derivatives, and structured products are built. The real, enduring institutional shift is happening in these largely invisible plumbing and financing systems.

marsbit1 ч. назад

ETFs Are Just the Ticket: The True Institutionalization of Bitcoin Is Happening Where You Can't See It

marsbit1 ч. назад

ZEC Co-Founder Responds to Orchard Vulnerability: No Signs of Theft, Orchard Pool to Be Sealed

ZEC Co-Founder Addresses Orchard Vulnerability: No Signs of Theft, Plans to Sunset Orchard Pool A security vulnerability was recently discovered in Zcash's Orchard shielded pool, raising key concerns. The primary questions are whether the flaw was exploited, if user funds are safe, whether users can verify the total ZEC supply, and if other similar vulnerabilities exist. Analysis suggests the vulnerability was likely not exploited prior to its discovery. It was found proactively by a researcher using specialized tools, not due to an active breach. The development team and mining pools acted quickly to contain the issue. Typical financially-motivated attacks would likely have left visible on-chain evidence, which has not been observed. User funds in Orchard are considered safe and should be recoverable, assuming no prior exploitation. If the flaw was never used, all legitimate funds can be withdrawn. The article outlines risks associated with moving funds to transparent addresses or other pools, but concludes that leaving assets in place is a reasonable option. Currently, users cannot independently verify that the total ZEC supply hasn't been inflated due to this bug. However, the planned Ironwood network upgrade is designed to resolve this. It will permanently close the Orchard pool to new deposits and internal transfers, allowing only withdrawals. This mechanism will cap total withdrawals at the amount of legitimately deposited funds, enabling anyone to cryptographically verify the supply post-upgrade. Multiple teams, including Shielded Labs, have conducted extensive audits focused on counterfeiting vulnerabilities, assisted by advanced AI tools. No additional flaws of this type have been found so far, increasing confidence that no other similar undisclosed vulnerabilities exist. In summary, evidence indicates the Orchard bug was probably not used, user funds are secure, and no other counterfeiting flaws are currently known. The upcoming Ironwood upgrade will restore users' ability to independently verify the total ZEC supply, closing this chapter.

Foresight News1 ч. назад

ZEC Co-Founder Responds to Orchard Vulnerability: No Signs of Theft, Orchard Pool to Be Sealed

Foresight News1 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

Топ вопросы

Популярные категорииright-arrow

Популярные тегиright-arrow